Market Electromagnetic Field [The_lurker]Market Electromagnetic Field
An innovative analytical indicator that presents a completely new model for understanding market dynamics, inspired by the laws of electromagnetic physics — but it's not a rhetorical metaphor, rather a complete mathematical system.
Unlike traditional indicators that focus on price or momentum, this indicator portrays the market as a closed physical system, where:
⚡ Candles = Electric charges (positive at bullish close, negative at bearish)
⚡ Buyers and Sellers = Two opposing poles where pressure accumulates
⚡ Market tension = Voltage difference between the poles
⚡ Price breakout = Electrical discharge after sufficient energy accumulation
█ Core Concept
Markets don't move randomly, but follow a clear physical cycle:
Accumulation → Tension → Discharge → Stabilization → New Accumulation
When charges accumulate (through strong candles with high volume) and exceed a certain "electrical capacitance" threshold, the indicator issues a "⚡ DISCHARGE IMMINENT" alert — meaning a price explosion is imminent, giving the trader an opportunity to enter before the move begins.
█ Competitive Advantage
- Predictive forecasting (not confirmatory after the event)
- Smart multi-layer filtering reduces false signals
- Animated 3D visual representation makes reading price conditions instant and intuitive — without need for number analysis
█ Theoretical Physical Foundation
The indicator doesn't use physical terms for decoration, but applies mathematical laws with precise market adjustments:
⚡ Coulomb's Law
Physics: F = k × (q₁ × q₂) / r²
Market: Field Intensity = 4 × norm_positive × norm_negative
Peaks at equilibrium (0.5 × 0.5 × 4 = 1.0), and decreases at dominance — because conflict increases at parity.
⚡ Ohm's Law
Physics: V = I × R
Market: Voltage = norm_positive − norm_negative
Measures balance of power:
- +1 = Absolute buying dominance
- −1 = Absolute selling dominance
- 0 = Balance
⚡ Capacitance
Physics: C = Q / V
Market: Capacitance = |Voltage| × Field Intensity
Represents stored energy ready for discharge — increases with bias combined with high interaction.
⚡ Electrical Discharge
Physics: Occurs when exceeding insulation threshold
Market: Discharge Probability = min(Capacitance / Discharge Threshold, 1.0)
When ≥ 0.9: "⚡ DISCHARGE IMMINENT"
📌 Key Note:
Maximum capacitance doesn't occur at absolute dominance (where field intensity = 0), nor at perfect balance (where voltage = 0), but at moderate bias (±30–50%) with high interaction (field intensity > 25%) — i.e., in moments of "pressure before breakout".
█ Detailed Calculation Mechanism
⚡ Phase 1: Candle Polarity
polarity = (close − open) / (high − low)
- +1.0: Complete bullish candle (Bullish Marubozu)
- −1.0: Complete bearish candle (Bearish Marubozu)
- 0.0: Doji (no decision)
- Intermediate values: Represent the ratio of candle body to its range — reducing the effect of long-shadow candles
⚡ Phase 2: Volume Weight
vol_weight = volume / SMA(volume, lookback)
A candle with 150% of average volume = 1.5x stronger charge
⚡ Phase 3: Adaptive Factor
adaptive_factor = ATR(lookback) / SMA(ATR, lookback × 2)
- In volatile markets: Increases sensitivity
- In quiet markets: Reduces noise
- Always recommended to keep it enabled
⚡ Phase 4–6: Charge Accumulation and Normalization
Charges are summed over lookback candles, then ratios are normalized:
norm_positive = positive_charge / total_charge
norm_negative = negative_charge / total_charge
So that: norm_positive + norm_negative = 1 — for easier comparison
⚡ Phase 7: Field Calculations
voltage = norm_positive − norm_negative
field_intensity = 4 × norm_positive × norm_negative × field_sensitivity
capacitance = |voltage| × field_intensity
discharge_prob = min(capacitance / discharge_threshold, 1.0)
█ Settings
⚡ Electromagnetic Model
Lookback Period
- Default: 20
- Range: 5–100
- Recommendations:
- Scalping: 10–15
- Day Trading: 20
- Swing: 30–50
- Investing: 50–100
Discharge Threshold
- Default: 0.7
- Range: 0.3–0.95
- Recommendations:
- Speed + Noise: 0.5–0.6
- Balance: 0.7
- High Accuracy: 0.8–0.95
Field Sensitivity
- Default: 1.0
- Range: 0.5–2.0
- Recommendations:
- Amplify Conflict: 1.2–1.5
- Natural: 1.0
- Calm: 0.5–0.8
Adaptive Mode
- Default: Enabled
- Always keep it enabled
🔬 Dynamic Filters
All enabled filters must pass for discharge signal to appear.
Volume Filter
- Condition: volume > SMA(volume) × vol_multiplier
- Function: Excludes "weak" candles not supported by volume
- Recommendation: Enabled (especially for stocks and forex)
Volatility Filter
- Condition: STDEV > SMA(STDEV) × 0.5
- Function: Ignores sideways stagnation periods
- Recommendation: Always enabled
Trend Filter
- Condition: Voltage alignment with fast/slow EMA
- Function: Reduces counter-trend signals
- Recommendation: Enabled for swing/investing only
Volume Threshold
- Default: 1.2
- Recommendations:
- 1.0–1.2: High sensitivity
- 1.5–2.0: Exclusive to high volume
🎨 Visual Settings
Settings improve visual reading experience — don't affect calculations.
Scale Factor
- Default: 600
- Higher = Larger scene (200–1200)
Horizontal Shift
- Default: 180
- Horizontal shift to the left — to focus on last candle
Pole Size
- Default: 60
- Base sphere size (30–120)
Field Lines
- Default: 8
- Number of field lines (4–16) — 8 is ideal balance
Colors
- Green/Red/Blue/Orange
- Fully customizable
█ Visual Representation: A Visual Language for Diagnosing Price Conditions
✨ Design Philosophy
The representation isn't "decoration", but a complete cognitive model — each element carries information, and element interaction tells a complete story.
The brain perceives changes in size, color, and movement 60,000 times faster than reading numbers — so you can "sense" the change before your eye finishes scanning.
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🟢 Positive Pole (Green Sphere — Left)
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What does it represent?
Active buying pressure accumulation — not just an uptrend, but real demand force supported by volume and volatility.
● Dynamic Size
Size = pole_size × (0.7 + norm_positive × 0.6)
- 70% of base size = No significant charge
- 130% of base size = Complete dominance
- The larger the sphere: Greater buyer dominance, higher probability of bullish continuation
Size Interpretation:
- Large sphere (>55%): Strong buying pressure — Buyers dominate
- Medium sphere (45–55%): Relative balance with buying bias
- Small sphere (<45%): Weak buying pressure — Sellers dominate
● Lighting and Transparency
- 20% transparency (when Bias = +1): Pole currently active — Bullish direction
- 50% transparency (when Bias ≠ +1): Pole inactive — Not the prevailing direction
Lighting = Current activity, while Size = Historical accumulation
● Pulsing Inner Glow
A smaller sphere pulses automatically when Bias = +1:
inner_pulse = 0.4 + 0.1 × sin(anim_time × 3)
Symbolizes continuity of buy order flow — not static dominance.
● Orbital Rings
Two rings rotating at different speeds and directions:
- Inner: 1.3× sphere size — Direct influence range
- Outer: 1.6× sphere size — Extended influence range
Represent "influence zone" of buyers:
- Continuous rotation = Stability and momentum
- Slowdown = Momentum exhaustion
● Percentage
Displayed below sphere: norm_positive × 100
- >55% = Clear dominance
- 45–55% = Balance
- <45% = Weakness
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🔴 Negative Pole (Red Sphere — Right)
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What does it represent?
Active selling pressure accumulation — whether cumulative selling (smart distribution) or panic selling (position liquidation).
● Visual Dynamics
Same size, lighting, and inner glow mechanism — but in red.
Key Difference:
- Rotation is reversed (counter-clockwise)
- Visually distinguishes "buy flow" from "sell flow"
- Allows reading direction at a glance — even for colorblind users
📌 Pole Reading Summary:
🟢 Large + Bright green sphere = Active buying force
🔴 Large + Bright red sphere = Active selling force
🟢🔴 Both large but dim = Energy accumulation (before discharge)
⚪ Both small = Stagnation / Low liquidity
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🔵 Field Lines (Curved Blue Lines)
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What do they represent?
Energy flow paths between poles — the arena where price battle is fought.
● Number of Lines
4–16 lines (Default: 8)
More lines: Greater sense of "interaction density"
● Arc Height
arc_h = (i − half_lines) × 15 × field_intensity × 2
- High field intensity = Highly elevated lines (like waves)
- Low intensity = Nearly straight lines
● Oscillating Transparency
transp = 30 + phase × 40
where phase = sin(anim_time × 2 + i × 0.5) × 0.5 + 0.5
Creates illusion of "flowing current" — not static lines
● Asymmetric Curvature
- Upper lines curve upward
- Lower lines curve downward
- Adds 3D depth and shows "pressure" direction
⚡ Pro Tip:
When you see lines suddenly "contract" (straighten), while both spheres are large — this is an early indicator of impending discharge, because the interaction is losing its flexibility.
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⚪ Moving Particles
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What do they represent?
Real liquidity flow in the market — who's driving price right now.
● Number and Movement
- 6 particles covering most field lines
- Move sinusoidally along the arc:
t = (sin(phase_val) + 1) / 2
- High speed = High trading activity
- Clustering at a pole = That side's control
● Color Gradient
From green (at positive pole) to red (at negative)
Shows "energy transformation":
- Green particle = Pure buying energy
- Orange particle = Conflict zone
- Red particle = Pure selling energy
📌 How to Read Them?
- Moving left to right (🟢 → 🔴): Buy flow → Bullish push
- Moving right to left (🔴 → 🟢): Sell flow → Bearish push
- Clustered in middle: Balanced conflict — Wait for breakout
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🟠 Discharge Zone (Orange Glow — Center)
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What does it represent?
Point of stored energy accumulation not yet discharged — heart of the early warning system.
● Glow Stages
Initial Warning (discharge_prob > 0.3):
- Dim orange circle (70% transparency)
- Meaning: Watch, don't enter yet
High Tension (discharge_prob ≥ 0.7):
- Stronger glow + "⚠️ HIGH TENSION" text
- Meaning: Prepare — Set pending orders
Imminent Discharge (discharge_prob ≥ 0.9):
- Bright glow + "⚡ DISCHARGE IMMINENT" text
- Meaning: Enter with direction (after candle confirmation)
● Layered Glow Effect (Glow Layering)
3 concentric circles with increasing transparency:
- Inner: 20%
- Middle: 35%
- Outer: 50%
Result: Realistic aura resembling actual electrical discharge.
📌 Why in the Center?
Because discharge always starts from the relative balance zone — where opposing pressures meet.
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📊 Voltage Meter (Bottom of Scene)
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What does it represent?
Simplified numeric indicator of voltage difference — for those who prefer numerical reading.
● Components
- Gray bar: Full range (−100% to +100%)
- Green fill: Positive voltage (extends right)
- Red fill: Negative voltage (extends left)
- Lightning symbol (⚡): Above center — reminder it's an "electrical gauge"
- Text value: Like "+23.4%" — in direction color
● Voltage Reading Interpretation
+50% to +100%:
Overwhelming buying dominance — Beware of saturation, may precede correction
+20% to +50%:
Strong buying dominance — Suitable for buying with trend
+5% to +20%:
Slight bullish bias — Wait for additional confirmation
−5% to +5%:
Balance/Neutral — Avoid entry or wait for breakout
−5% to −20%:
Slight bearish bias — Wait for confirmation
−20% to −50%:
Strong selling dominance — Suitable for selling with trend
−50% to −100%:
Overwhelming selling dominance — Beware of saturation, may precede bounce
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📈 Field Strength Indicator (Top of Scene)
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What it displays: "Field: XX.X%"
Meaning: Strength of conflict between buyers and sellers.
● Reading Interpretation
0–5%:
- Appearance: Nearly straight lines, transparent
- Meaning: Complete control by one side
- Strategy: Trend Following
5–15%:
- Appearance: Slight curvature
- Meaning: Clear direction with light resistance
- Strategy: Enter with trend
15–25%:
- Appearance: Medium curvature, clear lines
- Meaning: Balanced conflict
- Strategy: Range trading or waiting
25–35%:
- Appearance: High curvature, clear density
- Meaning: Strong conflict, high uncertainty
- Strategy: Volatility trading or prepare for discharge
35%+:
- Appearance: Very high lines, strong glow
- Meaning: Peak tension
- Strategy: Best discharge opportunities
📌 Golden Relationship:
Highest discharge probability when:
Field Strength (25–35%) + Voltage (±30–50%) + High Volume
← This is the "red zone" to monitor carefully.
█ Comprehensive Visual Reading
To read market condition at a glance, follow this sequence:
Step 1: Which sphere is larger?
- 🟢 Green larger ← Dominant buying pressure
- 🔴 Red larger ← Dominant selling pressure
- Equal ← Balance/Conflict
Step 2: Which sphere is bright?
- 🟢 Green bright ← Current bullish direction
- 🔴 Red bright ← Current bearish direction
- Both dim ← Neutral/No clear direction
Step 3: Is there orange glow?
- None ← Discharge probability <30%
- 🟠 Dim glow ← Discharge probability 30–70%
- 🟠 Strong glow with text ← Discharge probability >70%
Step 4: What's the voltage meter reading?
- Strong positive ← Confirms buying dominance
- Strong negative ← Confirms selling dominance
- Near zero ← No clear direction
█ Practical Visual Reading Examples
Example 1: Ideal Buy Opportunity ⚡🟢
- Green sphere: Large and bright with inner pulse
- Red sphere: Small and dim
- Orange glow: Strong with "DISCHARGE IMMINENT" text
- Voltage meter: +45%
- Field strength: 28%
Interpretation: Strong accumulated buying pressure, bullish explosion imminent
Example 2: Ideal Sell Opportunity ⚡🔴
- Green sphere: Small and dim
- Red sphere: Large and bright with inner pulse
- Orange glow: Strong with "DISCHARGE IMMINENT" text
- Voltage meter: −52%
- Field strength: 31%
Interpretation: Strong accumulated selling pressure, bearish explosion imminent
Example 3: Balance/Wait ⚖️
- Both spheres: Approximately equal in size
- Lighting: Both dim
- Orange glow: Strong
- Voltage meter: +3%
- Field strength: 24%
Interpretation: Strong conflict without clear winner, wait for breakout
Example 4: Clear Uptrend (No Discharge) 📈
- Green sphere: Large and bright
- Red sphere: Very small and dim
- Orange glow: None
- Voltage meter: +68%
- Field strength: 8%
Interpretation: Clear buying control, limited conflict, suitable for following bullish trend
Example 5: Potential Buying Saturation ⚠️
- Green sphere: Very large and bright
- Red sphere: Very small
- Orange glow: Dim
- Voltage meter: +88%
- Field strength: 4%
Interpretation: Absolute buying dominance, may precede bearish correction
█ Trading Signals
⚡ DISCHARGE IMMINENT
Appearance Conditions:
- discharge_prob ≥ 0.9
- All enabled filters passed
- Confirmed (after candle close)
Interpretation:
- Very large energy accumulation
- Pressure reached critical level
- Price explosion expected within 1–3 candles
How to Trade:
1. Determine voltage direction:
• Positive = Expect rise
• Negative = Expect fall
2. Wait for confirmation candle:
• For rise: Bullish candle closing above its open
• For fall: Bearish candle closing below its open
3. Entry: With next candle's open
4. Stop Loss: Behind last local low/high
5. Target: Risk/Reward ratio of at least 1:2
✅ Pro Tips:
- Best results when combined with support/resistance levels
- Avoid entry if voltage is near zero (±5%)
- Increase position size when field strength > 30%
⚠️ HIGH TENSION
Appearance Conditions:
- 0.7 ≤ discharge_prob < 0.9
Interpretation:
- Market in energy accumulation state
- Likely strong move soon, but not immediate
- Accumulation may continue or discharge may occur
How to Benefit:
- Prepare: Set pending orders at potential breakouts
- Monitor: Watch following candles for momentum candle
- Select: Don't enter every signal — choose those aligned with overall trend
█ Trading Strategies
📈 Strategy 1: Discharge Trading (Basic)
Principle: Enter at "DISCHARGE IMMINENT" in voltage direction
Steps:
1. Wait for "⚡ DISCHARGE IMMINENT"
2. Check voltage direction (+/−)
3. Wait for confirmation candle in voltage direction
4. Enter with next candle's open
5. Stop loss behind last low/high
6. Target: 1:2 or 1:3 ratio
Very high success rate when following confirmation conditions.
📈 Strategy 2: Dominance Following
Principle: Trade with dominant pole (largest and brightest sphere)
Steps:
1. Identify dominant pole (largest and brightest)
2. Trade in its direction
3. Beware when sizes converge (conflict)
Suitable for higher timeframes (H1+).
📈 Strategy 3: Reversal Hunting
Principle: Counter-trend entry under certain conditions
Conditions:
- High field strength (>30%)
- Extreme voltage (>±40%)
- Divergence with price (e.g., new price high with declining voltage)
⚠️ High risk — Use small position size.
📈 Strategy 4: Integration with Technical Analysis
Strong Confirmation Examples:
- Resistance breakout + Bullish discharge = Excellent buy signal
- Support break + Bearish discharge = Excellent sell signal
- Head & Shoulders pattern + Increasing negative voltage = Pattern confirmation
- RSI divergence + High field strength = Potential reversal
█ Ready Alerts
Bullish Discharge
- Condition: discharge_prob ≥ 0.9 + Positive voltage + All filters
- Message: "⚡ Bullish discharge"
- Use: High probability buy opportunity
Bearish Discharge
- Condition: discharge_prob ≥ 0.9 + Negative voltage + All filters
- Message: "⚡ Bearish discharge"
- Use: High probability sell opportunity
✅ Tip: Use these alerts with "Once Per Bar" setting to avoid repetition.
█ Data Window Outputs
Bias
- Values: −1 / 0 / +1
- Interpretation: −1 = Bearish, 0 = Neutral, +1 = Bullish
- Use: For integration in automated strategies
Discharge %
- Range: 0–100%
- Interpretation: Discharge probability
- Use: Monitor tension progression (e.g., from 40% to 85% in 5 candles)
Field Strength
- Range: 0–100%
- Interpretation: Conflict intensity
- Use: Identify "opportunity window" (25–35% ideal for discharge)
Voltage
- Range: −100% to +100%
- Interpretation: Balance of power
- Use: Monitor extremes (potential buying/selling saturation)
█ Optimal Settings by Trading Style
Scalping
- Timeframe: 1M–5M
- Lookback: 10–15
- Threshold: 0.5–0.6
- Sensitivity: 1.2–1.5
- Filters: Volume + Volatility
Day Trading
- Timeframe: 15M–1H
- Lookback: 20
- Threshold: 0.7
- Sensitivity: 1.0
- Filters: Volume + Volatility
Swing Trading
- Timeframe: 4H–D1
- Lookback: 30–50
- Threshold: 0.8
- Sensitivity: 0.8
- Filters: Volatility + Trend
Position Trading
- Timeframe: D1–W1
- Lookback: 50–100
- Threshold: 0.85–0.95
- Sensitivity: 0.5–0.8
- Filters: All filters
█ Tips for Optimal Use
1. Start with Default Settings
Try it first as is, then adjust to your style.
2. Watch for Element Alignment
Best signals when:
- Clear voltage (>│20%│)
- Moderate–high field strength (15–35%)
- High discharge probability (>70%)
3. Use Multiple Timeframes
- Higher timeframe: Determine overall trend
- Lower timeframe: Time entry
- Ensure signal alignment between frames
4. Integrate with Other Tools
- Support/Resistance levels
- Trend lines
- Candle patterns
- Volume indicators
5. Respect Risk Management
- Don't risk more than 1–2% of account
- Always use stop loss
- Don't enter every signal — choose the best
█ Important Warnings
⚠️ Not for Standalone Use
The indicator is an analytical support tool — don't use it isolated from technical or fundamental analysis.
⚠️ Doesn't Predict the Future
Calculations are based on historical data — Results are not guaranteed.
⚠️ Markets Differ
You may need to adjust settings for each market:
- Forex: Focus on Volume Filter
- Stocks: Add Trend Filter
- Crypto: Lower Threshold slightly (more volatile)
⚠️ News and Events
The indicator doesn't account for sudden news — Avoid trading before/during major news.
█ Unique Features
✅ First Application of Electromagnetism to Markets
Innovative mathematical model — Not just an ordinary indicator
✅ Predictive Detection of Price Explosions
Alerts before the move happens — Not after
✅ Multi-Layer Filtering
4 smart filters reduce false signals to minimum
✅ Smart Volatility Adaptation
Automatically adjusts sensitivity based on market conditions
✅ Animated 3D Visual Representation
Makes reading instant — Even for beginners
✅ High Flexibility
Works on all assets: Stocks, Forex, Crypto, Commodities
✅ Built-in Ready Alerts
No complex setup needed — Ready for immediate use
█ Conclusion: When Art Meets Science
Market Electromagnetic Field is not just an indicator — but a new analytical philosophy.
It's the bridge between:
- Physics precision in describing dynamic systems
- Market intelligence in generating trading opportunities
- Visual psychology in facilitating instant reading
The result: A tool that isn't read — but watched, felt, and sensed.
When you see the green sphere expanding, the glow intensifying, and particles rushing rightward — you're not seeing numbers, you're seeing market energy breathing.
⚠️ Disclaimer:
This indicator is for educational and analytical purposes only. It does not constitute financial, investment, or trading advice. Use it in conjunction with your own strategy and risk management. Neither TradingView nor the developer is liable for any financial decisions or losses.
المجال الكهرومغناطيسي للسوق - Market Electromagnetic Field
مؤشر تحليلي مبتكر يقدّم نموذجًا جديدًا كليًّا لفهم ديناميكيات السوق، مستوحى من قوانين الفيزياء الكهرومغناطيسية — لكنه ليس استعارة بلاغية، بل نظام رياضي متكامل.
على عكس المؤشرات التقليدية التي تُركّز على السعر أو الزخم، يُصوّر هذا المؤشر السوق كـنظام فيزيائي مغلق، حيث:
⚡ الشموع = شحنات كهربائية (موجبة عند الإغلاق الصاعد، سالبة عند الهابط)
⚡ المشتريون والبائعون = قطبان متعاكسان يتراكم فيهما الضغط
⚡ التوتر السوقي = فرق جهد بين القطبين
⚡ الاختراق السعري = تفريغ كهربائي بعد تراكم طاقة كافية
█ الفكرة الجوهرية
الأسواق لا تتحرك عشوائيًّا، بل تخضع لدورة فيزيائية واضحة:
تراكم → توتر → تفريغ → استقرار → تراكم جديد
عندما تتراكم الشحنات (من خلال شموع قوية بحجم مرتفع) وتتجاوز "السعة الكهربائية" عتبة معيّنة، يُصدر المؤشر تنبيه "⚡ DISCHARGE IMMINENT" — أي أن انفجارًا سعريًّا وشيكًا، مما يمنح المتداول فرصة الدخول قبل بدء الحركة.
█ الميزة التنافسية
- تنبؤ استباقي (ليس تأكيديًّا بعد الحدث)
- فلترة ذكية متعددة الطبقات تقلل الإشارات الكاذبة
- تمثيل بصري ثلاثي الأبعاد متحرك يجعل قراءة الحالة السعرية فورية وبديهية — دون حاجة لتحليل أرقام
█ الأساس النظري الفيزيائي
المؤشر لا يستخدم مصطلحات فيزيائية للزينة، بل يُطبّق القوانين الرياضية مع تعديلات سوقيّة دقيقة:
⚡ قانون كولوم (Coulomb's Law)
الفيزياء: F = k × (q₁ × q₂) / r²
السوق: شدة الحقل = 4 × norm_positive × norm_negative
تصل لذروتها عند التوازن (0.5 × 0.5 × 4 = 1.0)، وتنخفض عند الهيمنة — لأن الصراع يزداد عند التكافؤ.
⚡ قانون أوم (Ohm's Law)
الفيزياء: V = I × R
السوق: الجهد = norm_positive − norm_negative
يقيس ميزان القوى:
- +1 = هيمنة شرائية مطلقة
- −1 = هيمنة بيعية مطلقة
- 0 = توازن
⚡ السعة الكهربائية (Capacitance)
الفيزياء: C = Q / V
السوق: السعة = |الجهد| × شدة الحقل
تمثّل الطاقة المخزّنة القابلة للتفريغ — تزداد عند وجود تحيّز مع تفاعل عالي.
⚡ التفريغ الكهربائي (Discharge)
الفيزياء: يحدث عند تجاوز عتبة العزل
السوق: احتمال التفريغ = min(السعة / عتبة التفريغ, 1.0)
عندما ≥ 0.9: "⚡ DISCHARGE IMMINENT"
📌 ملاحظة جوهرية:
أقصى سعة لا تحدث عند الهيمنة المطلقة (حيث شدة الحقل = 0)، ولا عند التوازن التام (حيث الجهد = 0)، بل عند انحياز متوسط (±30–50%) مع تفاعل عالي (شدة حقل > 25%) — أي في لحظات "الضغط قبل الاختراق".
█ آلية الحساب التفصيلية
⚡ المرحلة 1: قطبية الشمعة
polarity = (close − open) / (high − low)
- +1.0: شمعة صاعدة كاملة (ماروبوزو صاعد)
- −1.0: شمعة هابطة كاملة (ماروبوزو هابط)
- 0.0: دوجي (لا قرار)
- القيم الوسيطة: تمثّل نسبة جسم الشمعة إلى مداها — مما يقلّل تأثير الشموع ذات الظلال الطويلة
⚡ المرحلة 2: وزن الحجم
vol_weight = volume / SMA(volume, lookback)
شمعة بحجم 150% من المتوسط = شحنة أقوى بـ 1.5 مرة
⚡ المرحلة 3: معامل التكيف (Adaptive Factor)
adaptive_factor = ATR(lookback) / SMA(ATR, lookback × 2)
- في الأسواق المتقلبة: يزيد الحساسية
- في الأسواق الهادئة: يقلل الضوضاء
- يوصى دائمًا بتركه مفعّلًا
⚡ المرحلة 4–6: تراكم وتوحيد الشحنات
تُجمّع الشحنات على lookback شمعة، ثم تُوحّد النسب:
norm_positive = positive_charge / total_charge
norm_negative = negative_charge / total_charge
بحيث: norm_positive + norm_negative = 1 — لتسهيل المقارنة
⚡ المرحلة 7: حسابات الحقل
voltage = norm_positive − norm_negative
field_intensity = 4 × norm_positive × norm_negative × field_sensitivity
capacitance = |voltage| × field_intensity
discharge_prob = min(capacitance / discharge_threshold, 1.0)
█ الإعدادات
⚡ Electromagnetic Model
Lookback Period
- الافتراضي: 20
- النطاق: 5–100
- التوصيات:
- المضاربة: 10–15
- اليومي: 20
- السوينغ: 30–50
- الاستثمار: 50–100
Discharge Threshold
- الافتراضي: 0.7
- النطاق: 0.3–0.95
- التوصيات:
- سرعة + ضوضاء: 0.5–0.6
- توازن: 0.7
- دقة عالية: 0.8–0.95
Field Sensitivity
- الافتراضي: 1.0
- النطاق: 0.5–2.0
- التوصيات:
- تضخيم الصراع: 1.2–1.5
- طبيعي: 1.0
- تهدئة: 0.5–0.8
Adaptive Mode
- الافتراضي: مفعّل
- أبقِه دائمًا مفعّلًا
🔬 Dynamic Filters
يجب اجتياز جميع الفلاتر المفعّلة لظهور إشارة التفريغ.
Volume Filter
- الشرط: volume > SMA(volume) × vol_multiplier
- الوظيفة: يستبعد الشموع "الضعيفة" غير المدعومة بحجم
- التوصية: مفعّل (خاصة للأسهم والعملات)
Volatility Filter
- الشرط: STDEV > SMA(STDEV) × 0.5
- الوظيفة: يتجاهل فترات الركود الجانبي
- التوصية: مفعّل دائمًا
Trend Filter
- الشرط: توافق الجهد مع EMA سريع/بطيء
- الوظيفة: يقلل الإشارات المعاكسة للاتجاه العام
- التوصية: مفعّل للسوينغ/الاستثمار فقط
Volume Threshold
- الافتراضي: 1.2
- التوصيات:
- 1.0–1.2: حساسية عالية
- 1.5–2.0: حصرية للحجم العالي
🎨 Visual Settings
الإعدادات تُحسّن تجربة القراءة البصرية — لا تؤثر على الحسابات.
Scale Factor
- الافتراضي: 600
- كلما زاد: المشهد أكبر (200–1200)
Horizontal Shift
- الافتراضي: 180
- إزاحة أفقيّة لليسار — ليركّز على آخر شمعة
Pole Size
- الافتراضي: 60
- حجم الكرات الأساسية (30–120)
Field Lines
- الافتراضي: 8
- عدد خطوط الحقل (4–16) — 8 توازن مثالي
الألوان
- أخضر/أحمر/أزرق/برتقالي
- قابلة للتخصيص بالكامل
█ التمثيل البصري: لغة بصرية لتشخيص الحالة السعرية
✨ الفلسفة التصميمية
التمثيل ليس "زينة"، بل نموذج معرفي متكامل — كل عنصر يحمل معلومة، وتفاعل العناصر يروي قصة كاملة.
العقل يدرك التغيير في الحجم، اللون، والحركة أسرع بـ 60,000 مرة من قراءة الأرقام — لذا يمكنك "الإحساس" بالتغير قبل أن تُنهي العين المسح.
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🟢 القطب الموجب (الكرة الخضراء — يسار)
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ماذا يمثّل؟
تراكم ضغط الشراء النشط — ليس مجرد اتجاه صاعد، بل قوة طلب حقيقية مدعومة بحجم وتقلّب.
● الحجم المتغير
حجم = pole_size × (0.7 + norm_positive × 0.6)
- 70% من الحجم الأساسي = لا شحنة تُذكر
- 130% من الحجم الأساسي = هيمنة تامة
- كلما كبرت الكرة: زاد تفوّق المشترين، وارتفع احتمال الاستمرار الصعودي
تفسير الحجم:
- كرة كبيرة (>55%): ضغط شراء قوي — المشترون يسيطرون
- كرة متوسطة (45–55%): توازن نسبي مع ميل للشراء
- كرة صغيرة (<45%): ضعف ضغط الشراء — البائعون يسيطرون
● الإضاءة والشفافية
- شفافية 20% (عند Bias = +1): القطب نشط حالياً — الاتجاه صعودي
- شفافية 50% (عند Bias ≠ +1): القطب غير نشط — ليس الاتجاه السائد
الإضاءة = النشاط الحالي، بينما الحجم = التراكم التاريخي
● التوهج الداخلي النابض
كرة أصغر تنبض تلقائيًّا عند Bias = +1:
inner_pulse = 0.4 + 0.1 × sin(anim_time × 3)
يرمز إلى استمرارية تدفق أوامر الشراء — وليس هيمنة جامدة.
● الحلقات المدارية
حلقتان تدوران بسرعات واتجاهات مختلفة:
- الداخلية: 1.3× حجم الكرة — نطاق التأثير المباشر
- الخارجية: 1.6× حجم الكرة — نطاق التأثير الممتد
تمثّل "نطاق تأثير" المشترين:
- الدوران المستمر = استقرار وزخم
- التباطؤ = نفاد الزخم
● النسبة المئوية
تظهر تحت الكرة: norm_positive × 100
- >55% = هيمنة واضحة
- 45–55% = توازن
- <45% = ضعف
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🔴 القطب السالب (الكرة الحمراء — يمين)
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ماذا يمثّل؟
تراكم ضغط البيع النشط — سواء كان بيعًا تراكميًّا (التوزيع الذكي) أو بيعًا هستيريًّا (تصفية مراكز).
● الديناميكيات البصرية
نفس آلية الحجم والإضاءة والتوهج الداخلي — لكن باللون الأحمر.
الفرق الجوهري:
- الدوران معكوس (عكس اتجاه عقارب الساعة)
- يُميّز بصريًّا بين "تدفق الشراء" و"تدفق البيع"
- يسمح بقراءة الاتجاه بنظرة واحدة — حتى للمصابين بعَمَى الألوان
📌 ملخص قراءة القطبين:
🟢 كرة خضراء كبيرة + مضيئة = قوة شرائية نشطة
🔴 كرة حمراء كبيرة + مضيئة = قوة بيعية نشطة
🟢🔴 كرتان كبيرتان لكن خافتتان = تراكم طاقة (قبل التفريغ)
⚪ كرتان صغيرتان = ركود / سيولة منخفضة
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🔵 خطوط الحقل (الخطوط الزرقاء المنحنية)
═════════════════════════════════════════════════════════════
ماذا تمثّل؟
مسارات تدفق الطاقة بين القطبين — أي الساحة التي تُدار فيها المعركة السعرية.
● عدد الخطوط
4–16 خط (الافتراضي: 8)
كلما زاد العدد: زاد إحساس "كثافة التفاعل"
● ارتفاع القوس
arc_h = (i − half_lines) × 15 × field_intensity × 2
- شدة حقل عالية = خطوط شديدة الارتفاع (مثل موجة)
- شدة منخفضة = خطوط شبه مستقيمة
● الشفافية المتذبذبة
transp = 30 + phase × 40
حيث phase = sin(anim_time × 2 + i × 0.5) × 0.5 + 0.5
تخلق وهم "تيّار متدفّق" — وليس خطوطًا ثابتة
● الانحناء غير المتناظر
- الخطوط العلوية تنحني لأعلى
- الخطوط السفلية تنحني لأسفل
- يُضفي عمقًا ثلاثي الأبعاد ويُظهر اتجاه "الضغط"
⚡ تلميح احترافي:
عندما ترى الخطوط "تتقلّص" فجأة (تستقيم)، بينما الكرتان كبيرتان — فهذا مؤشر مبكر على قرب التفريغ، لأن التفاعل بدأ يفقد مرونته.
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⚪ الجزيئات المتحركة
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ماذا تمثّل؟
تدفق السيولة الحقيقية في السوق — أي من يدفع السعر الآن.
● العدد والحركة
- 6 جزيئات تغطي معظم خطوط الحقل
- تتحرك جيبيًّا على طول القوس:
t = (sin(phase_val) + 1) / 2
- سرعة عالية = نشاط تداول عالي
- تجمّع عند قطب = سيطرة هذا الطرف
● تدرج اللون
من أخضر (عند القطب الموجب) إلى أحمر (عند السالب)
يُظهر "تحوّل الطاقة":
- جزيء أخضر = طاقة شرائية نقية
- جزيء برتقالي = منطقة صراع
- جزيء أحمر = طاقة بيعية نقية
📌 كيف تقرأها؟
- تحركت من اليسار لليمين (🟢 → 🔴): تدفق شرائي → دفع صعودي
- تحركت من اليمين لليسار (🔴 → 🟢): تدفق بيعي → دفع هبوطي
- تجمّعت في المنتصف: صراع متكافئ — انتظر اختراقًا
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🟠 منطقة التفريغ (التوهج البرتقالي — المركز)
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ماذا تمثّل؟
نقطة تراكم الطاقة المخزّنة التي لم تُفرّغ بعد — قلب نظام الإنذار المبكر.
● مراحل التوهج
إنذار أولي (discharge_prob > 0.3):
- دائرة برتقالية خافتة (شفافية 70%)
- المعنى: راقب، لا تدخل بعد
توتر عالي (discharge_prob ≥ 0.7):
- توهج أقوى + نص "⚠️ HIGH TENSION"
- المعنى: استعد — ضع أوامر معلقة
تفريغ وشيك (discharge_prob ≥ 0.9):
- توهج ساطع + نص "⚡ DISCHARGE IMMINENT"
- المعنى: ادخل مع الاتجاه (بعد تأكيد شمعة)
● تأثير التوهج الطبقي (Glow Layering)
3 دوائر متحدة المركز بشفافية متزايدة:
- داخلي: 20%
- وسط: 35%
- خارجي: 50%
النتيجة: هالة (Aura) واقعية تشبه التفريغ الكهربائي الحقيقي.
📌 لماذا في المركز؟
لأن التفريغ يبدأ دائمًا من منطقة التوازن النسبي — حيث يلتقي الضغطان المتعاكسان.
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📊 مقياس الجهد (أسفل المشهد)
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ماذا يمثّل؟
مؤشر رقمي مبسّط لفرق الجهد — لمن يفضّل القراءة العددية.
● المكونات
- الشريط الرمادي: النطاق الكامل (−100% إلى +100%)
- التعبئة الخضراء: جهد موجب (تمتد لليمين)
- التعبئة الحمراء: جهد سالب (تمتد لليسار)
- رمز البرق (⚡): فوق المركز — تذكير بأنه "مقياس كهربائي"
- القيمة النصية: مثل "+23.4%" — بلون الاتجاه
● تفسير قراءات الجهد
+50% إلى +100%:
هيمنة شرائية ساحقة — احذر التشبع، قد يسبق تصحيح
+20% إلى +50%:
هيمنة شرائية قوية — مناسب للشراء مع الاتجاه
+5% إلى +20%:
ميل صعودي خفيف — انتظر تأكيدًا إضافيًّا
−5% إلى +5%:
توازن/حياد — تجنّب الدخول أو انتظر اختراقًا
−5% إلى −20%:
ميل هبوطي خفيف — انتظر تأكيدًا
−20% إلى −50%:
هيمنة بيعية قوية — مناسب للبيع مع الاتجاه
−50% إلى −100%:
هيمنة بيعية ساحقة — احذر التشبع، قد يسبق ارتداد
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📈 مؤشر شدة الحقل (أعلى المشهد)
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ما يعرضه: "Field: XX.X%"
الدلالة: قوة الصراع بين المشترين والبائعين.
● تفسير القراءات
0–5%:
- المظهر: خطوط مستقيمة تقريبًا، شفافة
- المعنى: سيطرة تامة لأحد الطرفين
- الاستراتيجية: تتبع الترند (Trend Following)
5–15%:
- المظهر: انحناء خفيف
- المعنى: اتجاه واضح مع مقاومة خفيفة
- الاستراتيجية: الدخول مع الاتجاه
15–25%:
- المظهر: انحناء متوسط، خطوط واضحة
- المعنى: صراع متوازن
- الاستراتيجية: تداول النطاق أو الانتظار
25–35%:
- المظهر: انحناء عالي، كثافة واضحة
- المعنى: صراع قوي، عدم يقين عالي
- الاستراتيجية: تداول التقلّب أو الاستعداد للتفريغ
35%+:
- المظهر: خطوط عالية جدًّا، توهج قوي
- المعنى: ذروة التوتر
- الاستراتيجية: أفضل فرص التفريغ
📌 العلاقة الذهبية:
أعلى احتمال تفريغ عندما:
شدة الحقل (25–35%) + جهد (±30–50%) + حجم مرتفع
← هذه هي "المنطقة الحمراء" التي يجب مراقبتها بدقة.
█ قراءة التمثيل البصري الشاملة
لقراءة حالة السوق بنظرة واحدة، اتبع هذا التسلسل:
الخطوة 1: أي كرة أكبر؟
- 🟢 الخضراء أكبر ← ضغط شراء مهيمن
- 🔴 الحمراء أكبر ← ضغط بيع مهيمن
- متساويتان ← توازن/صراع
الخطوة 2: أي كرة مضيئة؟
- 🟢 الخضراء مضيئة ← اتجاه صعودي حالي
- 🔴 الحمراء مضيئة ← اتجاه هبوطي حالي
- كلاهما خافت ← حياد/لا اتجاه واضح
الخطوة 3: هل يوجد توهج برتقالي؟
- لا يوجد ← احتمال تفريغ <30%
- 🟠 توهج خافت ← احتمال تفريغ 30–70%
- 🟠 توهج قوي مع نص ← احتمال تفريغ >70%
الخطوة 4: ما قراءة مقياس الجهد؟
- موجب قوي ← تأكيد الهيمنة الشرائية
- سالب قوي ← تأكيد الهيمنة البيعية
- قريب من الصفر ← لا اتجاه واضح
█ أمثلة عملية للقراءة البصرية
المثال 1: فرصة شراء مثالية ⚡🟢
- الكرة الخضراء: كبيرة ومضيئة مع نبض داخلي
- الكرة الحمراء: صغيرة وخافتة
- التوهج البرتقالي: قوي مع نص "DISCHARGE IMMINENT"
- مقياس الجهد: +45%
- شدة الحقل: 28%
التفسير: ضغط شراء قوي متراكم، انفجار صعودي وشيك
المثال 2: فرصة بيع مثالية ⚡🔴
- الكرة الخضراء: صغيرة وخافتة
- الكرة الحمراء: كبيرة ومضيئة مع نبض داخلي
- التوهج البرتقالي: قوي مع نص "DISCHARGE IMMINENT"
- مقياس الجهد: −52%
- شدة الحقل: 31%
التفسير: ضغط بيع قوي متراكم، انفجار هبوطي وشيك
المثال 3: توازن/انتظار ⚖️
- الكرتان: متساويتان تقريباً في الحجم
- الإضاءة: كلاهما خافت
- التوهج البرتقالي: قوي
- مقياس الجهد: +3%
- شدة الحقل: 24%
التفسير: صراع قوي بدون فائز واضح، انتظر اختراقًا
المثال 4: اتجاه صعودي واضح (لا تفريغ) 📈
- الكرة الخضراء: كبيرة ومضيئة
- الكرة الحمراء: صغيرة جداً وخافتة
- التوهج البرتقالي: لا يوجد
- مقياس الجهد: +68%
- شدة الحقل: 8%
التفسير: سيطرة شرائية واضحة، صراع محدود، مناسب لتتبع الترند الصعودي
المثال 5: تشبع شرائي محتمل ⚠️
- الكرة الخضراء: كبيرة جداً ومضيئة
- الكرة الحمراء: صغيرة جداً
- التوهج البرتقالي: خافت
- مقياس الجهد: +88%
- شدة الحقل: 4%
التفسير: هيمنة شرائية مطلقة، قد يسبق تصحيحاً هبوطياً
█ إشارات التداول
⚡ DISCHARGE IMMINENT (التفريغ الوشيك)
شروط الظهور:
- discharge_prob ≥ 0.9
- اجتياز جميع الفلاتر المفعّلة
- Confirmed (بعد إغلاق الشمعة)
التفسير:
- تراكم طاقة كبير جدًّا
- الضغط وصل لمستوى حرج
- انفجار سعري متوقع خلال 1–3 شموع
كيفية التداول:
1. حدد اتجاه الجهد:
• موجب = توقع صعود
• سالب = توقع هبوط
2. انتظر شمعة تأكيدية:
• للصعود: شمعة صاعدة تغلق فوق افتتاحها
• للهبوط: شمعة هابطة تغلق تحت افتتاحها
3. الدخول: مع افتتاح الشمعة التالية
4. وقف الخسارة: وراء آخر قاع/قمة محلية
5. الهدف: نسبة مخاطرة/عائد 1:2 على الأقل
✅ نصائح احترافية:
- أفضل النتائج عند دمجها مع مستويات الدعم/المقاومة
- تجنّب الدخول إذا كان الجهد قريبًا من الصفر (±5%)
- زِد حجم المركز عند شدة حقل > 30%
⚠️ HIGH TENSION (التوتر العالي)
شروط الظهور:
- 0.7 ≤ discharge_prob < 0.9
التفسير:
- السوق في حالة تراكم طاقة
- احتمال حركة قوية قريبة، لكن ليست فورية
- قد يستمر التراكم أو يحدث تفريغ
كيفية الاستفادة:
- الاستعداد: حضّر أوامر معلقة عند الاختراقات المحتملة
- المراقبة: راقب الشموع التالية بحثًا عن شمعة دافعة
- الانتقاء: لا تدخل كل إشارة — اختر تلك التي تتوافق مع الاتجاه العام
█ استراتيجيات التداول
📈 استراتيجية 1: تداول التفريغ (الأساسية)
المبدأ: الدخول عند "DISCHARGE IMMINENT" في اتجاه الجهد
الخطوات:
1. انتظر ظهور "⚡ DISCHARGE IMMINENT"
2. تحقق من اتجاه الجهد (+/−)
3. انتظر شمعة تأكيدية في اتجاه الجهد
4. ادخل مع افتتاح الشمعة التالية
5. وقف الخسارة وراء آخر قاع/قمة
6. الهدف: نسبة 1:2 أو 1:3
نسبة نجاح عالية جدًّا عند الالتزام بشروط التأكيد.
📈 استراتيجية 2: تتبع الهيمنة
المبدأ: التداول مع القطب المهيمن (الكرة الأكبر والأكثر إضاءة)
الخطوات:
1. حدد القطب المهيمن (الأكبر حجماً والأكثر إضاءة)
2. تداول في اتجاهه
3. احذر عند تقارب الأحجام (صراع)
مناسبة للإطارات الزمنية الأعلى (H1+).
📈 استراتيجية 3: صيد الانعكاس
المبدأ: الدخول عكس الاتجاه عند ظروف معينة
الشروط:
- شدة حقل عالية (>30%)
- جهد متطرف (>±40%)
- تباعد مع السعر (مثل: قمة سعرية جديدة مع تراجع الجهد)
⚠️ عالية المخاطرة — استخدم حجم مركز صغير.
📈 استراتيجية 4: الدمج مع التحليل الفني
أمثلة تأكيد قوي:
- اختراق مقاومة + تفريغ صعودي = إشارة شراء ممتازة
- كسر دعم + تفريغ هبوطي = إشارة بيع ممتازة
- نموذج Head & Shoulders + جهد سالب متزايد = تأكيد النموذج
- تباعد RSI + شدة حقل عالية = انعكاس محتمل
█ التنبيهات الجاهزة
Bullish Discharge
- الشرط: discharge_prob ≥ 0.9 + جهد موجب + جميع الفلاتر
- الرسالة: "⚡ Bullish discharge"
- الاستخدام: فرصة شراء عالية الاحتمالية
Bearish Discharge
- الشرط: discharge_prob ≥ 0.9 + جهد سالب + جميع الفلاتر
- الرسالة: "⚡ Bearish discharge"
- الاستخدام: فرصة بيع عالية الاحتمالية
✅ نصيحة: استخدم هذه التنبيهات مع إعداد "Once Per Bar" لتجنب التكرار.
█ المخرجات في نافذة البيانات
Bias
- القيم: −1 / 0 / +1
- التفسير: −1 = هبوطي، 0 = حياد، +1 = صعودي
- الاستخدام: لدمجها في استراتيجيات آلية
Discharge %
- النطاق: 0–100%
- التفسير: احتمال التفريغ
- الاستخدام: مراقبة تدرّج التوتر (مثال: من 40% إلى 85% في 5 شموع)
Field Strength
- النطاق: 0–100%
- التفسير: شدة الصراع
- الاستخدام: تحديد "نافذة الفرص" (25–35% مثالية للتفريغ)
Voltage
- النطاق: −100% إلى +100%
- التفسير: ميزان القوى
- الاستخدام: مراقبة التطرف (تشبع شرائي/بيعي محتمل)
█ الإعدادات المثلى حسب أسلوب التداول
المضاربة (Scalping)
- الإطار: 1M–5M
- Lookback: 10–15
- Threshold: 0.5–0.6
- Sensitivity: 1.2–1.5
- الفلاتر: Volume + Volatility
التداول اليومي (Day Trading)
- الإطار: 15M–1H
- Lookback: 20
- Threshold: 0.7
- Sensitivity: 1.0
- الفلاتر: Volume + Volatility
السوينغ (Swing Trading)
- الإطار: 4H–D1
- Lookback: 30–50
- Threshold: 0.8
- Sensitivity: 0.8
- الفلاتر: Volatility + Trend
الاستثمار (Position Trading)
- الإطار: D1–W1
- Lookback: 50–100
- Threshold: 0.85–0.95
- Sensitivity: 0.5–0.8
- الفلاتر: جميع الفلاتر
█ نصائح للاستخدام الأمثل
1. ابدأ بالإعدادات الافتراضية
جرّبه أولًا كما هو، ثم عدّل حسب أسلوبك.
2. راقب التوافق بين العناصر
أفضل الإشارات عندما:
- الجهد واضح (>│20%│)
- شدة الحقل معتدلة–عالية (15–35%)
- احتمال التفريغ مرتفع (>70%)
3. استخدم أطر زمنية متعددة
- الإطار الأعلى: تحديد الاتجاه العام
- الإطار الأدنى: توقيت الدخول
- تأكد من توافق الإشارات بين الأطر
4. دمج مع أدوات أخرى
- مستويات الدعم/المقاومة
- خطوط الاتجاه
- أنماط الشموع
- مؤشرات الحجم
5. احترم إدارة المخاطرة
- لا تخاطر بأكثر من 1–2% من الحساب
- استخدم دائمًا وقف الخسارة
- لا تدخل كل الإشارات — اختر الأفضل
█ تحذيرات مهمة
⚠️ ليس للاستخدام المنفرد
المؤشر أداة تحليل مساعِدة — لا تستخدمه بمعزل عن التحليل الفني أو الأساسي.
⚠️ لا يتنبأ بالمستقبل
الحسابات مبنية على البيانات التاريخية — النتائج ليست مضمونة.
⚠️ الأسواق تختلف
قد تحتاج لضبط الإعدادات لكل سوق:
- العملات: تركّز على Volume Filter
- الأسهم: أضف Trend Filter
- الكريبتو: خفّض Threshold قليلًا (أكثر تقلّبًا)
⚠️ الأخبار والأحداث
المؤشر لا يأخذ في الاعتبار الأخبار المفاجئة — تجنّب التداول قبل/أثناء الأخبار الرئيسية.
█ الميزات الفريدة
✅ أول تطبيق للكهرومغناطيسية على الأسواق
نموذج رياضي مبتكر — ليس مجرد مؤشر عادي
✅ كشف استباقي للانفجارات السعرية
يُنبّه قبل حدوث الحركة — وليس بعدها
✅ تصفية متعددة الطبقات
4 فلاتر ذكية تقلل الإشارات الكاذبة إلى الحد الأدنى
✅ تكيف ذكي مع التقلب
يضبط حساسيته تلقائيًّا حسب ظروف السوق
✅ تمثيل بصري ثلاثي الأبعاد متحرك
يجعل القراءة فورية — حتى للمبتدئين
✅ مرونة عالية
يعمل على جميع الأصول: أسهم، عملات، كريبتو، سلع
✅ تنبيهات مدمجة جاهزة
لا حاجة لإعدادات معقدة — جاهز للاستخدام الفوري
█ خاتمة: عندما يلتقي الفن بالعلم
Market Electromagnetic Field ليس مجرد مؤشر — بل فلسفة تحليلية جديدة.
هو الجسر بين:
- دقة الفيزياء في وصف الأنظمة الديناميكية
- ذكاء السوق في توليد فرص التداول
- علم النفس البصري في تسهيل القراءة الفورية
النتيجة: أداة لا تُقرأ — بل تُشاهد، تُشعر، وتُستشعر.
عندما ترى الكرة الخضراء تتوسع، والتوهج يصفرّ، والجزيئات تندفع لليمين — فأنت لا ترى أرقامًا، بل ترى طاقة السوق تتنفّس.
⚠️ إخلاء مسؤولية:
هذا المؤشر لأغراض تعليمية وتحليلية فقط. لا يُمثل نصيحة مالية أو استثمارية أو تداولية. استخدمه بالتزامن مع استراتيجيتك الخاصة وإدارة المخاطر. لا يتحمل TradingView ولا المطور مسؤولية أي قرارات مالية أو خسائر.
在腳本中搜尋"马斯克+100万"
RSI Overbought/Oversold + Divergence Indicator (new)//@version=5
indicator('CryptoSignalScanner - RSI Overbought/Oversold + Divergence Indicator (new)',
//---------------------------------------------------------------------------------------------------------------------------------
//--- Define Colors ---------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------
vWhite = #FFFFFF
vViolet = #C77DF3
vIndigo = #8A2BE2
vBlue = #009CDF
vGreen = #5EBD3E
vYellow = #FFB900
vRed = #E23838
longColor = color.green
shortColor = color.red
textColor = color.white
bullishColor = color.rgb(38,166,154,0) //Used in the display table
bearishColor = color.rgb(239,83,79,0) //Used in the display table
nomatchColor = color.silver //Used in the display table
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- Functions--------------------------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
TF2txt(TF) =>
switch TF
"S" => "RSI 1s:"
"5S" => "RSI 5s:"
"10S" => "RSI 10s:"
"15S" => "RSI 15s:"
"30S" => "RSI 30s"
"1" => "RSI 1m:"
"3" => "RSI 3m:"
"5" => "RSI 5m:"
"15" => "RSI 15m:"
"30" => "RSI 30m"
"45" => "RSI 45m"
"60" => "RSI 1h:"
"120" => "RSI 2h:"
"180" => "RSI 3h:"
"240" => "RSI 4h:"
"480" => "RSI 8h:"
"D" => "RSI 1D:"
"1D" => "RSI 1D:"
"2D" => "RSI 2D:"
"3D" => "RSI 2D:"
"3D" => "RSI 3W:"
"W" => "RSI 1W:"
"1W" => "RSI 1W:"
"M" => "RSI 1M:"
"1M" => "RSI 1M:"
"3M" => "RSI 3M:"
"6M" => "RSI 6M:"
"12M" => "RSI 12M:"
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- Show/Hide Settings ----------------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
rsiShowInput = input(true, title='Show RSI', group='Show/Hide Settings')
maShowInput = input(false, title='Show MA', group='Show/Hide Settings')
showRSIMAInput = input(true, title='Show RSIMA Cloud', group='Show/Hide Settings')
rsiBandShowInput = input(true, title='Show Oversold/Overbought Lines', group='Show/Hide Settings')
rsiBandExtShowInput = input(true, title='Show Oversold/Overbought Extended Lines', group='Show/Hide Settings')
rsiHighlightShowInput = input(true, title='Show Oversold/Overbought Highlight Lines', group='Show/Hide Settings')
DivergenceShowInput = input(true, title='Show RSI Divergence Labels', group='Show/Hide Settings')
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- Table Settings --------------------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
rsiShowTable = input(true, title='Show RSI Table Information box', group="RSI Table Settings")
rsiTablePosition = input.string(title='Location', defval='middle_right', options= , group="RSI Table Settings", inline='1')
rsiTextSize = input.string(title=' Size', defval='small', options= , group="RSI Table Settings", inline='1')
rsiShowTF1 = input(true, title='Show TimeFrame1', group="RSI Table Settings", inline='tf1')
rsiTF1 = input.timeframe("15", title=" Time", group="RSI Table Settings", inline='tf1')
rsiShowTF2 = input(true, title='Show TimeFrame2', group="RSI Table Settings", inline='tf2')
rsiTF2 = input.timeframe("60", title=" Time", group="RSI Table Settings", inline='tf2')
rsiShowTF3 = input(true, title='Show TimeFrame3', group="RSI Table Settings", inline='tf3')
rsiTF3 = input.timeframe("240", title=" Time", group="RSI Table Settings", inline='tf3')
rsiShowTF4 = input(true, title='Show TimeFrame4', group="RSI Table Settings", inline='tf4')
rsiTF4 = input.timeframe("D", title=" Time", group="RSI Table Settings", inline='tf4')
rsiShowHist = input(true, title='Show RSI Historical Columns', group="RSI Table Settings", tooltip='Show the information of the 2 previous closed candles')
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- RSI Input Settings ----------------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
rsiSourceInput = input.source(close, 'Source', group='RSI Settings')
rsiLengthInput = input.int(14, minval=1, title='RSI Length', group='RSI Settings', tooltip='Here we set the RSI lenght')
rsiColorInput = input.color(#26a69a, title="RSI Color", group='RSI Settings')
rsimaColorInput = input.color(#ef534f, title="RSIMA Color", group='RSI Settings')
rsiBandColorInput = input.color(#787B86, title="RSI Band Color", group='RSI Settings')
rsiUpperBandExtInput = input.int(title='RSI Overbought Extended Line', defval=80, minval=50, maxval=100, group='RSI Settings')
rsiUpperBandInput = input.int(title='RSI Overbought Line', defval=70, minval=50, maxval=100, group='RSI Settings')
rsiLowerBandInput = input.int(title='RSI Oversold Line', defval=30, minval=0, maxval=50, group='RSI Settings')
rsiLowerBandExtInput = input.int(title='RSI Oversold Extended Line', defval=20, minval=0, maxval=50, group='RSI Settings')
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- MA Input Settings -----------------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
maTypeInput = input.string("EMA", title="MA Type", options= , group="MA Settings")
maLengthInput = input.int(14, title="MA Length", group="MA Settings")
maColorInput = input.color(color.yellow, title="MA Color", group='MA Settings') //#7E57C2
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- Divergence Input Settings ---------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
lbrInput = input(title="Pivot Lookback Right", defval=2, group='RSI Divergence Settings')
lblInput = input(title="Pivot Lookback Left", defval=2, group='RSI Divergence Settings')
lbRangeMaxInput = input(title="Max of Lookback Range", defval=10, group='RSI Divergence Settings')
lbRangeMinInput = input(title="Min of Lookback Range", defval=2, group='RSI Divergence Settings')
plotBullInput = input(title="Plot Bullish", defval=true, group='RSI Divergence Settings')
plotHiddenBullInput = input(title="Plot Hidden Bullish", defval=true, group='RSI Divergence Settings')
plotBearInput = input(title="Plot Bearish", defval=true, group='RSI Divergence Settings')
plotHiddenBearInput = input(title="Plot Hidden Bearish", defval=true, group='RSI Divergence Settings')
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- RSI Calculation -------------------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
rsi = ta.rsi(rsiSourceInput, rsiLengthInput)
rsiprevious = rsi
= request.security(syminfo.tickerid, rsiTF1, [rsi, rsi , rsi ], lookahead=barmerge.lookahead_on)
= request.security(syminfo.tickerid, rsiTF2, [rsi, rsi , rsi ], lookahead=barmerge.lookahead_on)
= request.security(syminfo.tickerid, rsiTF3, [rsi, rsi , rsi ], lookahead=barmerge.lookahead_on)
= request.security(syminfo.tickerid, rsiTF4, [rsi, rsi , rsi ], lookahead=barmerge.lookahead_on)
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- MA Calculation -------------------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
ma(source, length, type) =>
switch type
"SMA" => ta.sma(source, length)
"Bollinger Bands" => ta.sma(source, length)
"EMA" => ta.ema(source, length)
"SMMA (RMA)" => ta.rma(source, length)
"WMA" => ta.wma(source, length)
"VWMA" => ta.vwma(source, length)
rsiMA = ma(rsi, maLengthInput, maTypeInput)
rsiMAPrevious = rsiMA
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- Stoch RSI Settings + Calculation --------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
showStochRSI = input(false, title="Show Stochastic RSI", group='Stochastic RSI Settings')
smoothK = input.int(title="Stochastic K", defval=3, minval=1, maxval=10, group='Stochastic RSI Settings')
smoothD = input.int(title="Stochastic D", defval=4, minval=1, maxval=10, group='Stochastic RSI Settings')
lengthRSI = input.int(title="Stochastic RSI Lenght", defval=14, minval=1, group='Stochastic RSI Settings')
lengthStoch = input.int(title="Stochastic Lenght", defval=14, minval=1, group='Stochastic RSI Settings')
colorK = input.color(color.rgb(41,98,255,0), title="K Color", group='Stochastic RSI Settings', inline="1")
colorD = input.color(color.rgb(205,109,0,0), title="D Color", group='Stochastic RSI Settings', inline="1")
StochRSI = ta.rsi(rsiSourceInput, lengthRSI)
k = ta.sma(ta.stoch(StochRSI, StochRSI, StochRSI, lengthStoch), smoothK) //Blue Line
d = ta.sma(k, smoothD) //Red Line
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- Divergence Settings ------------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
bearColor = color.red
bullColor = color.green
hiddenBullColor = color.new(color.green, 50)
hiddenBearColor = color.new(color.red, 50)
//textColor = color.white
noneColor = color.new(color.white, 100)
osc = rsi
plFound = na(ta.pivotlow(osc, lblInput, lbrInput)) ? false : true
phFound = na(ta.pivothigh(osc, lblInput, lbrInput)) ? false : true
_inRange(cond) =>
bars = ta.barssince(cond == true)
lbRangeMinInput <= bars and bars <= lbRangeMaxInput
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- Define Plot & Line Colors ---------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
rsiColor = rsi >= rsiMA ? rsiColorInput : rsimaColorInput
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- Plot Lines ------------------------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
// Create a horizontal line at a specific price level
myLine = line.new(bar_index , 75, bar_index, 75, color = color.rgb(187, 14, 14), width = 2)
bottom = line.new(bar_index , 50, bar_index, 50, color = color.rgb(223, 226, 28), width = 2)
mymainLine = line.new(bar_index , 60, bar_index, 60, color = color.rgb(13, 154, 10), width = 3)
hline(50, title='RSI Baseline', color=color.new(rsiBandColorInput, 50), linestyle=hline.style_solid, editable=false)
hline(rsiBandExtShowInput ? rsiUpperBandExtInput : na, title='RSI Upper Band', color=color.new(rsiBandColorInput, 10), linestyle=hline.style_dashed, editable=false)
hline(rsiBandShowInput ? rsiUpperBandInput : na, title='RSI Upper Band', color=color.new(rsiBandColorInput, 10), linestyle=hline.style_dashed, editable=false)
hline(rsiBandShowInput ? rsiLowerBandInput : na, title='RSI Upper Band', color=color.new(rsiBandColorInput, 10), linestyle=hline.style_dashed, editable=false)
hline(rsiBandExtShowInput ? rsiLowerBandExtInput : na, title='RSI Upper Band', color=color.new(rsiBandColorInput, 10), linestyle=hline.style_dashed, editable=false)
bgcolor(rsiHighlightShowInput ? rsi >= rsiUpperBandExtInput ? color.new(rsiColorInput, 70) : na : na, title="Show Extended Oversold Highlight", editable=false)
bgcolor(rsiHighlightShowInput ? rsi >= rsiUpperBandInput ? rsi < rsiUpperBandExtInput ? color.new(#64ffda, 90) : na : na: na, title="Show Overbought Highlight", editable=false)
bgcolor(rsiHighlightShowInput ? rsi <= rsiLowerBandInput ? rsi > rsiLowerBandExtInput ? color.new(#F43E32, 90) : na : na : na, title="Show Extended Oversold Highlight", editable=false)
bgcolor(rsiHighlightShowInput ? rsi <= rsiLowerBandInput ? color.new(rsimaColorInput, 70) : na : na, title="Show Oversold Highlight", editable=false)
maPlot = plot(maShowInput ? rsiMA : na, title='MA', color=color.new(maColorInput,0), linewidth=1)
rsiMAPlot = plot(showRSIMAInput ? rsiMA : na, title="RSI EMA", color=color.new(rsimaColorInput,0), editable=false, display=display.none)
rsiPlot = plot(rsiShowInput ? rsi : na, title='RSI', color=color.new(rsiColor,0), linewidth=1)
fill(rsiPlot, rsiMAPlot, color=color.new(rsiColor, 60), title="RSIMA Cloud")
plot(showStochRSI ? k : na, title='Stochastic K', color=colorK, linewidth=1)
plot(showStochRSI ? d : na, title='Stochastic D', color=colorD, linewidth=1)
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- Plot Divergence -------------------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
// Regular Bullish
// Osc: Higher Low
oscHL = osc > ta.valuewhen(plFound, osc , 1) and _inRange(plFound )
// Price: Lower Low
priceLL = low < ta.valuewhen(plFound, low , 1)
bullCond = plotBullInput and priceLL and oscHL and plFound
plot(
plFound ? osc : na,
offset=-lbrInput,
title="Regular Bullish",
linewidth=2,
color=(bullCond ? bullColor : noneColor)
)
plotshape(
DivergenceShowInput ? bullCond ? osc : na : na,
offset=-lbrInput,
title="Regular Bullish Label",
text=" Bull ",
style=shape.labelup,
location=location.absolute,
color=bullColor,
textcolor=textColor
)
//------------------------------------------------------------------------------
// Hidden Bullish
// Osc: Lower Low
oscLL = osc < ta.valuewhen(plFound, osc , 1) and _inRange(plFound )
// Price: Higher Low
priceHL = low > ta.valuewhen(plFound, low , 1)
hiddenBullCond = plotHiddenBullInput and priceHL and oscLL and plFound
plot(
plFound ? osc : na,
offset=-lbrInput,
title="Hidden Bullish",
linewidth=2,
color=(hiddenBullCond ? hiddenBullColor : noneColor)
)
plotshape(
DivergenceShowInput ? hiddenBullCond ? osc : na : na,
offset=-lbrInput,
title="Hidden Bullish Label",
text=" H Bull ",
style=shape.labelup,
location=location.absolute,
color=bullColor,
textcolor=textColor
)
//------------------------------------------------------------------------------
// Regular Bearish
// Osc: Lower High
oscLH = osc < ta.valuewhen(phFound, osc , 1) and _inRange(phFound )
// Price: Higher High
priceHH = high > ta.valuewhen(phFound, high , 1)
bearCond = plotBearInput and priceHH and oscLH and phFound
plot(
phFound ? osc : na,
offset=-lbrInput,
title="Regular Bearish",
linewidth=2,
color=(bearCond ? bearColor : noneColor)
)
plotshape(
DivergenceShowInput ? bearCond ? osc : na : na,
offset=-lbrInput,
title="Regular Bearish Label",
text=" Bear ",
style=shape.labeldown,
location=location.absolute,
color=bearColor,
textcolor=textColor
)
//------------------------------------------------------------------------------
// Hidden Bearish
// Osc: Higher High
oscHH = osc > ta.valuewhen(phFound, osc , 1) and _inRange(phFound )
// Price: Lower High
priceLH = high < ta.valuewhen(phFound, high , 1)
hiddenBearCond = plotHiddenBearInput and priceLH and oscHH and phFound
plot(
phFound ? osc : na,
offset=-lbrInput,
title="Hidden Bearish",
linewidth=2,
color=(hiddenBearCond ? hiddenBearColor : noneColor)
)
plotshape(
DivergenceShowInput ? hiddenBearCond ? osc : na : na,
offset=-lbrInput,
title="Hidden Bearish Label",
text=" H Bear ",
style=shape.labeldown,
location=location.absolute,
color=bearColor,
textcolor=textColor
)
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- Check RSI Lineup ------------------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
bullTF = rsi > rsi and rsi > rsi
bearTF = rsi < rsi and rsi < rsi
bullTF1 = rsi1 > rsi1_1 and rsi1_1 > rsi1_2
bearTF1 = rsi1 < rsi1_1 and rsi1_1 < rsi1_2
bullTF2 = rsi2 > rsi2_1 and rsi2_1 > rsi2_2
bearTF2 = rsi2 < rsi2_1 and rsi2_1 < rsi2_2
bullTF3 = rsi3 > rsi3_1 and rsi3_1 > rsi3_2
bearTF3 = rsi3 < rsi3_1 and rsi3_1 < rsi3_2
bullTF4 = rsi4 > rsi4_1 and rsi4_1 > rsi4_2
bearTF4 = rsi4 < rsi4_1 and rsi4_1 < rsi4_2
bbTxt(bull,bear) =>
bull ? "BULLISH" : bear ? "BEARISCH" : 'NO LINEUP'
bbColor(bull,bear) =>
bull ? bullishColor : bear ? bearishColor : nomatchColor
newTC(tBox, col, row, txt, width, txtColor, bgColor, txtHA, txtSize) =>
table.cell(table_id=tBox,column=col, row=row, text=txt, width=width,text_color=txtColor,bgcolor=bgColor, text_halign=txtHA, text_size=txtSize)
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
//--- Define RSI Table Setting ----------------------------------------------------------------------------------------------------------------------------------------
//---------------------------------------------------------------------------------------------------------------------------------------------------------------------
width_c0 = 0
width_c1 = 0
if rsiShowTable
var tBox = table.new(position=rsiTablePosition, columns=5, rows=6, bgcolor=color.rgb(18,22,33,50), frame_color=color.black, frame_width=1, border_color=color.black, border_width=1)
newTC(tBox, 0,1,"RSI Current",width_c0,color.orange,color.rgb(0,0,0,100),'right',rsiTextSize)
newTC(tBox, 1,1,str.format(" {0,number,#.##} ", rsi),width_c0,vWhite,rsi < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
newTC(tBox, 4,1,bbTxt(bullTF, bearTF),width_c0,vWhite,bbColor(bullTF, bearTF),'center',rsiTextSize)
if rsiShowHist
newTC(tBox, 2,1,str.format(" {0,number,#.##} ", rsi ),width_c0,vWhite,rsi < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
newTC(tBox, 3,1,str.format(" {0,number,#.##} ", rsi ),width_c0,vWhite,rsi < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
if rsiShowTF1
newTC(tBox, 0,2,TF2txt(rsiTF1),width_c0,vWhite,color.rgb(0,0,0,100),'right',rsiTextSize)
newTC(tBox, 1,2,str.format(" {0,number,#.##} ", rsi1),width_c0,vWhite,rsi1 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
newTC(tBox, 4,2,bbTxt(bullTF1, bearTF1),width_c0,vWhite,bbColor(bullTF1,bearTF1),'center',rsiTextSize)
if rsiShowHist
newTC(tBox, 2,2,str.format(" {0,number,#.##} ", rsi1_1),width_c0,vWhite,rsi1_1 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
newTC(tBox, 3,2,str.format(" {0,number,#.##} ", rsi1_2),width_c0,vWhite,rsi1_2 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
if rsiShowTF2
newTC(tBox, 0,3,TF2txt(rsiTF2),width_c0,vWhite,color.rgb(0,0,0,100),'right',rsiTextSize)
newTC(tBox, 1,3,str.format(" {0,number,#.##} ", rsi2),width_c0,vWhite,rsi2 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
newTC(tBox, 4,3,bbTxt(bullTF2, bearTF2),width_c0,vWhite,bbColor(bullTF2,bearTF2),'center',rsiTextSize)
if rsiShowHist
newTC(tBox, 2,3,str.format(" {0,number,#.##} ", rsi2_1),width_c0,vWhite,rsi2_1 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
newTC(tBox, 3,3,str.format(" {0,number,#.##} ", rsi2_2),width_c0,vWhite,rsi2_2 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
if rsiShowTF3
newTC(tBox, 0,4,TF2txt(rsiTF3),width_c0,vWhite,color.rgb(0,0,0,100),'right',rsiTextSize)
newTC(tBox, 1,4,str.format(" {0,number,#.##} ", rsi3),width_c0,vWhite,rsi3 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
newTC(tBox, 4,4,bbTxt(bullTF3, bearTF3),width_c0,vWhite,bbColor(bullTF3,bearTF3),'center',rsiTextSize)
if rsiShowHist
newTC(tBox, 2,4,str.format(" {0,number,#.##} ", rsi3_1),width_c0,vWhite,rsi3_1 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
newTC(tBox, 3,4,str.format(" {0,number,#.##} ", rsi3_2),width_c0,vWhite,rsi3_2 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
if rsiShowTF4
newTC(tBox, 0,5,TF2txt(rsiTF4),width_c0,vWhite,color.rgb(0,0,0,100),'right',rsiTextSize)
newTC(tBox, 1,5,str.format(" {0,number,#.##} ", rsi4),width_c0,vWhite,rsi4 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
newTC(tBox, 4,5,bbTxt(bullTF4, bearTF4),width_c0,vWhite,bbColor(bullTF4,bearTF4),'center',rsiTextSize)
if rsiShowHist
newTC(tBox, 2,5,str.format(" {0,number,#.##} ", rsi4_1),width_c0,vWhite,rsi4_1 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
newTC(tBox, 3,5,str.format(" {0,number,#.##} ", rsi4_2),width_c0,vWhite,rsi4_2 < 50 ? bearishColor:bullishColor,'left',rsiTextSize)
//------------------------------------------------------
//--- Alerts -------------------------------------------
//------------------------------------------------------
KRX RS OverlayKRX RS Overlay (Manual, Pine v6) (한국어 설명 아래에)
What it does
Plots a Relative Strength (RS) line of the current symbol versus a selected Korean market index on the price chart (overlay). RS is computed as Close(symbol) / Close(benchmark) and rebased to 100 N bars ago for easy comparison. An SMA of RS is included for signal smoothing.
Benchmarks (manual selection only)
• KOSPI (KRX:KOSPI) — default
• KOSDAQ (KRX:KOSDAQ)
• KOSPI200 (KRX:KOSPI200)
• KOSDAQ150 (KRX:KOSDAQ150)
Inputs
• Benchmark: choose one of the four indices above (default: KOSPI)
• Rebase N bars ago to 100: sets the normalization point (e.g., 252 ≈ 1 trading year on daily)
• RS SMA length: smoothing period for the RS line
• Show 100 base line: toggle the reference line at 100
How to read
• RS rising → the symbol is outperforming the selected index.
• RS above RS-SMA and sloping up → strengthening leadership vs. the benchmark.
• RS crossing above RS-SMA → momentum-style confirmation (an alert is provided).
Tips
• Works on any timeframe; the benchmark is requested on the same timeframe.
• If the RS line scale conflicts with price, place the indicator on the Left scale (Chart Settings → Scales) or set the series to use the left axis.
Notes
• This script is manual only (no auto index detection).
• Educational use; not financial advice.
⸻
KRX RS 오버레이 (수동, Pine v6)
기능
현재 종목을 선택한 한국 지수와 비교한 상대강도(RS) 라인을 가격 차트 위(오버레이)에 표시합니다. RS는 종목 종가 / 지수 종가로 계산하며, 비교를 쉽게 하기 위해 N봉 전 = 100으로 리베이스합니다. 신호 완화를 위해 RS의 SMA도 함께 제공합니다.
벤치마크(수동 선택만 지원)
• KOSPI (KRX:KOSPI) — 기본값
• KOSDAQ (KRX:KOSDAQ)
• KOSPI200 (KRX:KOSPI200)
• KOSDAQ150 (KRX:KOSDAQ150)
입력값
• Benchmark: 위 4개 지수 중 선택(기본: KOSPI)
• Rebase N bars ago to 100: 리베이스 기준(일봉 252 ≈ 1년)
• RS SMA length: RS 스무딩 기간
• Show 100 base line: 100 기준선 표시 여부
해석 가이드
• RS 상승 → 선택 지수 대비 초과성과.
• RS가 RS-SMA 위 & 우상향 → 벤치마크 대비 리더십 강화.
• RS가 RS-SMA 상향 돌파 → 모멘텀 확인(알림 제공).
팁
• 모든 타임프레임에서 동작하며, 지수도 동일 타임프레임으로 요청됩니다.
• 가격 축과 스케일이 겹치면 왼쪽 스케일로 표시하도록 설정하세요(차트 설정 → Scales).
유의사항
• 자동 지수 판별 기능은 포함하지 않았습니다(수동 전용).
Quantum Rotational Field MappingQuantum Rotational Field Mapping (QRFM):
Phase Coherence Detection Through Complex-Plane Oscillator Analysis
Quantum Rotational Field Mapping applies complex-plane mathematics and phase-space analysis to oscillator ensembles, identifying high-probability trend ignition points by measuring when multiple independent oscillators achieve phase coherence. Unlike traditional multi-oscillator approaches that simply stack indicators or use boolean AND/OR logic, this system converts each oscillator into a rotating phasor (vector) in the complex plane and calculates the Coherence Index (CI) —a mathematical measure of how tightly aligned the ensemble has become—then generates signals only when alignment, phase direction, and pairwise entanglement all converge.
The indicator combines three mathematical frameworks: phasor representation using analytic signal theory to extract phase and amplitude from each oscillator, coherence measurement using vector summation in the complex plane to quantify group alignment, and entanglement analysis that calculates pairwise phase agreement across all oscillator combinations. This creates a multi-dimensional confirmation system that distinguishes between random oscillator noise and genuine regime transitions.
What Makes This Original
Complex-Plane Phasor Framework
This indicator implements classical signal processing mathematics adapted for market oscillators. Each oscillator—whether RSI, MACD, Stochastic, CCI, Williams %R, MFI, ROC, or TSI—is first normalized to a common scale, then converted into a complex-plane representation using an in-phase (I) and quadrature (Q) component. The in-phase component is the oscillator value itself, while the quadrature component is calculated as the first difference (derivative proxy), creating a velocity-aware representation.
From these components, the system extracts:
Phase (φ) : Calculated as φ = atan2(Q, I), representing the oscillator's position in its cycle (mapped to -180° to +180°)
Amplitude (A) : Calculated as A = √(I² + Q²), representing the oscillator's strength or conviction
This mathematical approach is fundamentally different from simply reading oscillator values. A phasor captures both where an oscillator is in its cycle (phase angle) and how strongly it's expressing that position (amplitude). Two oscillators can have the same value but be in opposite phases of their cycles—traditional analysis would see them as identical, while QRFM sees them as 180° out of phase (contradictory).
Coherence Index Calculation
The core innovation is the Coherence Index (CI) , borrowed from physics and signal processing. When you have N oscillators, each with phase φₙ, you can represent each as a unit vector in the complex plane: e^(iφₙ) = cos(φₙ) + i·sin(φₙ).
The CI measures what happens when you sum all these vectors:
Resultant Vector : R = Σ e^(iφₙ) = Σ cos(φₙ) + i·Σ sin(φₙ)
Coherence Index : CI = |R| / N
Where |R| is the magnitude of the resultant vector and N is the number of active oscillators.
The CI ranges from 0 to 1:
CI = 1.0 : Perfect coherence—all oscillators have identical phase angles, vectors point in the same direction, creating maximum constructive interference
CI = 0.0 : Complete decoherence—oscillators are randomly distributed around the circle, vectors cancel out through destructive interference
0 < CI < 1 : Partial alignment—some clustering with some scatter
This is not a simple average or correlation. The CI captures phase synchronization across the entire ensemble simultaneously. When oscillators phase-lock (align their cycles), the CI spikes regardless of their individual values. This makes it sensitive to regime transitions that traditional indicators miss.
Dominant Phase and Direction Detection
Beyond measuring alignment strength, the system calculates the dominant phase of the ensemble—the direction the resultant vector points:
Dominant Phase : φ_dom = atan2(Σ sin(φₙ), Σ cos(φₙ))
This gives the "average direction" of all oscillator phases, mapped to -180° to +180°:
+90° to -90° (right half-plane): Bullish phase dominance
+90° to +180° or -90° to -180° (left half-plane): Bearish phase dominance
The combination of CI magnitude (coherence strength) and dominant phase angle (directional bias) creates a two-dimensional signal space. High CI alone is insufficient—you need high CI plus dominant phase pointing in a tradeable direction. This dual requirement is what separates QRFM from simple oscillator averaging.
Entanglement Matrix and Pairwise Coherence
While the CI measures global alignment, the entanglement matrix measures local pairwise relationships. For every pair of oscillators (i, j), the system calculates:
E(i,j) = |cos(φᵢ - φⱼ)|
This represents the phase agreement between oscillators i and j:
E = 1.0 : Oscillators are in-phase (0° or 360° apart)
E = 0.0 : Oscillators are in quadrature (90° apart, orthogonal)
E between 0 and 1 : Varying degrees of alignment
The system counts how many oscillator pairs exceed a user-defined entanglement threshold (e.g., 0.7). This entangled pairs count serves as a confirmation filter: signals require not just high global CI, but also a minimum number of strong pairwise agreements. This prevents false ignitions where CI is high but driven by only two oscillators while the rest remain scattered.
The entanglement matrix creates an N×N symmetric matrix that can be visualized as a web—when many cells are bright (high E values), the ensemble is highly interconnected. When cells are dark, oscillators are moving independently.
Phase-Lock Tolerance Mechanism
A complementary confirmation layer is the phase-lock detector . This calculates the maximum phase spread across all oscillators:
For all pairs (i,j), compute angular distance: Δφ = |φᵢ - φⱼ|, wrapping at 180°
Max Spread = maximum Δφ across all pairs
If max spread < user threshold (e.g., 35°), the ensemble is considered phase-locked —all oscillators are within a narrow angular band.
This differs from entanglement: entanglement measures pairwise cosine similarity (magnitude of alignment), while phase-lock measures maximum angular deviation (tightness of clustering). Both must be satisfied for the highest-conviction signals.
Multi-Layer Visual Architecture
QRFM includes six visual components that represent the same underlying mathematics from different perspectives:
Circular Orbit Plot : A polar coordinate grid showing each oscillator as a vector from origin to perimeter. Angle = phase, radius = amplitude. This is a real-time snapshot of the complex plane. When vectors converge (point in similar directions), coherence is high. When scattered randomly, coherence is low. Users can see phase alignment forming before CI numerically confirms it.
Phase-Time Heat Map : A 2D matrix with rows = oscillators and columns = time bins. Each cell is colored by the oscillator's phase at that time (using a gradient where color hue maps to angle). Horizontal color bands indicate sustained phase alignment over time. Vertical color bands show moments when all oscillators shared the same phase (ignition points). This provides historical pattern recognition.
Entanglement Web Matrix : An N×N grid showing E(i,j) for all pairs. Cells are colored by entanglement strength—bright yellow/gold for high E, dark gray for low E. This reveals which oscillators are driving coherence and which are lagging. For example, if RSI and MACD show high E but Stochastic shows low E with everything, Stochastic is the outlier.
Quantum Field Cloud : A background color overlay on the price chart. Color (green = bullish, red = bearish) is determined by dominant phase. Opacity is determined by CI—high CI creates dense, opaque cloud; low CI creates faint, nearly invisible cloud. This gives an atmospheric "feel" for regime strength without looking at numbers.
Phase Spiral : A smoothed plot of dominant phase over recent history, displayed as a curve that wraps around price. When the spiral is tight and rotating steadily, the ensemble is in coherent rotation (trending). When the spiral is loose or erratic, coherence is breaking down.
Dashboard : A table showing real-time metrics: CI (as percentage), dominant phase (in degrees with directional arrow), field strength (CI × average amplitude), entangled pairs count, phase-lock status (locked/unlocked), quantum state classification ("Ignition", "Coherent", "Collapse", "Chaos"), and collapse risk (recent CI change normalized to 0-100%).
Each component is independently toggleable, allowing users to customize their workspace. The orbit plot is the most essential—it provides intuitive, visual feedback on phase alignment that no numerical dashboard can match.
Core Components and How They Work Together
1. Oscillator Normalization Engine
The foundation is creating a common measurement scale. QRFM supports eight oscillators:
RSI : Normalized from to using overbought/oversold levels (70, 30) as anchors
MACD Histogram : Normalized by dividing by rolling standard deviation, then clamped to
Stochastic %K : Normalized from using (80, 20) anchors
CCI : Divided by 200 (typical extreme level), clamped to
Williams %R : Normalized from using (-20, -80) anchors
MFI : Normalized from using (80, 20) anchors
ROC : Divided by 10, clamped to
TSI : Divided by 50, clamped to
Each oscillator can be individually enabled/disabled. Only active oscillators contribute to phase calculations. The normalization removes scale differences—a reading of +0.8 means "strongly bullish" regardless of whether it came from RSI or TSI.
2. Analytic Signal Construction
For each active oscillator at each bar, the system constructs the analytic signal:
In-Phase (I) : The normalized oscillator value itself
Quadrature (Q) : The bar-to-bar change in the normalized value (first derivative approximation)
This creates a 2D representation: (I, Q). The phase is extracted as:
φ = atan2(Q, I) × (180 / π)
This maps the oscillator to a point on the unit circle. An oscillator at the same value but rising (positive Q) will have a different phase than one that is falling (negative Q). This velocity-awareness is critical—it distinguishes between "at resistance and stalling" versus "at resistance and breaking through."
The amplitude is extracted as:
A = √(I² + Q²)
This represents the distance from origin in the (I, Q) plane. High amplitude means the oscillator is far from neutral (strong conviction). Low amplitude means it's near zero (weak/transitional state).
3. Coherence Calculation Pipeline
For each bar (or every Nth bar if phase sample rate > 1 for performance):
Step 1 : Extract phase φₙ for each of the N active oscillators
Step 2 : Compute complex exponentials: Zₙ = e^(i·φₙ·π/180) = cos(φₙ·π/180) + i·sin(φₙ·π/180)
Step 3 : Sum the complex exponentials: R = Σ Zₙ = (Σ cos φₙ) + i·(Σ sin φₙ)
Step 4 : Calculate magnitude: |R| = √
Step 5 : Normalize by count: CI_raw = |R| / N
Step 6 : Smooth the CI: CI = SMA(CI_raw, smoothing_window)
The smoothing step (default 2 bars) removes single-bar noise spikes while preserving structural coherence changes. Users can adjust this to control reactivity versus stability.
The dominant phase is calculated as:
φ_dom = atan2(Σ sin φₙ, Σ cos φₙ) × (180 / π)
This is the angle of the resultant vector R in the complex plane.
4. Entanglement Matrix Construction
For all unique pairs of oscillators (i, j) where i < j:
Step 1 : Get phases φᵢ and φⱼ
Step 2 : Compute phase difference: Δφ = φᵢ - φⱼ (in radians)
Step 3 : Calculate entanglement: E(i,j) = |cos(Δφ)|
Step 4 : Store in symmetric matrix: matrix = matrix = E(i,j)
The matrix is then scanned: count how many E(i,j) values exceed the user-defined threshold (default 0.7). This count is the entangled pairs metric.
For visualization, the matrix is rendered as an N×N table where cell brightness maps to E(i,j) intensity.
5. Phase-Lock Detection
Step 1 : For all unique pairs (i, j), compute angular distance: Δφ = |φᵢ - φⱼ|
Step 2 : Wrap angles: if Δφ > 180°, set Δφ = 360° - Δφ
Step 3 : Find maximum: max_spread = max(Δφ) across all pairs
Step 4 : Compare to tolerance: phase_locked = (max_spread < tolerance)
If phase_locked is true, all oscillators are within the specified angular cone (e.g., 35°). This is a boolean confirmation filter.
6. Signal Generation Logic
Signals are generated through multi-layer confirmation:
Long Ignition Signal :
CI crosses above ignition threshold (e.g., 0.80)
AND dominant phase is in bullish range (-90° < φ_dom < +90°)
AND phase_locked = true
AND entangled_pairs >= minimum threshold (e.g., 4)
Short Ignition Signal :
CI crosses above ignition threshold
AND dominant phase is in bearish range (φ_dom < -90° OR φ_dom > +90°)
AND phase_locked = true
AND entangled_pairs >= minimum threshold
Collapse Signal :
CI at bar minus CI at current bar > collapse threshold (e.g., 0.55)
AND CI at bar was above 0.6 (must collapse from coherent state, not from already-low state)
These are strict conditions. A high CI alone does not generate a signal—dominant phase must align with direction, oscillators must be phase-locked, and sufficient pairwise entanglement must exist. This multi-factor gating dramatically reduces false signals compared to single-condition triggers.
Calculation Methodology
Phase 1: Oscillator Computation and Normalization
On each bar, the system calculates the raw values for all enabled oscillators using standard Pine Script functions:
RSI: ta.rsi(close, length)
MACD: ta.macd() returning histogram component
Stochastic: ta.stoch() smoothed with ta.sma()
CCI: ta.cci(close, length)
Williams %R: ta.wpr(length)
MFI: ta.mfi(hlc3, length)
ROC: ta.roc(close, length)
TSI: ta.tsi(close, short, long)
Each raw value is then passed through a normalization function:
normalize(value, overbought_level, oversold_level) = 2 × (value - oversold) / (overbought - oversold) - 1
This maps the oscillator's typical range to , where -1 represents extreme bearish, 0 represents neutral, and +1 represents extreme bullish.
For oscillators without fixed ranges (MACD, ROC, TSI), statistical normalization is used: divide by a rolling standard deviation or fixed divisor, then clamp to .
Phase 2: Phasor Extraction
For each normalized oscillator value val:
I = val (in-phase component)
Q = val - val (quadrature component, first difference)
Phase calculation:
phi_rad = atan2(Q, I)
phi_deg = phi_rad × (180 / π)
Amplitude calculation:
A = √(I² + Q²)
These values are stored in arrays: osc_phases and osc_amps for each oscillator n.
Phase 3: Complex Summation and Coherence
Initialize accumulators:
sum_cos = 0
sum_sin = 0
For each oscillator n = 0 to N-1:
phi_rad = osc_phases × (π / 180)
sum_cos += cos(phi_rad)
sum_sin += sin(phi_rad)
Resultant magnitude:
resultant_mag = √(sum_cos² + sum_sin²)
Coherence Index (raw):
CI_raw = resultant_mag / N
Smoothed CI:
CI = SMA(CI_raw, smoothing_window)
Dominant phase:
phi_dom_rad = atan2(sum_sin, sum_cos)
phi_dom_deg = phi_dom_rad × (180 / π)
Phase 4: Entanglement Matrix Population
For i = 0 to N-2:
For j = i+1 to N-1:
phi_i = osc_phases × (π / 180)
phi_j = osc_phases × (π / 180)
delta_phi = phi_i - phi_j
E = |cos(delta_phi)|
matrix_index_ij = i × N + j
matrix_index_ji = j × N + i
entangle_matrix = E
entangle_matrix = E
if E >= threshold:
entangled_pairs += 1
The matrix uses flat array storage with index mapping: index(row, col) = row × N + col.
Phase 5: Phase-Lock Check
max_spread = 0
For i = 0 to N-2:
For j = i+1 to N-1:
delta = |osc_phases - osc_phases |
if delta > 180:
delta = 360 - delta
max_spread = max(max_spread, delta)
phase_locked = (max_spread < tolerance)
Phase 6: Signal Evaluation
Ignition Long :
ignition_long = (CI crosses above threshold) AND
(phi_dom > -90 AND phi_dom < 90) AND
phase_locked AND
(entangled_pairs >= minimum)
Ignition Short :
ignition_short = (CI crosses above threshold) AND
(phi_dom < -90 OR phi_dom > 90) AND
phase_locked AND
(entangled_pairs >= minimum)
Collapse :
CI_prev = CI
collapse = (CI_prev - CI > collapse_threshold) AND (CI_prev > 0.6)
All signals are evaluated on bar close. The crossover and crossunder functions ensure signals fire only once when conditions transition from false to true.
Phase 7: Field Strength and Visualization Metrics
Average Amplitude :
avg_amp = (Σ osc_amps ) / N
Field Strength :
field_strength = CI × avg_amp
Collapse Risk (for dashboard):
collapse_risk = (CI - CI) / max(CI , 0.1)
collapse_risk_pct = clamp(collapse_risk × 100, 0, 100)
Quantum State Classification :
if (CI > threshold AND phase_locked):
state = "Ignition"
else if (CI > 0.6):
state = "Coherent"
else if (collapse):
state = "Collapse"
else:
state = "Chaos"
Phase 8: Visual Rendering
Orbit Plot : For each oscillator, convert polar (phase, amplitude) to Cartesian (x, y) for grid placement:
radius = amplitude × grid_center × 0.8
x = radius × cos(phase × π/180)
y = radius × sin(phase × π/180)
col = center + x (mapped to grid coordinates)
row = center - y
Heat Map : For each oscillator row and time column, retrieve historical phase value at lookback = (columns - col) × sample_rate, then map phase to color using a hue gradient.
Entanglement Web : Render matrix as table cell with background color opacity = E(i,j).
Field Cloud : Background color = (phi_dom > -90 AND phi_dom < 90) ? green : red, with opacity = mix(min_opacity, max_opacity, CI).
All visual components render only on the last bar (barstate.islast) to minimize computational overhead.
How to Use This Indicator
Step 1 : Apply QRFM to your chart. It works on all timeframes and asset classes, though 15-minute to 4-hour timeframes provide the best balance of responsiveness and noise reduction.
Step 2 : Enable the dashboard (default: top right) and the circular orbit plot (default: middle left). These are your primary visual feedback tools.
Step 3 : Optionally enable the heat map, entanglement web, and field cloud based on your preference. New users may find all visuals overwhelming; start with dashboard + orbit plot.
Step 4 : Observe for 50-100 bars to let the indicator establish baseline coherence patterns. Markets have different "normal" CI ranges—some instruments naturally run higher or lower coherence.
Understanding the Circular Orbit Plot
The orbit plot is a polar grid showing oscillator vectors in real-time:
Center point : Neutral (zero phase and amplitude)
Each vector : A line from center to a point on the grid
Vector angle : The oscillator's phase (0° = right/east, 90° = up/north, 180° = left/west, -90° = down/south)
Vector length : The oscillator's amplitude (short = weak signal, long = strong signal)
Vector label : First letter of oscillator name (R = RSI, M = MACD, etc.)
What to watch :
Convergence : When all vectors cluster in one quadrant or sector, CI is rising and coherence is forming. This is your pre-signal warning.
Scatter : When vectors point in random directions (360° spread), CI is low and the market is in a non-trending or transitional regime.
Rotation : When the cluster rotates smoothly around the circle, the ensemble is in coherent oscillation—typically seen during steady trends.
Sudden flips : When the cluster rapidly jumps from one side to the opposite (e.g., +90° to -90°), a phase reversal has occurred—often coinciding with trend reversals.
Example: If you see RSI, MACD, and Stochastic all pointing toward 45° (northeast) with long vectors, while CCI, TSI, and ROC point toward 40-50° as well, coherence is high and dominant phase is bullish. Expect an ignition signal if CI crosses threshold.
Reading Dashboard Metrics
The dashboard provides numerical confirmation of what the orbit plot shows visually:
CI : Displays as 0-100%. Above 70% = high coherence (strong regime), 40-70% = moderate, below 40% = low (poor conditions for trend entries).
Dom Phase : Angle in degrees with directional arrow. ⬆ = bullish bias, ⬇ = bearish bias, ⬌ = neutral.
Field Strength : CI weighted by amplitude. High values (> 0.6) indicate not just alignment but strong alignment.
Entangled Pairs : Count of oscillator pairs with E > threshold. Higher = more confirmation. If minimum is set to 4, you need at least 4 pairs entangled for signals.
Phase Lock : 🔒 YES (all oscillators within tolerance) or 🔓 NO (spread too wide).
State : Real-time classification:
🚀 IGNITION: CI just crossed threshold with phase-lock
⚡ COHERENT: CI is high and stable
💥 COLLAPSE: CI has dropped sharply
🌀 CHAOS: Low CI, scattered phases
Collapse Risk : 0-100% scale based on recent CI change. Above 50% warns of imminent breakdown.
Interpreting Signals
Long Ignition (Blue Triangle Below Price) :
Occurs when CI crosses above threshold (e.g., 0.80)
Dominant phase is in bullish range (-90° to +90°)
All oscillators are phase-locked (within tolerance)
Minimum entangled pairs requirement met
Interpretation : The oscillator ensemble has transitioned from disorder to coherent bullish alignment. This is a high-probability long entry point. The multi-layer confirmation (CI + phase direction + lock + entanglement) ensures this is not a single-oscillator whipsaw.
Short Ignition (Red Triangle Above Price) :
Same conditions as long, but dominant phase is in bearish range (< -90° or > +90°)
Interpretation : Coherent bearish alignment has formed. High-probability short entry.
Collapse (Circles Above and Below Price) :
CI has dropped by more than the collapse threshold (e.g., 0.55) over a 5-bar window
CI was previously above 0.6 (collapsing from coherent state)
Interpretation : Phase coherence has broken down. If you are in a position, this is an exit warning. If looking to enter, stand aside—regime is transitioning.
Phase-Time Heat Map Patterns
Enable the heat map and position it at bottom right. The rows represent individual oscillators, columns represent time bins (most recent on left).
Pattern: Horizontal Color Bands
If a row (e.g., RSI) shows consistent color across columns (say, green for several bins), that oscillator has maintained stable phase over time. If all rows show horizontal bands of similar color, the entire ensemble has been phase-locked for an extended period—this is a strong trending regime.
Pattern: Vertical Color Bands
If a column (single time bin) shows all cells with the same or very similar color, that moment in time had high coherence. These vertical bands often align with ignition signals or major price pivots.
Pattern: Rainbow Chaos
If cells are random colors (red, green, yellow mixed with no pattern), coherence is low. The ensemble is scattered. Avoid trading during these periods unless you have external confirmation.
Pattern: Color Transition
If you see a row transition from red to green (or vice versa) sharply, that oscillator has phase-flipped. If multiple rows do this simultaneously, a regime change is underway.
Entanglement Web Analysis
Enable the web matrix (default: opposite corner from heat map). It shows an N×N grid where N = number of active oscillators.
Bright Yellow/Gold Cells : High pairwise entanglement. For example, if the RSI-MACD cell is bright gold, those two oscillators are moving in phase. If the RSI-Stochastic cell is bright, they are entangled as well.
Dark Gray Cells : Low entanglement. Oscillators are decorrelated or in quadrature.
Diagonal : Always marked with "—" because an oscillator is always perfectly entangled with itself.
How to use :
Scan for clustering: If most cells are bright, coherence is high across the board. If only a few cells are bright, coherence is driven by a subset (e.g., RSI and MACD are aligned, but nothing else is—weak signal).
Identify laggards: If one row/column is entirely dark, that oscillator is the outlier. You may choose to disable it or monitor for when it joins the group (late confirmation).
Watch for web formation: During low-coherence periods, the matrix is mostly dark. As coherence builds, cells begin lighting up. A sudden "web" of connections forming visually precedes ignition signals.
Trading Workflow
Step 1: Monitor Coherence Level
Check the dashboard CI metric or observe the orbit plot. If CI is below 40% and vectors are scattered, conditions are poor for trend entries. Wait.
Step 2: Detect Coherence Building
When CI begins rising (say, from 30% to 50-60%) and you notice vectors on the orbit plot starting to cluster, coherence is forming. This is your alert phase—do not enter yet, but prepare.
Step 3: Confirm Phase Direction
Check the dominant phase angle and the orbit plot quadrant where clustering is occurring:
Clustering in right half (0° to ±90°): Bullish bias forming
Clustering in left half (±90° to 180°): Bearish bias forming
Verify the dashboard shows the corresponding directional arrow (⬆ or ⬇).
Step 4: Wait for Signal Confirmation
Do not enter based on rising CI alone. Wait for the full ignition signal:
CI crosses above threshold
Phase-lock indicator shows 🔒 YES
Entangled pairs count >= minimum
Directional triangle appears on chart
This ensures all layers have aligned.
Step 5: Execute Entry
Long : Blue triangle below price appears → enter long
Short : Red triangle above price appears → enter short
Step 6: Position Management
Initial Stop : Place stop loss based on your risk management rules (e.g., recent swing low/high, ATR-based buffer).
Monitoring :
Watch the field cloud density. If it remains opaque and colored in your direction, the regime is intact.
Check dashboard collapse risk. If it rises above 50%, prepare for exit.
Monitor the orbit plot. If vectors begin scattering or the cluster flips to the opposite side, coherence is breaking.
Exit Triggers :
Collapse signal fires (circles appear)
Dominant phase flips to opposite half-plane
CI drops below 40% (coherence lost)
Price hits your profit target or trailing stop
Step 7: Post-Exit Analysis
After exiting, observe whether a new ignition forms in the opposite direction (reversal) or if CI remains low (transition to range). Use this to decide whether to re-enter, reverse, or stand aside.
Best Practices
Use Price Structure as Context
QRFM identifies when coherence forms but does not specify where price will go. Combine ignition signals with support/resistance levels, trendlines, or chart patterns. For example:
Long ignition near a major support level after a pullback: high-probability bounce
Long ignition in the middle of a range with no structure: lower probability
Multi-Timeframe Confirmation
Open QRFM on two timeframes simultaneously:
Higher timeframe (e.g., 4-hour): Use CI level to determine regime bias. If 4H CI is above 60% and dominant phase is bullish, the market is in a bullish regime.
Lower timeframe (e.g., 15-minute): Execute entries on ignition signals that align with the higher timeframe bias.
This prevents counter-trend trades and increases win rate.
Distinguish Between Regime Types
High CI, stable dominant phase (State: Coherent) : Trending market. Ignitions are continuation signals; collapses are profit-taking or reversal warnings.
Low CI, erratic dominant phase (State: Chaos) : Ranging or choppy market. Avoid ignition signals or reduce position size. Wait for coherence to establish.
Moderate CI with frequent collapses : Whipsaw environment. Use wider stops or stand aside.
Adjust Parameters to Instrument and Timeframe
Crypto/Forex (high volatility) : Lower ignition threshold (0.65-0.75), lower CI smoothing (2-3), shorter oscillator lengths (7-10).
Stocks/Indices (moderate volatility) : Standard settings (threshold 0.75-0.85, smoothing 5-7, oscillator lengths 14).
Lower timeframes (5-15 min) : Reduce phase sample rate to 1-2 for responsiveness.
Higher timeframes (daily+) : Increase CI smoothing and oscillator lengths for noise reduction.
Use Entanglement Count as Conviction Filter
The minimum entangled pairs setting controls signal strictness:
Low (1-2) : More signals, lower quality (acceptable if you have other confirmation)
Medium (3-5) : Balanced (recommended for most traders)
High (6+) : Very strict, fewer signals, highest quality
Adjust based on your trade frequency preference and risk tolerance.
Monitor Oscillator Contribution
Use the entanglement web to see which oscillators are driving coherence. If certain oscillators are consistently dark (low E with all others), they may be adding noise. Consider disabling them. For example:
On low-volume instruments, MFI may be unreliable → disable MFI
On strongly trending instruments, mean-reversion oscillators (Stochastic, RSI) may lag → reduce weight or disable
Respect the Collapse Signal
Collapse events are early warnings. Price may continue in the original direction for several bars after collapse fires, but the underlying regime has weakened. Best practice:
If in profit: Take partial or full profit on collapse
If at breakeven/small loss: Exit immediately
If collapse occurs shortly after entry: Likely a false ignition; exit to avoid drawdown
Collapses do not guarantee immediate reversals—they signal uncertainty .
Combine with Volume Analysis
If your instrument has reliable volume:
Ignitions with expanding volume: Higher conviction
Ignitions with declining volume: Weaker, possibly false
Collapses with volume spikes: Strong reversal signal
Collapses with low volume: May just be consolidation
Volume is not built into QRFM (except via MFI), so add it as external confirmation.
Observe the Phase Spiral
The spiral provides a quick visual cue for rotation consistency:
Tight, smooth spiral : Ensemble is rotating coherently (trending)
Loose, erratic spiral : Phase is jumping around (ranging or transitional)
If the spiral tightens, coherence is building. If it loosens, coherence is dissolving.
Do Not Overtrade Low-Coherence Periods
When CI is persistently below 40% and the state is "Chaos," the market is not in a regime where phase analysis is predictive. During these times:
Reduce position size
Widen stops
Wait for coherence to return
QRFM's strength is regime detection. If there is no regime, the tool correctly signals "stand aside."
Use Alerts Strategically
Set alerts for:
Long Ignition
Short Ignition
Collapse
Phase Lock (optional)
Configure alerts to "Once per bar close" to avoid intrabar repainting and noise. When an alert fires, manually verify:
Orbit plot shows clustering
Dashboard confirms all conditions
Price structure supports the trade
Do not blindly trade alerts—use them as prompts for analysis.
Ideal Market Conditions
Best Performance
Instruments :
Liquid, actively traded markets (major forex pairs, large-cap stocks, major indices, top-tier crypto)
Instruments with clear cyclical oscillator behavior (avoid extremely illiquid or manipulated markets)
Timeframes :
15-minute to 4-hour: Optimal balance of noise reduction and responsiveness
1-hour to daily: Slower, higher-conviction signals; good for swing trading
5-minute: Acceptable for scalping if parameters are tightened and you accept more noise
Market Regimes :
Trending markets with periodic retracements (where oscillators cycle through phases predictably)
Breakout environments (coherence forms before/during breakout; collapse occurs at exhaustion)
Rotational markets with clear swings (oscillators phase-lock at turning points)
Volatility :
Moderate to high volatility (oscillators have room to move through their ranges)
Stable volatility regimes (sudden VIX spikes or flash crashes may create false collapses)
Challenging Conditions
Instruments :
Very low liquidity markets (erratic price action creates unstable oscillator phases)
Heavily news-driven instruments (fundamentals may override technical coherence)
Highly correlated instruments (oscillators may all reflect the same underlying factor, reducing independence)
Market Regimes :
Deep, prolonged consolidation (oscillators remain near neutral, CI is chronically low, few signals fire)
Extreme chop with no directional bias (oscillators whipsaw, coherence never establishes)
Gap-driven markets (large overnight gaps create phase discontinuities)
Timeframes :
Sub-5-minute charts: Noise dominates; oscillators flip rapidly; coherence is fleeting and unreliable
Weekly/monthly: Oscillators move extremely slowly; signals are rare; better suited for long-term positioning than active trading
Special Cases :
During major economic releases or earnings: Oscillators may lag price or become decorrelated as fundamentals overwhelm technicals. Reduce position size or stand aside.
In extremely low-volatility environments (e.g., holiday periods): Oscillators compress to neutral, CI may be artificially high due to lack of movement, but signals lack follow-through.
Adaptive Behavior
QRFM is designed to self-adapt to poor conditions:
When coherence is genuinely absent, CI remains low and signals do not fire
When only a subset of oscillators aligns, entangled pairs count stays below threshold and signals are filtered out
When phase-lock cannot be achieved (oscillators too scattered), the lock filter prevents signals
This means the indicator will naturally produce fewer (or zero) signals during unfavorable conditions, rather than generating false signals. This is a feature —it keeps you out of low-probability trades.
Parameter Optimization by Trading Style
Scalping (5-15 Minute Charts)
Goal : Maximum responsiveness, accept higher noise
Oscillator Lengths :
RSI: 7-10
MACD: 8/17/6
Stochastic: 8-10, smooth 2-3
CCI: 14-16
Others: 8-12
Coherence Settings :
CI Smoothing Window: 2-3 bars (fast reaction)
Phase Sample Rate: 1 (every bar)
Ignition Threshold: 0.65-0.75 (lower for more signals)
Collapse Threshold: 0.40-0.50 (earlier exit warnings)
Confirmation :
Phase Lock Tolerance: 40-50° (looser, easier to achieve)
Min Entangled Pairs: 2-3 (fewer oscillators required)
Visuals :
Orbit Plot + Dashboard only (reduce screen clutter for fast decisions)
Disable heavy visuals (heat map, web) for performance
Alerts :
Enable all ignition and collapse alerts
Set to "Once per bar close"
Day Trading (15-Minute to 1-Hour Charts)
Goal : Balance between responsiveness and reliability
Oscillator Lengths :
RSI: 14 (standard)
MACD: 12/26/9 (standard)
Stochastic: 14, smooth 3
CCI: 20
Others: 10-14
Coherence Settings :
CI Smoothing Window: 3-5 bars (balanced)
Phase Sample Rate: 2-3
Ignition Threshold: 0.75-0.85 (moderate selectivity)
Collapse Threshold: 0.50-0.55 (balanced exit timing)
Confirmation :
Phase Lock Tolerance: 30-40° (moderate tightness)
Min Entangled Pairs: 4-5 (reasonable confirmation)
Visuals :
Orbit Plot + Dashboard + Heat Map or Web (choose one)
Field Cloud for regime backdrop
Alerts :
Ignition and collapse alerts
Optional phase-lock alert for advance warning
Swing Trading (4-Hour to Daily Charts)
Goal : High-conviction signals, minimal noise, fewer trades
Oscillator Lengths :
RSI: 14-21
MACD: 12/26/9 or 19/39/9 (longer variant)
Stochastic: 14-21, smooth 3-5
CCI: 20-30
Others: 14-20
Coherence Settings :
CI Smoothing Window: 5-10 bars (very smooth)
Phase Sample Rate: 3-5
Ignition Threshold: 0.80-0.90 (high bar for entry)
Collapse Threshold: 0.55-0.65 (only significant breakdowns)
Confirmation :
Phase Lock Tolerance: 20-30° (tight clustering required)
Min Entangled Pairs: 5-7 (strong confirmation)
Visuals :
All modules enabled (you have time to analyze)
Heat Map for multi-bar pattern recognition
Web for deep confirmation analysis
Alerts :
Ignition and collapse
Review manually before entering (no rush)
Position/Long-Term Trading (Daily to Weekly Charts)
Goal : Rare, very high-conviction regime shifts
Oscillator Lengths :
RSI: 21-30
MACD: 19/39/9 or 26/52/12
Stochastic: 21, smooth 5
CCI: 30-50
Others: 20-30
Coherence Settings :
CI Smoothing Window: 10-14 bars
Phase Sample Rate: 5 (every 5th bar to reduce computation)
Ignition Threshold: 0.85-0.95 (only extreme alignment)
Collapse Threshold: 0.60-0.70 (major regime breaks only)
Confirmation :
Phase Lock Tolerance: 15-25° (very tight)
Min Entangled Pairs: 6+ (broad consensus required)
Visuals :
Dashboard + Orbit Plot for quick checks
Heat Map to study historical coherence patterns
Web to verify deep entanglement
Alerts :
Ignition only (collapses are less critical on long timeframes)
Manual review with fundamental analysis overlay
Performance Optimization (Low-End Systems)
If you experience lag or slow rendering:
Reduce Visual Load :
Orbit Grid Size: 8-10 (instead of 12+)
Heat Map Time Bins: 5-8 (instead of 10+)
Disable Web Matrix entirely if not needed
Disable Field Cloud and Phase Spiral
Reduce Calculation Frequency :
Phase Sample Rate: 5-10 (calculate every 5-10 bars)
Max History Depth: 100-200 (instead of 500+)
Disable Unused Oscillators :
If you only want RSI, MACD, and Stochastic, disable the other five. Fewer oscillators = smaller matrices, faster loops.
Simplify Dashboard :
Choose "Small" dashboard size
Reduce number of metrics displayed
These settings will not significantly degrade signal quality (signals are based on bar-close calculations, which remain accurate), but will improve chart responsiveness.
Important Disclaimers
This indicator is a technical analysis tool designed to identify periods of phase coherence across an ensemble of oscillators. It is not a standalone trading system and does not guarantee profitable trades. The Coherence Index, dominant phase, and entanglement metrics are mathematical calculations applied to historical price data—they measure past oscillator behavior and do not predict future price movements with certainty.
No Predictive Guarantee : High coherence indicates that oscillators are currently aligned, which historically has coincided with trending or directional price movement. However, past alignment does not guarantee future trends. Markets can remain coherent while prices consolidate, or lose coherence suddenly due to news, liquidity changes, or other factors not captured by oscillator mathematics.
Signal Confirmation is Probabilistic : The multi-layer confirmation system (CI threshold + dominant phase + phase-lock + entanglement) is designed to filter out low-probability setups. This increases the proportion of valid signals relative to false signals, but does not eliminate false signals entirely. Users should combine QRFM with additional analysis—support and resistance levels, volume confirmation, multi-timeframe alignment, and fundamental context—before executing trades.
Collapse Signals are Warnings, Not Reversals : A coherence collapse indicates that the oscillator ensemble has lost alignment. This often precedes trend exhaustion or reversals, but can also occur during healthy pullbacks or consolidations. Price may continue in the original direction after a collapse. Use collapses as risk management cues (tighten stops, take partial profits) rather than automatic reversal entries.
Market Regime Dependency : QRFM performs best in markets where oscillators exhibit cyclical, mean-reverting behavior and where trends are punctuated by retracements. In markets dominated by fundamental shocks, gap openings, or extreme low-liquidity conditions, oscillator coherence may be less reliable. During such periods, reduce position size or stand aside.
Risk Management is Essential : All trading involves risk of loss. Use appropriate stop losses, position sizing, and risk-per-trade limits. The indicator does not specify stop loss or take profit levels—these must be determined by the user based on their risk tolerance and account size. Never risk more than you can afford to lose.
Parameter Sensitivity : The indicator's behavior changes with input parameters. Aggressive settings (low thresholds, loose tolerances) produce more signals with lower average quality. Conservative settings (high thresholds, tight tolerances) produce fewer signals with higher average quality. Users should backtest and forward-test parameter sets on their specific instruments and timeframes before committing real capital.
No Repainting by Design : All signal conditions are evaluated on bar close using bar-close values. However, the visual components (orbit plot, heat map, dashboard) update in real-time during bar formation for monitoring purposes. For trade execution, rely on the confirmed signals (triangles and circles) that appear only after the bar closes.
Computational Load : QRFM performs extensive calculations, including nested loops for entanglement matrices and real-time table rendering. On lower-powered devices or when running multiple indicators simultaneously, users may experience lag. Use the performance optimization settings (reduce visual complexity, increase phase sample rate, disable unused oscillators) to improve responsiveness.
This system is most effective when used as one component within a broader trading methodology that includes sound risk management, multi-timeframe analysis, market context awareness, and disciplined execution. It is a tool for regime detection and signal confirmation, not a substitute for comprehensive trade planning.
Technical Notes
Calculation Timing : All signal logic (ignition, collapse) is evaluated using bar-close values. The barstate.isconfirmed or implicit bar-close behavior ensures signals do not repaint. Visual components (tables, plots) render on every tick for real-time feedback but do not affect signal generation.
Phase Wrapping : Phase angles are calculated in the range -180° to +180° using atan2. Angular distance calculations account for wrapping (e.g., the distance between +170° and -170° is 20°, not 340°). This ensures phase-lock detection works correctly across the ±180° boundary.
Array Management : The indicator uses fixed-size arrays for oscillator phases, amplitudes, and the entanglement matrix. The maximum number of oscillators is 8. If fewer oscillators are enabled, array sizes shrink accordingly (only active oscillators are processed).
Matrix Indexing : The entanglement matrix is stored as a flat array with size N×N, where N is the number of active oscillators. Index mapping: index(row, col) = row × N + col. Symmetric pairs (i,j) and (j,i) are stored identically.
Normalization Stability : Oscillators are normalized to using fixed reference levels (e.g., RSI overbought/oversold at 70/30). For unbounded oscillators (MACD, ROC, TSI), statistical normalization (division by rolling standard deviation) is used, with clamping to prevent extreme outliers from distorting phase calculations.
Smoothing and Lag : The CI smoothing window (SMA) introduces lag proportional to the window size. This is intentional—it filters out single-bar noise spikes in coherence. Users requiring faster reaction can reduce the smoothing window to 1-2 bars, at the cost of increased sensitivity to noise.
Complex Number Representation : Pine Script does not have native complex number types. Complex arithmetic is implemented using separate real and imaginary accumulators (sum_cos, sum_sin) and manual calculation of magnitude (sqrt(real² + imag²)) and argument (atan2(imag, real)).
Lookback Limits : The indicator respects Pine Script's maximum lookback constraints. Historical phase and amplitude values are accessed using the operator, with lookback limited to the chart's available bar history (max_bars_back=5000 declared).
Visual Rendering Performance : Tables (orbit plot, heat map, web, dashboard) are conditionally deleted and recreated on each update using table.delete() and table.new(). This prevents memory leaks but incurs redraw overhead. Rendering is restricted to barstate.islast (last bar) to minimize computational load—historical bars do not render visuals.
Alert Condition Triggers : alertcondition() functions evaluate on bar close when their boolean conditions transition from false to true. Alerts do not fire repeatedly while a condition remains true (e.g., CI stays above threshold for 10 bars fires only once on the initial cross).
Color Gradient Functions : The phaseColor() function maps phase angles to RGB hues using sine waves offset by 120° (red, green, blue channels). This creates a continuous spectrum where -180° to +180° spans the full color wheel. The amplitudeColor() function maps amplitude to grayscale intensity. The coherenceColor() function uses cos(phase) to map contribution to CI (positive = green, negative = red).
No External Data Requests : QRFM operates entirely on the chart's symbol and timeframe. It does not use request.security() or access external data sources. All calculations are self-contained, avoiding lookahead bias from higher-timeframe requests.
Deterministic Behavior : Given identical input parameters and price data, QRFM produces identical outputs. There are no random elements, probabilistic sampling, or time-of-day dependencies.
— Dskyz, Engineering precision. Trading coherence.
CCI + MACD Signal MTF (2nd-cross)This custom indicator combines the Commodity Channel Index (CCI) and the MACD to generate trading signals.
Basic signals (dots):
A green dot is plotted when CCI is above +100 and MACD is positive.
A red dot is plotted when CCI is below –100 and MACD is negative.
These dots help visualize momentum alignment between the two indicators.
Second-cross signals (text + alert):
The indicator also tracks cycles of the CCI.
When CCI first moves above +100 and later falls back below +100, this is counted as one completed cycle.
The next time CCI crosses back above +100 (the second cross), if MACD is still positive, a “BUY” label is plotted and a buy alert is triggered.
Conversely, when CCI first moves below –100 and later rises back above –100, that is one completed cycle.
The next time CCI crosses back below –100 (the second cross), if MACD is negative, a “SELL” label is plotted and a sell alert is triggered.
Alerts:
Alerts are only fired on the second-cross events (BUY or SELL), making them rarer but potentially more reliable than the basic dot conditions.
Timeframe flexibility:
Both the CCI and the MACD can be calculated on custom timeframes independently of the chart’s timeframe.
CCI + MACD Signal MTF (2nd-cross)This custom indicator combines the Commodity Channel Index (CCI) and the MACD to generate trading signals.
Basic signals (dots):
A green dot is plotted when CCI is above +100 and MACD is positive.
A red dot is plotted when CCI is below –100 and MACD is negative.
These dots help visualize momentum alignment between the two indicators.
Second-cross signals (text + alert):
The indicator also tracks cycles of the CCI.
When CCI first moves above +100 and later falls back below +100, this is counted as one completed cycle.
The next time CCI crosses back above +100 (the second cross), if MACD is still positive, a “BUY” label is plotted and a buy alert is triggered.
Conversely, when CCI first moves below –100 and later rises back above –100, that is one completed cycle.
The next time CCI crosses back below –100 (the second cross), if MACD is negative, a “SELL” label is plotted and a sell alert is triggered.
Alerts:
Alerts are only fired on the second-cross events (BUY or SELL), making them rarer but potentially more reliable than the basic dot conditions.
Timeframe flexibility:
Both the CCI and the MACD can be calculated on custom timeframes independently of the chart’s timeframe.
QTrade Golden, Bronze & Death, Bubonic Cross AlertsThis indicator highlights key EMA regime shifts with simple, color-coded triangles:
- Golden / Death Cross — 50 EMA crossing above/below the 200 EMA.
- Bronze / Bubonic Cross — 50 EMA crossing above/below the 100 EMA.
- Early-Warning Proxy — tiny triangles for the 4 EMA vs. 200 EMA (4↑200 and 4↓200). These often fire before the 50/100 and 50/200 crosses.
No text clutter on the chart—just triangles. Colors: gold (50↑200), red (50↓200), darker-yellow bronze (50↑100), burgundy (50↓100), turquoise (4↑200), purple (4↓200).
What it tells you (in order of warning → confirmation)
- First warning: 4 EMA crosses the 200 EMA (proxy for price shifting around the 200 line).
- Second warning: 50 EMA crosses the 100 EMA (Bronze/Bubonic).
- Confirmation: 50 EMA crosses the 200 EMA (Golden/Death).
Alerts included
- Golden Cross (50↑200) and Death Cross (50↓200)
- Bronze Cross (50↑100) and Bubonic Cross (50↓100)
- 4 EMA vs. 200 EMA crosses (up & down) — early-warning proxy
- Price–100 EMA events (touch/cross, if enabled in settings)
KRX RS OverlayKRX RS Overlay (Manual, Pine v6) (한국어 설명 아래에)
What it does
Plots a Relative Strength (RS) line of the current symbol versus a selected Korean market index on the price chart (overlay). RS is computed as Close(symbol) / Close(benchmark) and rebased to 100 N bars ago for easy comparison. An SMA of RS is included for signal smoothing.
Benchmarks (manual selection only)
• KOSPI (KRX:KOSPI) — default
• KOSDAQ (KRX:KOSDAQ)
• KOSPI200 (KRX:KOSPI200)
• KOSDAQ150 (KRX:KOSDAQ150)
Inputs
• Benchmark: choose one of the four indices above (default: KOSPI)
• Rebase N bars ago to 100: sets the normalization point (e.g., 252 ≈ 1 trading year on daily)
• RS SMA length: smoothing period for the RS line
• Show 100 base line: toggle the reference line at 100
How to read
• RS rising → the symbol is outperforming the selected index.
• RS above RS-SMA and sloping up → strengthening leadership vs. the benchmark.
• RS crossing above RS-SMA → momentum-style confirmation (an alert is provided).
Tips
• Works on any timeframe; the benchmark is requested on the same timeframe.
• If the RS line scale conflicts with price, place the indicator on the Left scale (Chart Settings → Scales) or set the series to use the left axis.
Notes
• This script is manual only (no auto index detection).
• Educational use; not financial advice.
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KRX RS 오버레이 (수동, Pine v6)
기능
현재 종목을 선택한 한국 지수와 비교한 상대강도(RS) 라인을 가격 차트 위(오버레이)에 표시합니다. RS는 종목 종가 / 지수 종가로 계산하며, 비교를 쉽게 하기 위해 N봉 전 = 100으로 리베이스합니다. 신호 완화를 위해 RS의 SMA도 함께 제공합니다.
벤치마크(수동 선택만 지원)
• KOSPI (KRX:KOSPI) — 기본값
• KOSDAQ (KRX:KOSDAQ)
• KOSPI200 (KRX:KOSPI200)
• KOSDAQ150 (KRX:KOSDAQ150)
입력값
• Benchmark: 위 4개 지수 중 선택(기본: KOSPI)
• Rebase N bars ago to 100: 리베이스 기준(일봉 252 ≈ 1년)
• RS SMA length: RS 스무딩 기간
• Show 100 base line: 100 기준선 표시 여부
해석 가이드
• RS 상승 → 선택 지수 대비 초과성과.
• RS가 RS-SMA 위 & 우상향 → 벤치마크 대비 리더십 강화.
• RS가 RS-SMA 상향 돌파 → 모멘텀 확인(알림 제공).
팁
• 모든 타임프레임에서 동작하며, 지수도 동일 타임프레임으로 요청됩니다.
• 가격 축과 스케일이 겹치면 왼쪽 스케일로 표시하도록 설정하세요(차트 설정 → Scales).
유의사항
• 자동 지수 판별 기능은 포함하지 않았습니다(수동 전용).
Bollinger Bands Entry/Exit ThresholdsBollinger Bands Entry/Exit Thresholds
Author of enhancements: chuckaschultz
Inspired and adapted from the original 'Bollinger Bands Breakout Oscillator' by LuxAlgo
Overview
Pairs nicely with Contrarian 100 MA
The Bollinger Bands Entry/Exit Thresholds is a powerful momentum-based indicator designed to help traders identify potential entry and exit points in trending or breakout markets. By leveraging Bollinger Bands, this indicator quantifies price deviations from the bands to generate bullish and bearish momentum signals, displayed as an oscillator. It includes customizable entry and exit signals based on user-defined thresholds, with visual cues plotted either on the oscillator panel or directly on the price chart.
This indicator is ideal for traders looking to capture breakout opportunities or confirm trend strength, with flexible settings to adapt to various markets and trading styles.
How It Works
The Bollinger Bands Entry/Exit Thresholds calculates two key metrics:
Bullish Momentum (Bull): Measures the extent to which the price exceeds the upper Bollinger Band, expressed as a percentage (0–100).
Bearish Momentum (Bear): Measures the extent to which the price falls below the lower Bollinger Band, also expressed as a percentage (0–100).
The indicator generates:
Long Entry Signals: Triggered when the bearish momentum (bear) crosses below a user-defined Long Threshold (default: 40). This suggests weakening bearish pressure, potentially indicating a reversal or breakout to the upside.
Exit Signals: Triggered when the bullish momentum (bull) crosses below a user-defined Sell Threshold (default: 80), indicating a potential reduction in bullish momentum and a signal to exit long positions.
Signals are visualized as tiny colored dots:
Long Entry: Blue dots, plotted either at the bottom of the oscillator or below the price bar (depending on user settings).
Exit Signal: White dots, plotted either at the top of the oscillator or above the price bar.
Calculation Methodology
Bollinger Bands:
A user-defined Length (default: 14) is used to calculate an Exponential Moving Average (EMA) of the source price (default: close).
Standard deviation is computed over the same length, multiplied by a user-defined Multiplier (default: 1.0).
Upper Band = EMA + (Standard Deviation × Multiplier)
Lower Band = EMA - (Standard Deviation × Multiplier)
Bull and Bear Momentum:
For each bar in the lookback period (length), the indicator calculates:
Bullish Momentum: The sum of positive deviations of the price above the upper band, normalized by the total absolute deviation from the upper band, scaled to a 0–100 range.
Bearish Momentum: The sum of positive deviations of the price below the lower band, normalized by the total absolute deviation from the lower band, scaled to a 0–100 range.
Formula:
bull = (sum of max(price - upper, 0) / sum of abs(price - upper)) * 100
bear = (sum of max(lower - price, 0) / sum of abs(lower - price)) * 100
Signal Generation:
Long Entry: Triggered when bear crosses below the Long Threshold.
Exit: Triggered when bull crosses below the Sell Threshold.
Settings
Length: Lookback period for EMA and standard deviation (default: 14).
Multiplier: Multiplier for standard deviation to adjust Bollinger Band width (default: 1.0).
Source: Input price data (default: close).
Long Threshold: Bearish momentum level below which a long entry signal is generated (default: 40).
Sell Threshold: Bullish momentum level below which an exit signal is generated (default: 80).
Plot Signals on Main Chart: Option to display entry/exit signals on the price chart instead of the oscillator panel (default: false).
Style:
Bullish Color: Color for bullish momentum plot (default: #f23645).
Bearish Color: Color for bearish momentum plot (default: #089981).
Visual Features
Bull and Bear Plots: Displayed as colored lines with gradient fills for visual clarity.
Midline: Horizontal line at 50 for reference.
Threshold Lines: Dashed green line for Long Threshold and dashed red line for Sell Threshold.
Signal Dots:
Long Entry: Tiny blue dots (below price bar or at oscillator bottom).
Exit: Tiny white dots (above price bar or at oscillator top).
How to Use
Add to Chart: Apply the indicator to your TradingView chart.
Adjust Settings: Customize the Length, Multiplier, Long Threshold, and Sell Threshold to suit your trading strategy.
Interpret Signals:
Enter a long position when a blue dot appears, indicating bearish momentum dropping below the Long Threshold.
Exit the long position when a white dot appears, indicating bullish momentum dropping below the Sell Threshold.
Toggle Plot Location: Enable Plot Signals on Main Chart to display signals on the price chart for easier integration with price action analysis.
Combine with Other Tools: Use alongside other indicators (e.g., trendlines, support/resistance) to confirm signals.
Notes
This indicator is inspired by LuxAlgo’s Bollinger Bands Breakout Oscillator but has been enhanced with customizable entry/exit thresholds and signal plotting options.
Best used in conjunction with other technical analysis tools to filter false signals, especially in choppy or range-bound markets.
Adjust the Multiplier to make the Bollinger Bands wider or narrower, affecting the sensitivity of the momentum calculations.
Disclaimer
This indicator is provided for educational and informational purposes only.
CCI Divergence Detector
A technical analysis tool that identifies divergences between price action and the Commodity Channel Index (CCI) oscillator. Unlike standard divergence indicators, this system employs advanced gradient visualization, multi-layer wave effects, and comprehensive customization options to provide traders with crystal-clear divergence signals and market momentum insights.
Core Detection Mechanism
CCI-Based Analysis: The indicator utilizes the Commodity Channel Index as its primary oscillator, calculated from user-configurable source data (default: HLC3) with adjustable length parameters. The CCI provides reliable momentum readings that effectively highlight price-momentum divergences.
Dynamic Pivot Detection: The system employs adaptive pivot detection with three sensitivity levels (High/Normal/Low) to identify significant highs and lows in both price and CCI values. This dynamic approach ensures optimal divergence detection across different market conditions and timeframes.
Dual Divergence Analysis:
Regular Bullish Divergences: Detected when price makes lower lows while CCI makes higher lows, indicating potential upward reversal
Regular Bearish Divergences: Identified when price makes higher highs while CCI makes lower highs, signaling potential downward reversal
Strength Classification System: Each detected divergence is automatically classified into three strength categories (Weak/Moderate/Strong) based on:
-Price differential magnitude
-CCI differential magnitude
-Time duration between pivot points
-User-configurable strength multiplier
Advanced Visual System
Multi-Layer Wave Effects: The indicator features a revolutionary wave visualization system that creates depth through multiple gradient layers around the CCI line. The wave width dynamically adjusts based on ATR volatility, providing intuitive visual feedback about market conditions.
Professional Color Gradient System: Nine independent color inputs control every visual aspect:
Bullish Colors (Light/Medium/Dark): Control oversold areas, wave effects, and strong bullish signals
Bearish Colors (Light/Medium/Dark): Manage overbought zones, wave fills, and strong bearish signals
Neutral Colors (Light/Medium/Dark): Handle table elements, zero line, and transitional states
Intelligent Color Mapping: Colors automatically adapt based on CCI values:
Overbought territory (>100): Bearish color gradients with increasing intensity
Neutral positive (0 to 100): Blend from neutral to bearish tones
Oversold territory (<-100): Bullish color gradients with increasing intensity
Neutral negative (-100 to 0): Transition from neutral to bullish tones
Key Features & Components
Advanced Configuration System: Eight organized input groups provide granular control:
General Settings: System enable, pivot length, confidence thresholds
Oscillator Selection: CCI parameters, overbought/oversold levels, normalization options
Detection Parameters: Divergence types, minimum strength requirements
Sensitivity Tuning: Pivot sensitivity, divergence threshold, confirmation bars
Visual System: Line thickness, labels, backgrounds, table display
Wave Effects: Dynamic width, volatility response, layer count, glow effects
Transparency Controls: Independent transparency for all visual elements
Smoothing & Filtering: CCI smoothing types, noise filtering, wave smoothing
Professional Alert System: Comprehensive alert functionality with dynamic messages including:
-Divergence type and strength classification
-Current CCI value and confidence percentage
-Customizable alert frequency and conditions
Enhanced Information Table: Real-time display showing:
-Current CCI length and value
-Market status (Overbought/Normal/Oversold)
-Active sensitivity setting
Configurable table positioning (4 corner options)
Visual Elements Explained
Primary CCI Line: Main oscillator plot with gradient coloring that reflects market momentum and CCI intensity. Line thickness is user-configurable (1-8 pixels).
Wave Effect Layers: Multi-layer gradient fills creating a dynamic wave around the
CCI line:
-Outer layers provide broad market context
-Inner layers highlight immediate momentum
-Core layers show precise CCI movement
-All layers respond to volatility and momentum changes
Divergence Lines & Labels:
-Solid lines connecting divergence pivot points
-Color-coded based on divergence type and strength
-Labels displaying divergence type and strength classification
-Customizable transparency and size options
Reference Lines:
-Zero line with neutral color coding
-Overbought level (default: 100) with bearish coloring
-Oversold level (default: -100) with bullish coloring
Background Gradient: Optional background coloring that reflects CCI intensity and market conditions with user-controlled transparency (80-99%).
Configuration Options
Sensitivity Controls:
Pivot sensitivity: High/Normal/Low detection levels
Divergence threshold: 0.1-2.0 sensitivity range
Confirmation bars: 1-5 bar confirmation requirement
Strength multiplier: 0.1-3.0 calculation adjustment
Visual Customization:
Line transparency: 0-90% for main elements
Wave transparency: 0-95% for fill effects
Background transparency: 80-99% for subtle background
Label transparency: 0-50% for text elements
Glow transparency: 50-95% for glow effects
Advanced Processing:
Five smoothing types: None/SMA/EMA/RMA/WMA
Noise filtering with adjustable threshold (0.1-10.0)
CCI normalization for enhanced gradient scaling
Dynamic wave width with ATR-based volatility response
Interpretation Guidelines
Divergence Signals:
Strong divergences: High-confidence reversal signals requiring immediate attention
Moderate divergences: Reliable signals suitable for most trading strategies
Weak divergences: Early warning signals best combined with additional confirmation
Wave Intensity: Wave width and color intensity provide real-time volatility and momentum feedback. Wider, more intense waves indicate higher market volatility and stronger momentum.
Color Transitions: Smooth color transitions between bullish, neutral, and bearish states help identify market regime changes and momentum shifts.
CCI Levels: Traditional overbought (>100) and oversold (<-100) levels remain relevant, but the gradient system provides more nuanced momentum reading between these extremes.
Technical Specifications
Compatible Timeframes: All timeframes supported
Maximum Labels: 500 (for divergence marking)
Maximum Lines: 500 (for divergence drawing)
Pine Script Version: v5 (latest optimization)
Overlay Mode: False (separate pane indicator)
Usage Recommendations
This indicator works best when:
-Combined with price action analysis and support/resistance levels
-Used across multiple timeframes for confirmation
-Integrated with proper risk management protocols
-Applied in trending markets for divergence-based reversal signals
-Utilized with other technical indicators for comprehensive analysis
Risk Disclaimer: Trading involves substantial risk of loss. This indicator is provided for analytical purposes only and does not constitute financial advice. Divergence signals, while powerful, are not guaranteed to predict future price movements. Past performance is not indicative of future results. Always use proper risk management and never trade with capital you cannot afford to lose.
ADR% Extension Levels from SMA 50I created this indicator inspired by RealSimpleAriel (a swing trader I recommend following on X) who does not buy stocks extended beyond 4 ADR% from the 50 SMA and uses extensions from the 50 SMA at 7-8-9-10-11-12-13 ADR% to take profits with a 20% position trimming.
RealSimpleAriel's strategy (as I understood it):
-> Focuses on leading stocks from leading groups and industries, i.e., those that have grown the most in the last 1-3-6 months (see on Finviz groups and then select sector-industry).
-> Targets stocks with the best technical setup for a breakout, above the 200 SMA in a bear market and above both the 50 SMA and 200 SMA in a bull market, selecting those with growing Earnings and Sales.
-> Buys stocks on breakout with a stop loss set at the day's low of the breakout and ensures they are not extended beyond 4 ADR% from the 50 SMA.
-> 3-5 day momentum burst: After a breakout, takes profits by selling 1/2 or 1/3 of the position after a 3-5 day upward move.
-> 20% trimming on extension from the 50 SMA: At 7 ADR% (ADR% calculated over 20 days) extension from the 50 SMA, takes profits by selling 20% of the remaining position. Continues to trim 20% of the remaining position based on the stock price extension from the 50 SMA, calculated using the 20-period ADR%, thus trimming 20% at 8-9-10-11 ADR% extension from the 50 SMA. Upon reaching 12-13 ADR% extension from the 50 SMA, considers the stock overextended, closes the remaining position, and evaluates a short.
-> Trailing stop with ascending SMA: Uses a chosen SMA (10, 20, or 50) as the definitive stop loss for the position, depending on the stock's movement speed (preferring larger SMAs for slower-moving stocks or for long-term theses). If the stock's closing price falls below the chosen SMA, the entire position is closed.
In summary:
-->Buy a breakout using the day's low of the breakout as the stop loss (this stop loss is the most critical).
--> Do not buy stocks extended beyond 4 ADR% from the 50 SMA.
--> Sell 1/2 or 1/3 of the position after 3-5 days of upward movement.
--> Trim 20% of the position at each 7-8-9-10-11-12-13 ADR% extension from the 50 SMA.
--> Close the entire position if the breakout fails and the day's low of the breakout is reached.
--> Close the entire position if the price, during the rise, falls below a chosen SMA (10, 20, or 50, depending on your preference).
--> Definitively close the position if it reaches 12-13 ADR% extension from the 50 SMA.
I used Grok from X to create this indicator. I am not a programmer, but based on the ADR% I use, it works.
Below is Grok from X's description of the indicator:
Script Description
The script is a custom indicator for TradingView that displays extension levels based on ADR% relative to the 50-period Simple Moving Average (SMA). Below is a detailed description of its features, structure, and behavior:
1. Purpose of the Indicator
Name: "ADR% Extension Levels from SMA 50".
Objective: Draw horizontal blue lines above and below the 50-period SMA, corresponding to specific ADR% multiples (4, 7, 8, 9, 10, 11, 12, 13). These levels represent potential price extension zones based on the average daily percentage volatility.
Overlay: The indicator is overlaid on the price chart (overlay=true), so the lines and SMA appear directly on the price graph.
2. Configurable Inputs
The indicator allows users to customize parameters through TradingView settings:
SMA Length (smaLength):
Default: 50 periods.
Description: Specifies the number of periods for calculating the Simple Moving Average (SMA). The 50-period SMA serves as the reference point for extension levels.
Constraint: Minimum 1 period.
ADR% Length (adrLength):
Default: 20 periods.
Description: Specifies the number of days to calculate the moving average of the daily high/low ratio, used to determine ADR%.
Constraint: Minimum 1 period.
Scale Factor (scaleFactor):
Default: 1.0.
Description: An optional multiplier to adjust the distance of extension levels from the SMA. Useful if levels are too close or too far due to an overly small or large ADR%.
Constraint: Minimum 0.1, increments of 0.1.
Tooltip: "Adjust if levels are too close or far from SMA".
3. Main Calculations
50-period SMA:
Calculated with ta.sma(close, smaLength) using the closing price (close).
Serves as the central line around which extension levels are drawn.
ADR% (Average Daily Range Percentage):
Formula: 100 * (ta.sma(dhigh / dlow, adrLength) - 1).
Details:
dhigh and dlow are the daily high and low prices, obtained via request.security(syminfo.tickerid, "D", high/low) to ensure data is daily-based, regardless of the chart's timeframe.
The dhigh / dlow ratio represents the daily percentage change.
The simple moving average (ta.sma) of this ratio over 20 days (adrLength) is subtracted by 1 and multiplied by 100 to obtain ADR% as a percentage.
The result is multiplied by scaleFactor for manual adjustments.
Extension Levels:
Defined as ADR% multiples: 4, 7, 8, 9, 10, 11, 12, 13.
Stored in an array (levels) for easy iteration.
For each level, prices above and below the SMA are calculated as:
Above: sma50 * (1 + (level * adrPercent / 100))
Below: sma50 * (1 - (level * adrPercent / 100))
These represent price levels corresponding to a percentage change from the SMA equal to level * ADR%.
4. Visualization
Horizontal Blue Lines:
For each level (4, 7, 8, 9, 10, 11, 12, 13 ADR%), two lines are drawn:
One above the SMA (e.g., +4 ADR%).
One below the SMA (e.g., -4 ADR%).
Color: Blue (color.blue).
Style: Solid (style=line.style_solid).
Management:
Each level has dedicated variables for upper and lower lines (e.g., upperLine1, lowerLine1 for 4 ADR%).
Previous lines are deleted with line.delete before drawing new ones to avoid overlaps.
Lines are updated at each bar with line.new(bar_index , level, bar_index, level), covering the range from the previous bar to the current one.
Labels:
Displayed only on the last bar (barstate.islast) to avoid clutter.
For each level, two labels:
Above: E.g., "4 ADR%", positioned above the upper line (style=label.style_label_down).
Below: E.g., "-4 ADR%", positioned below the lower line (style=label.style_label_up).
Color: Blue background, white text.
50-period SMA:
Drawn as a gray line (color.gray) for visual reference.
Diagnostics:
ADR% Plot: ADR% is plotted in the status line (orange, histogram style) to verify the value.
ADR% Label: A label on the last bar near the SMA shows the exact ADR% value (e.g., "ADR%: 2.34%"), with a gray background and white text.
5. Behavior
Dynamic Updating:
Lines update with each new bar to reflect new SMA 50 and ADR% values.
Since ADR% uses daily data ("D"), it remains constant within the same day but changes day-to-day.
Visibility Across All Bars:
Lines are drawn on every bar, not just the last one, ensuring visibility on historical data as well.
Adaptability:
The scaleFactor allows level adjustments if ADR% is too small (e.g., for low-volatility symbols) or too large (e.g., for cryptocurrencies).
Compatibility:
Works on any timeframe since ADR% is calculated from daily data.
Suitable for symbols with varying volatility (e.g., stocks, forex, cryptocurrencies).
6. Intended Use
Technical Analysis: Extension levels represent significant price zones based on average daily volatility. They can be used to:
Identify potential price targets (e.g., take profit at +7 ADR%).
Assess support/resistance zones (e.g., -4 ADR% as support).
Measure price extension relative to the 50 SMA.
Trading: Useful for strategies based on breakouts or mean reversion, where ADR% levels indicate reversal or continuation points.
Debugging: Labels and ADR% plot help verify that values align with the symbol’s volatility.
7. Limitations
Dependence on Daily Data: ADR% is based on daily dhigh/dlow, so it may not reflect intraday volatility on short timeframes (e.g., 1 minute).
Extreme ADR% Values: For low-volatility symbols (e.g., bonds) or high-volatility symbols (e.g., meme stocks), ADR% may require adjustments via scaleFactor.
Graphical Load: Drawing 16 lines (8 upper, 8 lower) on every bar may slow the chart for very long historical periods, though line management is optimized.
ADR% Formula: The formula 100 * (sma(dhigh/dlow, Length) - 1) may produce different values compared to other ADR% definitions (e.g., (high - low) / close * 100), so users should be aware of the context.
8. Visual Example
On a chart of a stock like TSLA (daily timeframe):
The 50 SMA is a gray line tracking the average trend.
Assuming an ADR% of 3%:
At +4 ADR% (12%), a blue line appears at sma50 * 1.12.
At -4 ADR% (-12%), a blue line appears at sma50 * 0.88.
Other lines appear at ±7, ±8, ±9, ±10, ±11, ±12, ±13 ADR%.
On the last bar, labels show "4 ADR%", "-4 ADR%", etc., and a gray label shows "ADR%: 3.00%".
ADR% is visible in the status line as an orange histogram.
9. Code: Technical Structure
Language: Pine Script @version=5.
Inputs: Three configurable parameters (smaLength, adrLength, scaleFactor).
Calculations:
SMA: ta.sma(close, smaLength).
ADR%: 100 * (ta.sma(dhigh / dlow, adrLength) - 1) * scaleFactor.
Levels: sma50 * (1 ± (level * adrPercent / 100)).
Graphics:
Lines: Created with line.new, deleted with line.delete to avoid overlaps.
Labels: Created with label.new only on the last bar.
Plots: plot(sma50) for the SMA, plot(adrPercent) for debugging.
Optimization: Uses dedicated variables for each line (e.g., upperLine1, lowerLine1) for clear management and to respect TradingView’s graphical object limits.
10. Possible Improvements
Option to show lines only on the last bar: Would reduce visual clutter.
Customizable line styles: Allow users to choose color or style (e.g., dashed).
Alert for anomalous ADR%: A message if ADR% is too small or large.
Dynamic levels: Allow users to specify ADR% multiples via input.
Optimization for short timeframes: Adapt ADR% for intraday timeframes.
Conclusion
The script creates a visual indicator that helps traders identify price extension levels based on daily volatility (ADR%) relative to the 50 SMA. It is robust, configurable, and includes debugging tools (ADR% plot and labels) to verify values. The ADR% formula based on dhigh/dlow
EMA Scoring Strategy## **📊 EMA Scoring Strategy for Trend Analysis**
This strategy is designed to **identify bullish trends** based on multiple **Exponential Moving Averages (EMAs)**. It assigns a **score** based on how the price and EMAs interact, and highlights strong bullish conditions when the score reaches **4 or above**.
---
## **🔹 Strategy Logic**
### 1️⃣ **Calculating EMAs**
- **EMA 21** → Short-term trend
- **EMA 50** → Mid-term trend
- **EMA 100** → Long-term trend
---
### 2️⃣ **Scoring System**
For each trading day, the strategy assigns **+1 or -1 points** based on the following conditions:
| Condition | Score |
|-----------|-------|
| If **Price > EMA 21** | +1 |
| If **Price > EMA 50** | +1 |
| If **Price > EMA 100** | +1 |
| If **EMA 21 > EMA 50** | +1 |
| If **EMA 50 > EMA 100** | +1 |
| If **EMA 21 > EMA 100** | +1 |
| If **Price < EMA 21** | -1 |
| If **Price < EMA 50** | -1 |
| If **Price < EMA 100** | -1 |
| If **EMA 21 < EMA 50** | -1 |
| If **EMA 50 < EMA 100** | -1 |
| If **EMA 21 < EMA 100** | -1 |
---
### 3️⃣ **Bullish Confirmation** (Score ≥ 4)
- The **score is calculated every day**.
- When the **score reaches 4 or above**, it confirms a strong **bullish trend**.
- A **green background** is applied to highlight such days.
- A **histogram** is plotted **only when the score is 4 or higher** to keep the chart clean.
- A **buy signal** is generated when the score **crosses above 4**.
---
## **🔹 Visualization & Alerts**
### ✅ **What You See on the Chart**
1. **EMA Lines (21, 50, 100)** 📈
2. **Green Background for Strong Bullish Days (Score ≥ 4)** ✅
3. **Histogram Showing Score (Only for 4 and above)** 📊
4. **Buy Signal When Score Crosses Above 4** 💰
### 🔔 **Alerts**
- **An alert is triggered** when the score crosses **above 4**, notifying the user about a bullish trend.
---
## **📌 How to Use This Strategy**
1. **Identify Strong Bullish Trends:** When the score is **4 or above**, it suggests that price momentum is strong.
2. **Enter Trades on Buy Signals:** When the score **crosses above 4**, it could be a good time to buy.
3. **Stay in the Trade While Score is 4+:** The green background confirms a **strong uptrend**.
4. **Exit When Score Drops Below 4:** This suggests weakening momentum.
---
## **🔹 Advantages of This Strategy**
✅ **Simple & Objective** - Uses clear rules for trend confirmation
✅ **Filters Out Noise** - Only highlights strong bullish conditions
✅ **Works on Any Market** - Can be applied to stocks, indices, crypto, etc.
✅ **Customizable** - You can tweak EMAs or score conditions as needed
---
## **🚀 Next Steps**
Would you like me to add **stop-loss conditions**, **sell signals**, or any **extra confirmations like RSI or volume**? 😃
Position Size Using Manual Stop Loss [odnac]
This indicator calculates the risk per position based on user-defined settings.
Two Calculation Methods
1. Manual Stop Loss (%) & Manual Leverage
2. Manual Stop Loss (%) & Optimized Leverage
Settings
1. init_capital
Enter your current total capital.
2. Maximum Risk (%) per Position of Total Capital
Specify the percentage of your total funds to be risked for a single position.
3. manual_SL(%)
Enter the stop-loss percentage.
Range: 0.01 ~ 100
4. manual_leverage
Enter the leverage you wish to use.
Range: 1 ~ 100
Used in the first method (Manual Stop Loss (%) & Manual Leverage).
5. Safety Margin
Specify the safety margin for optimized leverage.
Range: 0.01 ~ 1
Used in the second method (Manual Stop Loss (%) & Optimized Leverage). Details are explained below.
Indicator Colors
Black: Indicates which method is being used.
White: Leverage.
First Green: Funds to be invested.
Second Green: Funds to be invested * Leverage.
First Red: Stop-loss (%).
Second Red: Stop-loss (%) * Leverage.
Details for Each Method:
1. Manual Stop Loss (%) & Manual Leverage
This method calculates the size of the funds based on user-defined stop-loss (%) and leverage settings.
White: manual_leverage.
First Green: Investment = Maximum Risk / (manual_SL / 100) / manual_leverage
Second Green: Maximum Risk * (manual_SL / 100)
First Red: manual_SL.
Second Red: manual_SL * manual_leverage
Ensure that the product of manual_SL and manual_leverage does not exceed 100.
If it does, there is a risk of liquidation.
2. Manual Stop Loss (%) & Optimized Leverage
This method calculates optimized leverage based on the user-defined stop-loss (%) and determines the size of the funds.
Optimization_LEVER = auto_leverage * safety_margin
auto_leverage = 100 / stop-loss (%), rounded down to the nearest whole number.
(Exception: If the stop-loss (%) is in the range of 0 ~ 1%, auto_leverage is always 100.)
Example:
If the stop-loss is 4%, auto_leverage = 25 (100 / 4 = 25).
However, 4% × 25 leverage equals 100%, meaning liquidation occurs even with a stop-loss.
To reduce this risk, the safety_margin value is applied.
White: auto_leverage * safety_margin
First Green: Investment = Maximum Risk / (manual_SL / 100) / optimization_LEVER
Second Green: Maximum Risk * (manual_SL / 100)
First Red: manual_SL.
Second Red: manual_SL * optimization_LEVER
Z-Score Weighted Trend System I [InvestorUnknown]The Z-Score Weighted Trend System I is an advanced and experimental trading indicator designed to utilize a combination of slow and fast indicators for a comprehensive analysis of market trends. The system is designed to identify stable trends using slower indicators while capturing rapid market shifts through dynamically weighted fast indicators. The core of this indicator is the dynamic weighting mechanism that utilizes the Z-score of price , allowing the system to respond effectively to significant market movements.
Dynamic Z-Score-Based Weighting System
The Z-Score Weighted Trend System I utilizes the Z-score of price to assign weights dynamically to fast indicators. This mechanism is designed to capture rapid market shifts at potential turning points, providing timely entry and exit signals.
Traders can choose from two primary weighting mechanisms:
Threshold-Based Weighting: The fast indicators are given weight only when the absolute Z-score exceeds a user-defined threshold. Below this threshold, fast indicators have no impact on the final signal.
Continuous Weighting: By setting the threshold to zero, fast indicators always contribute to the final signal, regardless of Z-score levels. However, this increases the likelihood of false signals during ranging or low-volatility markets
// Calculate weight for Fast Indicators based on Z-Score (Slow Indicator weight is kept to 1 for simplicity)
f_zscore_weights(series float z, simple float weight_thre) =>
float fast_weight = na
float slow_weight = na
if weight_thre > 0
if math.abs(z) <= weight_thre
fast_weight := 0
slow_weight := 1
else
fast_weight := 0 + math.sqrt(math.abs(z))
slow_weight := 1
else
fast_weight := 0 + math.sqrt(math.abs(z))
slow_weight := 1
Choice of Z-Score Normalization
Traders have the flexibility to select different Z-score processing methods to better suit their trading preferences:
Raw Z-Score or Moving Average: Traders can opt for either the raw Z-score or a moving average of the Z-score to smooth out fluctuations.
Normalized Z-Score (ranging from -1 to 1) or Z-Score Percentile: The normalized Z-score is simply the raw Z-score divided by 3, while the Z-score percentile utilizes a normal distribution for transformation.
f_zscore_perc(series float zscore_src, simple int zscore_len, simple string zscore_a, simple string zscore_b, simple string ma_type, simple int ma_len) =>
z = (zscore_src - ta.sma(zscore_src, zscore_len)) / ta.stdev(zscore_src, zscore_len)
zscore = switch zscore_a
"Z-Score" => z
"Z-Score MA" => ma_type == "EMA" ? (ta.ema(z, ma_len)) : (ta.sma(z, ma_len))
output = switch zscore_b
"Normalized Z-Score" => (zscore / 3) > 1 ? 1 : (zscore / 3) < -1 ? -1 : (zscore / 3)
"Z-Score Percentile" => (f_percentileFromZScore(zscore) - 0.5) * 2
output
Slow and Fast Indicators
The indicator uses a combination of slow and fast indicators:
Slow Indicators (constant weight) for stable trend identification: DMI (Directional Movement Index), CCI (Commodity Channel Index), Aroon
Fast Indicators (dynamic weight) to identify rapid trend shifts: ZLEMA (Zero-Lag Exponential Moving Average), IIRF (Infinite Impulse Response Filter)
Each indicator is calculated using for-loop methods to provide a smoothed and averaged view of price data over varying lengths, ensuring stability for slow indicators and responsiveness for fast indicators.
Signal Calculation
The final trading signal is determined by a weighted combination of both slow and fast indicators. The slow indicators provide a stable view of the trend, while the fast indicators offer agile responses to rapid market movements. The signal calculation takes into account the dynamic weighting of fast indicators based on the Z-score:
// Calculate Signal (as weighted average)
float sig = math.round(((DMI*slow_w) + (CCI*slow_w) + (Aroon*slow_w) + (ZLEMA*fast_w) + (IIRF*fast_w)) / (3*slow_w + 2*fast_w), 2)
Backtest Mode and Performance Metrics
The indicator features a detailed backtesting mode, allowing traders to compare the effectiveness of their selected settings against a traditional Buy & Hold strategy. The backtesting provides:
Equity calculation based on signals generated by the indicator.
Performance metrics comparing Buy & Hold metrics with the system’s signals, including: Mean, positive, and negative return percentages, Standard deviations, Sharpe, Sortino, and Omega Ratios
// Calculate Performance Metrics
f_PerformanceMetrics(series float base, int Lookback, simple float startDate, bool Annualize = true) =>
// Initialize variables for positive and negative returns
pos_sum = 0.0
neg_sum = 0.0
pos_count = 0
neg_count = 0
returns_sum = 0.0
returns_squared_sum = 0.0
pos_returns_squared_sum = 0.0
neg_returns_squared_sum = 0.0
// Loop through the past 'Lookback' bars to calculate sums and counts
if (time >= startDate)
for i = 0 to Lookback - 1
r = (base - base ) / base
returns_sum += r
returns_squared_sum += r * r
if r > 0
pos_sum += r
pos_count += 1
pos_returns_squared_sum += r * r
if r < 0
neg_sum += r
neg_count += 1
neg_returns_squared_sum += r * r
float export_array = array.new_float(12)
// Calculate means
mean_all = math.round((returns_sum / Lookback), 4)
mean_pos = math.round((pos_count != 0 ? pos_sum / pos_count : na), 4)
mean_neg = math.round((neg_count != 0 ? neg_sum / neg_count : na), 4)
// Calculate standard deviations
stddev_all = math.round((math.sqrt((returns_squared_sum - (returns_sum * returns_sum) / Lookback) / Lookback)) * 100, 2)
stddev_pos = math.round((pos_count != 0 ? math.sqrt((pos_returns_squared_sum - (pos_sum * pos_sum) / pos_count) / pos_count) : na) * 100, 2)
stddev_neg = math.round((neg_count != 0 ? math.sqrt((neg_returns_squared_sum - (neg_sum * neg_sum) / neg_count) / neg_count) : na) * 100, 2)
// Calculate probabilities
prob_pos = math.round((pos_count / Lookback) * 100, 2)
prob_neg = math.round((neg_count / Lookback) * 100, 2)
prob_neu = math.round(((Lookback - pos_count - neg_count) / Lookback) * 100, 2)
// Calculate ratios
sharpe_ratio = math.round((mean_all / stddev_all * (Annualize ? math.sqrt(Lookback) : 1))* 100, 2)
sortino_ratio = math.round((mean_all / stddev_neg * (Annualize ? math.sqrt(Lookback) : 1))* 100, 2)
omega_ratio = math.round(pos_sum / math.abs(neg_sum), 2)
// Set values in the array
array.set(export_array, 0, mean_all), array.set(export_array, 1, mean_pos), array.set(export_array, 2, mean_neg),
array.set(export_array, 3, stddev_all), array.set(export_array, 4, stddev_pos), array.set(export_array, 5, stddev_neg),
array.set(export_array, 6, prob_pos), array.set(export_array, 7, prob_neu), array.set(export_array, 8, prob_neg),
array.set(export_array, 9, sharpe_ratio), array.set(export_array, 10, sortino_ratio), array.set(export_array, 11, omega_ratio)
// Export the array
export_array
//}
Calibration Mode
A Calibration Mode is included for traders to focus on individual indicators, helping them fine-tune their settings without the influence of other components. In Calibration Mode, the user can visualize each indicator separately, making it easier to adjust parameters.
Alerts
The indicator includes alerts for long and short signals when the indicator changes direction, allowing traders to set automated notifications for key market events.
// Alert Conditions
alertcondition(long_alert, "LONG (Z-Score Weighted Trend System)", "Z-Score Weighted Trend System flipped ⬆LONG⬆")
alertcondition(short_alert, "SHORT (Z-Score Weighted Trend System)", "Z-Score Weighted Trend System flipped ⬇Short⬇")
Important Note:
The default settings of this indicator are not optimized for any particular market condition. They are generic starting points for experimentation. Traders are encouraged to use the calibration tools and backtesting features to adjust the system to their specific trading needs.
The results generated from the backtest are purely historical and are not indicative of future results. Market conditions can change, and the performance of this system may differ under different circumstances. Traders and investors should exercise caution and conduct their own research before using this indicator for any trading decisions.
Multiple SMA, EMA, and VWAP CrossoversMultiple SMA, EMA, and VWAP Crossovers with Alerts
Overview : The "Multiple SMA, EMA, and VWAP Crossovers" script is designed for traders who want to monitor various simple moving averages (SMAs), exponential moving averages (EMAs), and the volume-weighted average price (VWAP) to identify potential buy and sell opportunities. This script allows you to visualize key moving averages on your chart and create custom alerts for specific crossover events.
Detail s: This script plots the following moving averages:
Simple Moving Averages (SMA): 5, 10, 20, 50, 100, 200, and 325 periods
Exponential Moving Average (EMA): 9 periods
Volume-Weighted Average Price (VWAP)
It includes options to display these moving averages and set alerts for their crossovers.
Available Crossovers:
20/50 SMA, 20/100 SMA, 20/200 SMA, 20/325 SMA
50/100 SMA, 50/200 SMA, 50/325 SMA
100/200 SMA, 100/325 SMA
200/325 SMA
VWAP/20 SMA, VWAP/50 SMA, VWAP/100 SMA, VWAP/200 SMA, VWAP/325 SMA
Optional Lines to Add to the Chart:
9 EMA, 5 SMA, 10 SMA, 20 SMA, 50 SMA, 100 SMA, 200 SMA, 325 SMA, VWAP
How to Use:
Enable Indicators: Use the input options to select which SMAs, EMA, and VWAP you want to display on your chart.
Set Alerts: Choose the specific crossover events you want to monitor. For example, you can set an alert for the 20/50 SMA crossover or the VWAP/100 SMA crossover.
Monitor the Chart: The script will plot the selected moving averages on your chart. When a selected crossover event occurs, an alert will be triggered, notifying you of the potential trade opportunity.
Usage Tips:
Trending Market: Use the buy and sell alerts in trending markets where the moving averages can help confirm the direction of the trend.
Key Support and Resistance Levels: Combine crossover alerts with key support and resistance levels for more reliable trading signals.
Volume Confirmation: Ensure there is sufficient volume to support the crossover signals, indicating stronger momentum behind the move.
When NOT to Use Buy and Sell Alerts:
Low Volume: Avoid using buy and sell alerts during periods of low trading volume, as the signals may be less reliable.
Market Noise: Be cautious in highly volatile markets where frequent crossovers might generate false signals.
Sideways Market: In a sideways or range-bound market, crossover signals can result in multiple whipsaws, leading to potential losses.
Why Use This Script? This script provides a comprehensive tool for traders to monitor multiple moving averages and VWAP crossovers efficiently. It allows you to customize alerts based on your trading strategy and helps you make informed decisions by visualizing key technical indicators on your chart.
Legal Disclaimer: The information provided by this script is for educational and informational purposes only and should not be considered financial advice. The developer of this script is not responsible for any financial losses incurred from using this script.
Support and resistance levels (Day, Week, Month) + EMAs + SMAs(ENG): This Pine 5 script provides various tools for configuring and displaying different support and resistance levels, as well as moving averages (EMA and SMA) on charts. Using these tools is an essential strategy for determining entry and exit points in trades.
Support and Resistance Levels
Daily, weekly, and monthly support and resistance levels play a key role in analyzing price movements:
Daily levels: Represent prices where a cryptocurrency has tended to bounce within the current trading day.
Weekly levels: Reflect strong prices that hold throughout the week.
Monthly levels: Indicate the most significant levels that can influence price movement over the month.
When trading cryptocurrencies, traders use these levels to make decisions about entering or exiting positions. For example, if a cryptocurrency approaches a weekly resistance level and fails to break through it, this may signal a sell opportunity. If the price reaches a daily support level and starts to bounce up, it may indicate a potential long position.
Market context and trading volumes are also important when analyzing support and resistance levels. High volume near a level can confirm its significance and the likelihood of subsequent price movement. Traders often combine analysis across different time frames to get a more complete picture and improve the accuracy of their trading decisions.
Moving Averages
Moving averages (EMA and SMA) are another important tool in the technical analysis of cryptocurrencies:
EMA (Exponential Moving Average): Gives more weight to recent prices, allowing it to respond more quickly to price changes.
SMA (Simple Moving Average): Equally considers all prices over a given period.
Key types of moving averages used by traders:
EMA 50 and 200: Often used to identify trends. The crossing of the 50-day EMA with the 200-day EMA is called a "golden cross" (buy signal) or a "death cross" (sell signal).
SMA 50, 100, 150, and 200: These periods are often used to determine long-term trends and support/resistance levels. Similar to the EMA, the crossings of these averages can signal potential trend changes.
Settings Groups:
EMA Golden Cross & Death Cross: A setting to display the "golden cross" and "death cross" for the EMA.
EMA 50 & 200: A setting to display the 50-day and 200-day EMA.
Support and Resistance Levels: Includes settings for daily, weekly, and monthly levels.
SMA 50, 100, 150, 200: A setting to display the 50, 100, 150, and 200-day SMA.
SMA Golden Cross & Death Cross: A setting to display the "golden cross" and "death cross" for the SMA.
Components:
Enable/disable the display of support and resistance levels.
Show level labels.
Parameters for adjusting offset, display of EMA and SMA, and their time intervals.
Parameters for configuring EMA and SMA Golden Cross & Death Cross.
EMA Parameters:
Enable/disable the display of 50 and 200-day EMA.
Color and style settings for EMA.
Options to use bar gaps and the "LookAhead" function.
SMA Parameters:
Enable/disable the display of 50, 100, 150, and 200-day SMA.
Color and style settings for SMA.
Options to use bar gaps and the "LookAhead" function.
Effective use of support and resistance levels, as well as moving averages, requires an understanding of technical analysis, discipline, and the ability to adapt the strategy according to changing market conditions.
(RUS) Данный Pine 5 скрипт предоставляет разнообразные инструменты для настройки и отображения различных уровней поддержки и сопротивления, а также скользящих средних (EMA и SMA) на графиках. Использование этих инструментов является важной стратегией для определения точек входа и выхода из сделок.
Уровни поддержки и сопротивления
Дневные, недельные и месячные уровни поддержки и сопротивления играют ключевую роль в анализе движения цен:
Дневные уровни: Представляют собой цены, на которых криптовалюта имела тенденцию отскакивать в течение текущего торгового дня.
Недельные уровни: Отражают сильные цены, которые сохраняются в течение недели.
Месячные уровни: Указывают на наиболее значимые уровни, которые могут влиять на движение цены в течение месяца.
При торговле криптовалютами трейдеры используют эти уровни для принятия решений о входе в позицию или закрытии сделки. Например, если криптовалюта приближается к недельному уровню сопротивления и не удается его преодолеть, это может стать сигналом для продажи. Если цена достигает дневного уровня поддержки и начинает отскакивать вверх, это может указывать на возможность открытия длинной позиции.
Контекст рынка и объемы торговли также важны при анализе уровней поддержки и сопротивления. Высокий объем при приближении к уровню может подтвердить его значимость и вероятность последующего движения цены. Трейдеры часто комбинируют анализ различных временных рамок для получения более полной картины и улучшения точности своих торговых решений.
Скользящие средние
Скользящие средние (EMA и SMA) являются еще одним важным инструментом в техническом анализе криптовалют:
EMA (Exponential Moving Average): Экспоненциальная скользящая средняя, которая придает большее значение последним ценам. Это позволяет более быстро реагировать на изменения в ценах.
SMA (Simple Moving Average): Простая скользящая средняя, которая равномерно учитывает все цены в заданном периоде.
Основные виды скользящих средних, которые используются трейдерами:
EMA 50 и 200: Часто используются для выявления трендов. Пересечение 50-дневной EMA с 200-дневной EMA называется "золотым крестом" (сигнал на покупку) или "крестом смерти" (сигнал на продажу).
SMA 50, 100, 150 и 200: Эти периоды часто используются для определения долгосрочных трендов и уровней поддержки/сопротивления. Аналогично EMA, пересечения этих средних могут сигнализировать о возможных изменениях тренда.
Группы настроек:
EMA Golden Cross & Death Cross: Настройка для отображения "золотого креста" и "креста смерти" для EMA.
EMA 50 & 200: Настройка для отображения 50-дневной и 200-дневной EMA.
Уровни поддержки и сопротивления: Включает настройки для дневных, недельных и месячных уровней.
SMA 50, 100, 150, 200: Настройка для отображения 50, 100, 150 и 200-дневных SMA.
SMA Golden Cross & Death Cross: Настройка для отображения "золотого креста" и "креста смерти" для SMA.
Компоненты:
Включение/отключение отображения уровней поддержки и сопротивления.
Показ ярлыков уровней.
Параметры для настройки смещения, отображения EMA и SMA, а также их временных интервалов.
Параметры для настройки EMA и SMA Golden Cross & Death Cross.
Параметры EMA:
Включение/отключение отображения 50 и 200-дневных EMA.
Настройки цвета и стиля для EMA.
Опции для использования разрыва баров и функции "LookAhead".
Параметры SMA:
Включение/отключение отображения 50, 100, 150 и 200-дневных SMA.
Настройки цвета и стиля для SMA.
Опции для использования разрыва баров и функции "LookAhead".
Эффективное использование уровней поддержки и сопротивления, а также скользящих средних, требует понимания технического анализа, дисциплины и умения адаптировать стратегию в зависимости от изменяющихся условий рынка.
Normalized Relative Strength LineNormalized Relative Strength Line Indicator
Overview
The "Normalized Relative Strength Line" indicator measures the relative performance of a stock compared to a benchmark index (e.g., NSE
). This indicator helps traders and investors identify whether a stock is outperforming or underperforming the selected benchmark over a specified lookback period. The values are normalized to a range of -100 to +100 for easy interpretation.
Key Features
Comparison Symbol: Users can select a benchmark index or any other comparison symbol to measure relative performance.
Lookback Period: A user-defined period for normalization, typically set to a number of trading days (e.g., 252 days for one year).
Relative Strength Calculation: The indicator calculates the percentage change in price for both the stock and the comparison symbol from the start of the lookback period.
Normalization: The relative strength values are normalized to a range of -100 to +100 to facilitate comparison and visualization.
Smoothing: An optional 14-period simple moving average (SMA) is applied to the normalized relative strength line for a smoother representation of trends.
Interpretation
Positive Values (+100 to 0): When the normalized relative strength (RS) line is above 0, it indicates that the stock is outperforming the comparison symbol. Higher values signify stronger outperformance.
Negative Values (0 to -100): When the normalized RS line is below 0, it indicates that the stock is underperforming the comparison symbol. Lower values signify stronger underperformance.
Horizontal Line at 0: The horizontal line at 0 serves as a reference point. Crossing this line from below indicates a shift from underperformance to outperformance, and crossing from above indicates a shift from outperformance to underperformance.
Crossovers: The points where the RS line crosses the moving average (red line) can signal potential changes in relative performance trends.
Example Use Case
If the normalized RS line of a stock consistently remains around +100, it suggests that the stock has been strongly outperforming the comparison symbol over the selected lookback period. Conversely, if it remains around -100, it suggests strong underperformance.
TOTAL:(RSI+TSI)TOTAL:(RSI+TSI)
This indicator collects instant data of RSI and TSI oscillators. RSI moves between (0) and (100) values as a moving line, while TSI moves between (-100) and (+100) values as two moving lines.
The top value of the sum of these values is graphically;
It takes the total value (+300) from RSI (+100), TSI (+100) and (+100).
The lowest value of the sum of these values is graphically;
It takes the value (-200) from the RSI (0), (-100) and (-100) from the TSI.
In case this indicator approaches (+300) graphically; It can be seen that price candlesticks mostly move upwards. This may not always give accurate results. Past incompatibilities can affect this situation.
In case this indicator approaches (-200) graphically; It can be seen that price candlesticks mostly move downwards. This may not always give accurate results. Past incompatibilities can affect this situation.
The graphical movements and numerical values created by this indicator do not give precise results for price candles.
CCI colored RSIKnowing how to write code will hopefully be my saving grace with trading. Regardless, I have things to learn yet and the CCI indicator seems to get a lot of respect from chart-art minimalists.
On Investopedia, it says, “The CCI compares the current price to an average price over a period of time. The indicator fluctuates above or below zero, moving into positive or negative territory. While most values, approximately 75%, fall between -100 and +100, about 25% of the values fall outside this range, indicating a lot of weakness or strength in the price movement”
So I decided to have the regular RSI colored with information from the CCI that I just learned about. RSI color changes depending on whether or not the CCI was extended beyond the –100 and 100 extremities, as this indicates trend strength, and helps to not exit a trade early. Arrows are drawn for when the CCI crosses the 0 point of the CCI, which if overlaid, is the 50 on the RSI.
I have also added the option of having the background shaded according to CCI signals. Crosses OVER the –100 and 100 are the early and late bullish signals, while crosses UNDER the –100 and 100 are early and late bearish. I added to the RSI according to how Investopedia says to trade the CCI here.
www.investopedia.com
I added lines to the RSI to delineate the zones that Constance Brown talks about in her work with the RSI.
I kept the code simple to demonstrate my process, editing out lines instead of deleting, etc. I hope it helps somebody new to programming in Pine Script be able to hop right in.
Happy Turkey Day! Gobble Gobble. Say “Gobble Gobble” out loud. Do it.
Edit: Gratuity options removed. Try not to support terrorism this holiday season. And ffs turn off that race-baiting fact-destroying humanity threatening trash on your tv. We fight terrorism all day up in this mf. Savin stupid hoes and everything. Because it's the right thing to do. Not because Soros said so and paid TradingView enough.
Trend Scores + Volume-Weighted Trend ScoresHere is a simple indicator based on Tushar Chande's TrendScore .
The main purpose of the TrendScore is to determine the strength and direction of a trend, which it does by comparing the current price to the prices within a user-defined window of historical prices.
In the input menu, the user defines the starting and ending period. The current price is then compared to each historical price. If the current price is greater than the given historical price, then the TrendScore is incremented, while it is decremented if it is below the given historical price. TrendScore values fluctuate between a maximum of 100 and a minimum of -100, with 100 meaning that the current price is greater than each historical price in the window and a value of -100 meaning the inverse is true.
We then use the same process to calculate the volume trend score by passing in volume to the 'getTrendScore' function. Lastly, the indicator also also calculates a 'volume-weighted trend score'. This is simply the average of the price trend score and the volume trend score. It is not plotted by default, but users can set the input option to true in the input menu and it will be plotted as a yellow line (as seen in the bottom chart).
The Chart:
The trend scores for price are plotted as a histogram. We've summarized the meaning behind its color changes below:
-If ( trendScore == 100)
then color = dark green
-if ( trendScore < 100 and trendScore is increasing)
then color = light green
-if ( trendScore > 0 and trendScore is DECREASING)
then color = pink
-if ( trendScore < 0)
then color = red
The volume trend score is plotted as a blue line. We felt that using a similar coloring system for the volume trend scores would over-crowd the chart and take away from the simplicity that makes this indicator useful. The volume-weighted trend score is plotted as a yellow line.
The main price bars change color based on the price trend score to make the values easier to visualize as well.
Interpretation:
This is a pretty versatile indicator. We summarized the ways in which traders can use it:
-Enter Long Positions when the trend score crosses zero from negative to positive territory.
-Exit Long Positions when the trend score was previously 100 and begins decreasing (ie bar color changes from dark green to pink).
-Spot bearish divergences when price trend score is 100 or relatively high and the volume trend score decreases significantly.
-Identify bullish divergences when price trend score is relatively low and volume trend score is increasing.
~Happy Trading~
Liquidity Void Zone Detector [PhenLabs]📊 Liquidity Void Zone Detector
Version: PineScript™v6
📌 Description
The Liquidity Void Zone Detector is a sophisticated technical indicator designed to identify and visualize areas where price moved with abnormally low volume or rapid momentum, creating "voids" in market liquidity. These zones represent areas where insufficient trading activity occurred during price movement, often acting as magnets for future price action as the market seeks to fill these gaps.
Built on PineScript v6, this indicator employs a dual-detection methodology that analyzes both volume depletion patterns and price movement intensity relative to ATR. The revolutionary 3D visualization system uses three-layer polyline rendering with adaptive transparency and vertical offsets, creating genuine depth perception where low liquidity zones visually recede and high liquidity zones protrude forward. This makes critical market structure immediately apparent without cluttering your chart.
🚀 Points of Innovation
Dual detection algorithm combining volume threshold analysis and ATR-normalized price movement sensitivity for comprehensive void identification
Three-layer 3D visualization system with progressive transparency gradients (85%, 78%, 70%) and calculated vertical offsets for authentic depth perception
Intelligent state machine logic that tracks consecutive void bars and only renders zones meeting minimum qualification requirements
Dynamic strength scoring system (0-100 scale) that combines inverted volume ratios with movement intensity for accurate void characterization
Adaptive ATR-based spacing calculation that automatically adjusts 3D layering depth to match instrument volatility
Efficient memory management system supporting up to 100 simultaneous void visualizations with automatic array-based cleanup
🔧 Core Components
Volume Analysis Engine: Calculates rolling volume averages and compares current bar volume against dynamic thresholds to detect abnormally thin trading conditions
Price Movement Analyzer: Normalizes bar range against ATR to identify rapid price movements that indicate liquidity exhaustion regardless of instrument or timeframe
Void Tracking State Machine: Maintains persistent tracking of void start bars, price boundaries, consecutive bar counts, and cumulative strength across multiple bars
3D Polyline Renderer: Generates three-layer rectangular polylines with precise timestamp-to-bar index conversion and progressive offset calculations
Strength Calculation System: Combines volume component (inverted ratio capped at 100) with movement component (ATR intensity × 30) for comprehensive void scoring
🔥 Key Features
Automatic Void Detection: Continuously scans price action for low volume conditions or rapid movements, triggering void tracking when thresholds are exceeded
Real-Time Visualization: Creates 3D rectangular zones spanning from void initiation to termination, with color-coded depth indicating liquidity type
Adjustable Sensitivity: Configure volume threshold multiplier (0.1-2.0x), price movement sensitivity (0.5-5.0x), and minimum qualifying bars (1-10) for customized detection
Dual Color Coding: Separate visual treatment for low liquidity voids (receding red) and high liquidity zones (protruding green) based on 50-point strength threshold
Optional Compact Labels: Toggle LV (Low Volume) or HV (High Volume) circular labels at void centers for quick identification without visual clutter
Lookback Period Control: Adjust analysis window from 5 to 100 bars to match your trading timeframe and market volatility characteristics
Memory-Efficient Design: Automatically manages polyline and label arrays, deleting oldest elements when user-defined maximum is reached
Data Window Integration: Plots void detection binary, current strength score, and average volume for detailed analysis in TradingView's data window
🎨 Visualization
Three-Layer Depth System: Each void is rendered as three stacked polylines with progressive transparency (85%, 78%, 70%) and calculated vertical offsets creating authentic 3D appearance
Directional Depth Perception: Low liquidity zones recede with back layer most transparent; high liquidity zones protrude with front layer most transparent for instant visual differentiation
Adaptive Offset Spacing: Vertical separation between layers calculated as ATR(14) × 0.001, ensuring consistent 3D effect across different instruments and volatility regimes
Color Customization: Fully configurable base colors for both low liquidity zones (default: red with 80 transparency) and high liquidity zones (default: green with 80 transparency)
Minimal Chart Clutter: Closed polylines with matching line and fill colors create clean rectangular zones without unnecessary borders or visual noise
Background Highlight: Subtle yellow background (96% transparency) marks bars where void conditions are actively detected in real-time
Compact Labeling: Optional tiny circular labels with 60% transparent backgrounds positioned at void center points for quick reference
📖 Usage Guidelines
Detection Settings
Lookback Period: Default: 10 | Range: 5-100 | Number of bars analyzed for volume averaging and void detection. Lower values increase sensitivity to recent changes; higher values smooth detection across longer timeframes. Adjust based on your trading timeframe: short-term traders use 5-15, swing traders use 20-50, position traders use 50-100.
Volume Threshold: Default: 1.0 | Range: 0.1-2.0 (step 0.1) | Multiplier applied to average volume. Bars with volume below (average × threshold) trigger void conditions. Lower values detect only extreme volume depletion; higher values capture more moderate low-volume situations. Start with 1.0 and decrease to 0.5-0.7 for stricter detection.
Price Movement Sensitivity: Default: 1.5 | Range: 0.5-5.0 (step 0.1) | Multiplier for ATR-normalized price movement detection. Values above this threshold indicate rapid price changes suggesting liquidity voids. Increase to 2.0-3.0 for volatile instruments; decrease to 0.8-1.2 for ranging or low-volatility conditions.
Minimum Void Bars: Default: 10 | Range: 1-10 | Minimum consecutive bars exhibiting void conditions required before visualization is created. Filters out brief anomalies and ensures only sustained voids are displayed. Use 1-3 for scalping, 5-10 for intraday trading, 10+ for swing trading to match your time horizon.
Visual Settings
Low Liquidity Color: Default: Red (80% transparent) | Base color for zones where volume depletion or rapid movement indicates thin liquidity. These zones recede visually (back layer most transparent). Choose colors that contrast with your chart theme for optimal visibility.
High Liquidity Color: Default: Green (80% transparent) | Base color for zones with relatively higher liquidity compared to void threshold. These zones protrude visually (front layer most transparent). Ensure clear differentiation from low liquidity color.
Show Void Labels: Default: True | Toggle display of compact LV/HV labels at void centers. Disable for cleaner charts when trading; enable for analysis and review to quickly identify void types across your chart.
Max Visible Voids: Default: 50 | Range: 10-100 | Maximum number of void visualizations kept on chart. Each void uses 3 polylines, so setting of 50 maintains 150 total polylines. Higher values preserve more history but may impact performance on lower-end systems.
✅ Best Use Cases
Gap Fill Trading: Identify unfilled liquidity voids that price frequently returns to, providing high-probability retest and reversal opportunities when price approaches these zones
Breakout Validation: Distinguish genuine breakouts through established liquidity from false breaks into void zones that lack sustainable volume support
Support/Resistance Confluence: Layer void detection over key horizontal levels to validate structural integrity—levels within high liquidity zones are stronger than those in voids
Trend Continuation: Monitor for new void formation in trend direction as potential continuation zones where price may accelerate due to reduced resistance
Range Trading: Identify void zones within consolidation ranges that price tends to traverse quickly, helping to avoid getting caught in rapid moves through thin areas
Entry Timing: Wait for price to reach void boundaries rather than entering mid-void, as voids tend to be traversed quickly with limited profit-taking opportunities
⚠️ Limitations
Historical Pattern Indicator: Identifies past liquidity voids but cannot predict whether price will return to fill them or when filling might occur
No Volume on Forex: Indicator uses tick volume for forex pairs, which approximates but doesn't represent true trading volume, potentially affecting detection accuracy
Lagging Confirmation: Requires minimum consecutive bars (default 10) before void is visualized, meaning detection occurs after void formation begins
Trending Market Behavior: Strong trends driven by fundamental catalysts may create voids that remain unfilled for extended periods or permanently
Timeframe Dependency: Detection sensitivity varies significantly across timeframes; settings optimized for one timeframe may not perform well on others
No Directional Bias: Indicator identifies liquidity characteristics but provides no predictive signal for price direction after void detection
Performance Considerations: Higher max visible void settings combined with small minimum void bars can generate numerous visualizations impacting chart rendering speed
💡 What Makes This Unique
Industry-First 3D Visualization: Unlike flat volume or liquidity indicators, the three-layer rendering with directional depth perception provides instant visual hierarchy of liquidity quality
Dual-Mode Detection: Combines both volume-based and movement-based detection methodologies, capturing voids that single-approach indicators miss
Intelligent Qualification System: State machine logic prevents premature visualization by requiring sustained void conditions, reducing false signals and chart clutter
ATR-Normalized Analysis: All detection thresholds adapt to instrument volatility, ensuring consistent performance across stocks, forex, crypto, and futures without constant recalibration
Transparency-Based Depth: Uses progressive transparency gradients rather than colors or patterns to create depth, maintaining visual clarity while conveying information hierarchy
Comprehensive Strength Metrics: 0-100 void strength calculation considers both the degree of volume depletion and the magnitude of price movement for nuanced zone characterization
🔬 How It Works
Phase 1: Real-Time Detection
On each bar close, the indicator calculates average volume over the lookback period and compares current bar volume against the volume threshold multiplier
Simultaneously measures current bar's high-low range and normalizes it against ATR, comparing the result to price movement sensitivity parameter
If either volume falls below threshold OR movement exceeds sensitivity threshold, the bar is flagged as exhibiting void characteristics
Phase 2: Void Tracking & Qualification
When void conditions first appear, state machine initializes tracking variables: start bar index, initial top/bottom prices, consecutive bar counter, and cumulative strength accumulator
Each subsequent bar with void conditions extends the tracking, updating price boundaries to envelope all bars and accumulating strength scores
When void conditions cease, system checks if consecutive bar count meets minimum threshold; if yes, proceeds to visualization; if no, discards the tracking and resets
Phase 3: 3D Visualization Construction
Calculates average void strength by dividing cumulative strength by number of bars, then determines if void is low liquidity (>50 strength) or high liquidity (≤50 strength)
Generates three polyline layers spanning from start bar to end bar and from top price to bottom price, each with calculated vertical offset based on ATR
Applies progressive transparency (85%, 78%, 70%) with layer ordering creating recession effect for low liquidity zones and protrusion effect for high liquidity zones
Creates optional center label and pushes all visual elements into arrays for memory management
Phase 4: Memory Management & Display
Continuously monitors polyline array size (each void creates 3 polylines); when total exceeds max visible voids × 3, deletes oldest polylines via array.shift()
Similarly manages label array, removing oldest labels when count exceeds maximum to prevent memory accumulation over extended chart history
Plots diagnostic data to TradingView’s data window (void detection binary, current strength, average volume) for detailed analysis without cluttering main chart
💡 Note:
This indicator is designed to enhance your market structure analysis by revealing liquidity characteristics that aren’t visible through standard price and volume displays. For best results, combine void detection with your existing support/resistance analysis, trend identification, and risk management framework. Liquidity voids are descriptive of past market behavior and should inform positioning decisions rather than serve as standalone entry/exit signals. Experiment with detection parameters across different timeframes to find settings that align with your trading style and instrument characteristics.
Multi-Symbol EMA Crossover Scanner with Multi-Timeframe AnalysisDescription
What This Indicator Does:
This indicator is a comprehensive market scanner that monitors up to 10 symbols simultaneously across 4 different timeframes (15-minute, 1-hour, 4-hour, and daily) to detect exponential moving average (EMA) crossovers in real-time. Instead of manually checking multiple charts and timeframes for EMA crossover signals, this scanner automatically does the work for you and presents all detected signals in a clean, organized table that updates continuously throughout the trading session.
Key Features:
Multi-Symbol Monitoring: Scan up to 10 different symbols at once (stocks, forex, crypto, or any TradingView symbol)
Multi-Timeframe Analysis: Simultaneously tracks 4 timeframes (15m, 1H, 4H, 1D) with toggle options to enable/disable each
Comprehensive EMA Pairs: Detects crossovers between all major EMA combinations: 20×50, 20×100, 20×200, 50×100, 50×200, and 100×200
Real-Time Signal Feed: Displays the most recent signals in a sorted table (newest first) with timestamp, direction, price, and EMA pair information
Session Filter: Built-in time filter (default 10:00-18:00) to focus on specific trading hours and avoid pre-market/after-hours noise
Pagination System: Navigate through signals using a page selector when you have more signals than fit in one view
Signal Statistics: Footer displays total signals, bullish/bearish breakdown, and page navigation hints
Customizable Display: Choose table position (4 corners), signals per page (5-20), and maximum signal history (10-100)
How It Works:
The scanner uses the request.security() function to fetch EMA data from multiple symbols and timeframes simultaneously. For each symbol-timeframe combination, it calculates four exponential moving averages (20, 50, 100, and 200 periods) and monitors for crossovers:
Bullish Crossovers (▲ Green):
Faster EMA crosses above slower EMA
Indicates potential upward momentum
Common entry signals for long positions
Bearish Crossovers (▼ Red):
Faster EMA crosses below slower EMA
Indicates potential downward momentum
Common entry signals for short positions or exits
The scanner prioritizes crossovers involving faster EMAs (20×50) over slower ones (100×200), as faster crossovers typically generate more frequent signals. Each detected crossover is stored with its timestamp, allowing the scanner to sort signals chronologically and remove duplicates within the same timeframe.
Signal Table Columns:
Sym: Symbol name (abbreviated, e.g., "ASELS" instead of "BIST:ASELS")
TF: Timeframe where the crossover occurred (15m, 1h, 4h, 1D)
⏰: Exact time of the crossover (HH:MM format in Istanbul timezone)
↕: Direction indicator (▲ bullish green / ▼ bearish red)
₺: Price level where the crossover occurred (average of the two EMAs)
MA: Which EMA pair crossed (e.g., "20×50", "50×200")
How to Use:
For Day Traders:
Enable 15m and 1h timeframes
Monitor symbols from your watchlist
Use crossovers as entry timing signals in the direction of the larger trend
Adjust the time filter to match your trading session (e.g., market open to 2 hours before close)
For Swing Traders:
Enable 4h and 1D timeframes
Focus on 50×200 and 100×200 crossovers (golden/death crosses)
Look for multiple timeframe confluence (same symbol showing bullish crossovers on both 4h and 1D)
Use as a pre-market scanner to identify potential setups for the day
For Multi-Market Traders:
Mix symbols from different markets (stocks, forex, crypto)
Use the scanner to identify which markets are showing the most momentum
Track relative strength by comparing crossover frequency across symbols
Identify rotation opportunities when one asset shows bullish signals while another shows bearish
Setup Recommendations:
Default BIST (Turkish Stock Market) Setup:
The code comes pre-configured with 10 popular BIST stocks:
ASELS, EKGYO, THYAO, AKBNK, PGSUS, ASTOR, OTKAR, ALARK, ISCTR, BIMAS
For US Stocks:
Replace with symbols like: NASDAQ:AAPL, NASDAQ:TSLA, NASDAQ:NVDA, NYSE:JPM, etc.
For Forex:
Use pairs like: FX:EURUSD, FX:GBPUSD, FX:USDJPY, OANDA:XAUUSD, etc.
For Crypto:
Use exchanges like: BINANCE:BTCUSDT, COINBASE:ETHUSD, BINANCE:SOLUSDT, etc.
Settings Guide:
Symbol List (10 inputs):
Enter any valid TradingView symbol in "EXCHANGE:TICKER" format
Use symbols you actively trade or monitor
Mix different asset classes if desired
Timeframe Toggles:
15 Minutes: High-frequency signals, best for day trading
1 Hour: Balanced frequency, good for intraday swing trades
4 Hours: Lower frequency, quality swing trade signals
1 Day: Low frequency, major trend changes only
Time Filter:
Start Hour (10): Beginning of your trading session
End Hour (18): End of your trading session
Prevents signals during low-liquidity periods
Adjust to match your market's active hours
Display Settings:
Table Position: Choose corner placement (doesn't interfere with other indicators)
Max Signals (40): Total historical signals to keep in memory
Signals Per Page (10): How many rows to show at once
Page Number: Navigate through signal history (auto-adjusts to available pages)
What Makes This Original:
Multi-symbol scanners exist on TradingView, but this indicator's originality comes from:
Comprehensive EMA Pair Coverage: Most scanners focus on 1-2 EMA pairs, this monitors 6 different combinations simultaneously
Unified Multi-Timeframe View: Presents signals from 4 timeframes in a single, chronologically sorted feed rather than separate panels
Session-Aware Filtering: Built-in time filter prevents signal overload from 24-hour markets
Smart Pagination: Handles large signal volumes gracefully with page navigation instead of scrolling
Signal Deduplication: Prevents the same crossover from appearing multiple times if it persists across several bars
Price-at-Cross Recording: Captures the exact price where the crossover occurred, not just that it happened
Real-Time Statistics: Live tracking of bullish vs bearish signal distribution
Trading Strategy Examples:
Trend Confirmation Strategy:
Find a symbol showing bullish crossover on 1D (major trend change)
Wait for pullback
Enter when 1h shows bullish crossover (confirmation)
Exit when 1h shows bearish crossover
Multi-Timeframe Confluence:
Look for symbols appearing multiple times with same direction
Example: ASELS shows ▲ on both 4h and 1D = strong bullish signal
Avoid symbols showing conflicting signals (▲ on 1h but ▼ on 4h)
Rotation Scanner:
Monitor 10+ symbols from the same sector
Identify which are turning bullish (▲) first
Enter leaders, avoid laggards
Rotate out when crossovers turn bearish (▼)
Important Considerations:
Not a Complete System: EMA crossovers should be confirmed with price action, volume, and support/resistance analysis
Whipsaw Risk: During consolidation, EMAs can cross back and forth frequently (especially on 15m timeframe)
Lag: EMAs are lagging indicators; crossovers occur after the move has already begun
False Signals: More common during sideways markets; work best in trending environments
Symbol Limits: TradingView has limits on request.security() calls; this scanner uses 40 calls (10 symbols × 4 timeframes)
Performance: On lower-end devices, scanning 10 symbols across 4 timeframes may cause slight delays in chart updates
Best Practices:
Start with 5 symbols and 2 timeframes, then expand as you get comfortable
Use in conjunction with a main chart for price context
Don't trade every signal—filter for high-quality setups
Backtest your favorite EMA pairs on your symbols to understand their reliability
Adjust the time filter to exclude lunch hours if your market has low midday volume
Check the footer statistics—if you're getting 50+ signals per day, tighten your time filter or reduce symbols
Technical Notes:
Uses lookahead=barmerge.lookahead_off to prevent future data leakage
Signals are stored in arrays and sorted by timestamp (newest first)
Automatic daily reset clears old signals to prevent memory buildup
Table dynamically resizes based on signal count
All times displayed in Europe/Istanbul timezone (configurable in code)
Advanced Psychological Levels with Dynamic Spacing═══════════════════════════════════════
ADVANCED PSYCHOLOGICAL LEVELS WITH DYNAMIC SPACING
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A comprehensive psychological price level indicator that automatically identifies and displays round number levels across multiple timeframes. Features dynamic ATR-based spacing, smart crypto detection, distance tracking, and customizable alert system.
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WHAT THIS INDICATOR DOES
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This indicator automatically draws psychological price levels (round numbers) that often act as support and resistance:
- Dynamic ATR-Based Spacing - Adapts level spacing to market volatility
- Multiple Level Types - Major (250 pip), Standard (100 pip), Mid, and Intraday levels
- Smart Asset Detection - Automatically adjusts for Forex, Crypto, Indices, and CFDs
- Crypto Price Adaptation - Intelligent level spacing based on cryptocurrency price magnitude
- Distance Information Table - Real-time percentage distance to nearest levels
- Combined Level Labels - Clear identification when multiple level types coincide
- Performance Optimized - Configurable visible range and label limits
- Comprehensive Alerts - Notifications when price crosses any level type
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HOW IT WORKS
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PSYCHOLOGICAL LEVELS CONCEPT:
Psychological levels are round numbers where traders tend to place orders, creating natural support and resistance zones. These include:
- Forex: 1.0000, 1.0100, 1.0050 (pips)
- Crypto: $100, $1,000, $10,000 (whole numbers)
- Indices: 10,000, 10,500, 11,000 (points)
Why They Matter:
- Traders naturally gravitate to round numbers
- Stop losses cluster at these levels
- Take profit orders concentrate here
- Institutional algorithmic trading often targets these levels
DYNAMIC ATR-BASED SPACING:
Traditional Method:
- Fixed spacing regardless of volatility
- May be too tight in volatile markets
- May be too wide in quiet markets
Dynamic Method (Recommended):
- Uses ATR (Average True Range) to measure volatility
- Automatically adjusts level spacing
- Tighter levels in low volatility
- Wider levels in high volatility
Calculation:
1. Calculate ATR over specified period (default: 14)
2. Multiply by ATR multiplier (default: 2.0)
3. Round to nearest psychological level
4. Generate levels at dynamic intervals
Benefits:
- Adapts to market conditions
- More relevant levels in all volatility regimes
- Reduces clutter in trending markets
- Provides more detail in ranging markets
LEVEL TYPES:
Major Levels (250 pip/point):
- Highest significance
- Primary support/resistance zones
- Color: Red (default)
- Style: Solid lines
- Spacing: 2.5x standard step
Standard Levels (100 pip/point):
- Secondary importance
- Common psychological barriers
- Color: Blue (default)
- Style: Dashed lines
- Spacing: Standard step
Mid Levels (50% between major):
- Optional intermediate levels
- Halfway between major levels
- Color: Gray (default)
- Style: Dotted lines
- Usage: Additional confluence points
Intraday Levels (sub-100 pip):
- For intraday traders
- Fine-grained precision
- Color: Yellow (default)
- Style: Dotted lines
- Only shown on intraday timeframes
SMART ASSET DETECTION:
Forex Pairs:
- Detects major currency pairs automatically
- Uses pip-based calculations
- Standard: 100 pips (0.0100)
- Major: 250 pips (0.0250)
- Intraday: 20, 50, 80 pip subdivisions
Cryptocurrencies:
- Automatic price magnitude detection
- Adaptive spacing based on price:
* Under $0.10: Levels at $0.01, $0.05
* $0.10-$1: Levels at $0.10, $0.50
* $1-$10: Levels at $1, $5
* $10-$100: Levels at $10, $50
* $100-$1,000: Levels at $100, $500
* $1,000-$10,000: Levels at $1,000, $5,000
* Over $10,000: Levels at $5,000, $10,000
Indices & CFDs:
- Fixed point-based system
- Major: 500 point intervals (with 250 sub-levels)
- Standard: 100 point intervals
- Suitable for stock indices like SPX, NASDAQ
COMBINED LEVEL LABELS:
When multiple level types coincide at the same price:
- Single line drawn (highest priority color)
- Combined label shows all types
- Priority: Major > Standard > Mid > Intraday
Example Label Formats:
- "1.1000 Major" - Major level only
- "1.1000 Std + Major" - Both standard and major
- "50000 Intra + Mid + Std" - Three levels coincide
Benefits:
- Cleaner chart appearance
- Clear identification of confluence
- Reduced visual clutter
- Easy to spot high-importance levels
DISTANCE INFORMATION TABLE:
Real-time tracking of nearest levels:
Table Contents:
- Nearest major level above (price and % distance)
- Nearest standard level above (price and % distance)
- Nearest standard level below (price and % distance)
Display:
- Top right corner (configurable)
- Color-coded by level type
- Real-time percentage calculations
- Helpful for position management
Usage:
- Identify proximity to key levels
- Set realistic profit targets
- Gauge potential move magnitude
- Monitor approaching resistance/support
ALERT SYSTEM:
Comprehensive crossing alerts:
Alert Types:
- Major Level Crosses
- Standard Level Crosses
- Intraday Level Crosses
Alert Modes:
- First Cross Only: Alert once when level is crossed
- All Crosses: Alert every time level is crossed
Alert Information:
- Level type crossed
- Specific price level
- Direction (above/below)
- One alert per bar to prevent spam
Configuration:
- Enable/disable by level type
- Choose alert frequency
- Customize for your trading style
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HOW TO USE
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INITIAL SETUP:
General Settings:
1. Enable "Use Dynamic ATR-Based Spacing" (recommended)
2. Set ATR Period (14 is standard)
3. Adjust ATR Multiplier (2.0 is balanced)
Visibility Settings:
1. Set Visible Range % (10% recommended for clarity)
2. Adjust Label Offset for readability
3. Configure performance limits if needed
Level Selection:
1. Enable/disable level types based on trading style
2. Adjust line counts for each type
3. Choose line styles and colors for visibility
TRADING STRATEGIES:
Breakout Trading:
1. Wait for price to approach major or standard level
2. Monitor for consolidation near level
3. Enter on confirmed break above/beyond level
4. Stop loss just beyond the broken level
5. Target: Next major or standard level
Rejection Trading:
1. Identify major psychological level
2. Wait for price to test the level
3. Look for rejection signals (wicks, bearish/bullish candles)
4. Enter in direction of rejection
5. Stop beyond the level
6. Target: Previous level or mid-level
Range Trading:
1. Identify range between two major levels
2. Buy at lower psychological level
3. Sell at upper psychological level
4. Use standard and mid-levels for position management
5. Exit if major level breaks with volume
Confluence Trading:
1. Look for combined levels (Std + Major)
2. These represent high-probability zones
3. Use as primary support/resistance
4. Increase position size at confluence
5. Expect stronger reactions at these levels
Session-Based Trading:
1. Note opening level at session start (Asian/London/NY)
2. Trade breakouts of major levels during high-volume sessions
3. London/NY sessions: More likely to break levels
4. Asian session: More likely to respect levels (range trading)
RISK MANAGEMENT WITH PSYCHOLOGICAL LEVELS:
Stop Loss Placement:
- Place stops just beyond psychological levels
- Add buffer (5-10 pips for forex)
- Avoid exact round numbers (stop hunting risk)
- Use previous major level as maximum stop
Take Profit Strategy:
- First target: Next standard level (partial profit)
- Second target: Next major level (remaining position)
- Trail stops to breakeven at first target
- Use distance table to calculate risk/reward
Position Sizing:
- Larger positions at major levels (higher probability)
- Smaller positions at intraday levels (lower probability)
- Scale in at standard levels between major levels
- Reduce size when multiple levels are close together
TIMEFRAME CONSIDERATIONS:
Higher Timeframes (4H, Daily, Weekly):
- Focus on Major and Standard levels only
- Disable Intraday and Mid levels
- Wider level spacing expected
- Use for swing trading and position trading
Lower Timeframes (5m, 15m, 1H):
- Enable all level types
- Use Intraday levels for precision
- Tighter level spacing acceptable
- Good for day trading and scalping
Multi-Timeframe Approach:
- Identify major levels on Daily/4H charts
- Refine entries using 15m/1H intraday levels
- Trade in direction of higher timeframe bias
- Use lower timeframe levels for position management
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CONFIGURATION GUIDE
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GENERAL SETTINGS:
Dynamic ATR-Based Spacing:
- Enabled: Recommended for most markets
- Disabled: Fixed psychological levels
- ATR Period: 14 (standard), 10 (responsive), 20 (smooth)
- ATR Multiplier: 1.0-5.0 (2.0 is balanced)
VISIBILITY SETTINGS:
Visible Range %:
- 5%: Very tight range, minimal clutter
- 10%: Balanced view (recommended)
- 20%: Wide range, more context
- 50%: Maximum range, all levels visible
Label Offset:
- 10-20 bars: Close to current price
- 30-50 bars: Moderate distance
- 50-100 bars: Far from price action
Performance Limits:
- Max Historical Bars: Reduce if indicator loads slowly
- Max Labels: Reduce for cleaner chart (20-30 recommended)
LEVEL CUSTOMIZATION:
Line Count:
- Lower (1-3): Cleaner chart, fewer levels
- Medium (4-6): Balanced view
- Higher (7-10): More context, busier chart
Line Styles:
- Solid: High importance, easy to see
- Dashed: Medium importance, clear but subtle
- Dotted: Low importance, minimal visual weight
Colors:
- Use contrasting colors for different level types
- Red/Blue/Yellow default works well
- Adjust based on chart background and personal preference
DISTANCE TABLE:
Position:
- Top Right: Doesn't interfere with price action
- Top Left: Good for right-side price scale
- Bottom positions: Less common but available
Colors:
- Default (white text, dark background) works for most charts
- Match your chart theme for consistency
- Ensure text is readable against background
ALERT CONFIGURATION:
Alert by Level Type:
- Major: Most important, fewer false signals
- Standard: Balance of frequency and importance
- Intraday: Many signals, best for active traders
Alert Frequency:
- First Cross Only: Cleaner, less noise (recommended for swing trading)
- All Crosses: Every touch, good for scalping
Alert Setup in TradingView:
1. Configure desired alert types in indicator settings
2. Right-click chart → Add Alert
3. Select this indicator
4. Choose "Any alert() function call"
5. Set delivery method (mobile, email, webhook)
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ASSET-SPECIFIC TIPS
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FOREX (EUR/USD, GBP/USD, etc.):
- Major levels at x.x000, x.x500
- Standard levels at x.xx00
- Intraday levels at 20/50/80 pips
- Most effective during London/NY sessions
- Watch for "figure" levels (1.0000, 1.1000)
CRYPTOCURRENCIES (BTC, ETH, etc.):
- Enable dynamic spacing for volatile markets
- Levels adjust automatically based on price
- Watch major $1,000 increments for BTC
- $100 levels important for ETH
- Smaller caps: Use standard levels
- High volatility: Increase ATR multiplier to 3.0
STOCK INDICES (SPX, NASDAQ, etc.):
- 100-point levels most important
- 500-point levels for major S/R
- 50-point mid-levels for refinement
- Watch end-of-day for level reactions
- Futures often lead spot on level breaks
GOLD/COMMODITIES:
- Major levels at $50 increments ($1,900, $1,950)
- Standard levels at $10 increments
- Very reactive to psychological levels
- Watch for false breaks during low volume
- Best reactions during active trading hours
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BEST PRACTICES
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Chart Setup:
- Use clean price action charts
- Avoid too many indicators
- Ensure psychological levels are clearly visible
- Match colors to your chart theme
Level Selection:
- Start with Major and Standard levels only
- Add Mid and Intraday as needed
- Less is more - avoid chart clutter
- Adjust based on timeframe
Combining with Other Tools:
- Volume profile for confluence
- Trendlines intersecting psychological levels
- Moving averages near round numbers
- Fibonacci levels coinciding with psychological levels
Common Mistakes to Avoid:
- Trading every level touch (be selective)
- Ignoring volume confirmation
- Setting stops exactly at levels (stop hunting)
- Forgetting to adjust for different assets
- Over-relying on levels without price action confirmation
Performance Optimization:
- Reduce visible range for faster loading
- Lower max historical bars on lower timeframes
- Limit labels to 30-50 for clarity
- Disable unused level types
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EDUCATIONAL DISCLAIMER
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This indicator identifies psychological price levels based on round numbers that tend to act as support and resistance. The methodology includes:
- Round number detection algorithms
- ATR-based dynamic spacing calculations
- Asset-specific level determination
- Distance percentage calculations
Psychological levels are a recognized concept in technical analysis, studied by traders and institutions. However, they do not guarantee price reactions and should be used as part of a comprehensive trading strategy including proper risk management, volume analysis, and price action confirmation.
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USAGE DISCLAIMER
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This tool is for educational and analytical purposes. Psychological levels can act as support or resistance but price reactions are not guaranteed. Dynamic spacing may generate different levels in different market conditions. Always conduct independent analysis, use proper risk management, and never risk capital you cannot afford to lose. Past performance does not indicate future results.
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CREDITS & ATTRIBUTION
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Original Concept: Sonar Lab
