CBC Flip StrategyThe CBC Flip Strategy is a momentum-based trading system that identifies shifts in market control by monitoring price closes relative to previous bars' highs and lows: it flips to bullish mode when the close exceeds the prior high (indicating bulls in control) and enters a long position, or to bearish mode when the close falls below the prior low (indicating bears in control) and enters a short position, all while incorporating optional confluences like higher timeframe CBC alignment, RSI thresholds (above 50 + offset for longs, below 50 - offset for shorts), and EMA positioning (above for longs, below for shorts) to filter entries; trades are restricted to a user-defined session window and direction preferences, with exits handled via tick-based TP/SL, reversal on chart or higher timeframe CBC flips, and an optional flatten at a specified time to close all positions.
Number of Contracts: Adjust the quantity of contracts per trade (default: 1).
SL and TP Ticks: Set stop-loss (default: 12 ticks) and take-profit (default: 24 ticks) distances from entry.
Exit Strategy: Choose from TP/SL in ticks, exit on chart CBC flip (reverses on opposite signal), or exit on higher timeframe CBC flip.
Flatten All: Enable/disable flattening all positions at a customizable time (default: 16:00, with adjustable hour/minute).
Trading Session: Define the time window for allowing entries (default: 0800-1700).
Trade Direction: Select "Both" (longs and shorts), "Only Long", "Only Short", or "Towards Daily Open" (longs if below daily open, shorts if above).
Higher Timeframe CBC Confluence: Toggle use of HTF CBC alignment (default: enabled, with customizable HTF like "240").
RSI Confluence: Toggle RSI filter (default: enabled, with adjustable length=14, offset=20 for thresholds).
EMA Confluence: Toggle EMA filter (default: enabled, with adjustable length=200 for position relative to price).
在腳本中搜尋"bear"
Hyper SAR Reactor Trend StrategyHyperSAR Reactor Adaptive PSAR Strategy
Summary
Adaptive Parabolic SAR strategy for liquid stocks, ETFs, futures, and crypto across intraday to daily timeframes. It acts only when an adaptive trail flips and confirmation gates agree. Originality comes from a logistic boost of the SAR acceleration using drift versus ATR, plus ATR hysteresis, inertia on the trail, and a bear-only gate for shorts. Add to a clean chart and run on bar close for conservative alerts.
Scope and intent
• Markets: large cap equities and ETFs, index futures, major FX, liquid crypto
• Timeframes: one minute to daily
• Default demo: BTC on 60 minute
• Purpose: faster yet calmer PSAR that resists chop and improves short discipline
• Limits: this is a strategy that places simulated orders on standard candles
Originality and usefulness
• Novel fusion: PSAR AF is boosted by a logistic function of normalized drift, trail is monotone with inertia, entries use ATR buffers and optional cooldown, shorts are allowed only in a bear bias
• Addresses false flips in low volatility and weak downtrends
• All controls are exposed in Inputs for testability
• Yardstick: ATR normalizes drift so settings port across symbols
• Open source. No links. No solicitation
Method overview
Components
• Adaptive AF: base step plus boost factor times logistic strength
• Trail inertia: one sided blend that keeps the SAR monotone
• Flip hysteresis: price must clear SAR by a buffer times ATR
• Volatility gate: ATR over its mean must exceed a ratio
• Bear bias for shorts: price below EMA of length 91 with negative slope window 54
• Cooldown bars optional after any entry
• Visual SAR smoothing is cosmetic and does not drive orders
Fusion rule
Entry requires the internal flip plus all enabled gates. No weighted scores.
Signal rule
• Long when trend flips up and close is above SAR plus buffer times ATR and gates pass
• Short when trend flips down and close is below SAR minus buffer times ATR and gates pass
• Exit uses SAR as stop and optional ATR take profit per side
Inputs with guidance
Reactor Engine
• Start AF 0.02. Lower slows new trends. Higher reacts quicker
• Max AF 1. Typical 0.2 to 1. Caps acceleration
• Base step 0.04. Typical 0.01 to 0.08. Raises speed in trends
• Strength window 18. Typical 10 to 40. Drift estimation window
• ATR length 16. Typical 10 to 30. Volatility unit
• Strength gain 4.5. Typical 2 to 6. Steepness of logistic
• Strength center 0.45. Typical 0.3 to 0.8. Midpoint of logistic
• Boost factor 0.03. Typical 0.01 to 0.08. Adds to step when strength rises
• AF smoothing 0.50. Typical 0.2 to 0.7. Adds inertia to AF growth
• Trail smoothing 0.35. Typical 0.15 to 0.45. Adds inertia to the trail
• Allow Long, Allow Short toggles
Trade Filters
• Flip confirm buffer ATR 0.50. Typical 0.2 to 0.8. Raise to cut flips
• Cooldown bars after entry 0. Typical 0 to 8. Blocks re entry for N bars
• Vol gate length 30 and Vol gate ratio 1. Raise ratio to trade only in active regimes
• Gate shorts by bear regime ON. Bear bias window 54 and Bias MA length 91 tune strictness
Risk
• TP long ATR 1.0. Set to zero to disable
• TP short ATR 0.0. Set to 0.8 to 1.2 for quicker shorts
Usage recipes
Intraday trend focus
Confirm buffer 0.35 to 0.5. Cooldown 2 to 4. Vol gate ratio 1.1. Shorts gated by bear regime.
Intraday mean reversion focus
Confirm buffer 0.6 to 0.8. Cooldown 4 to 6. Lower boost factor. Leave shorts gated.
Swing continuation
Strength window 24 to 34. ATR length 20 to 30. Confirm buffer 0.4 to 0.6. Use daily or four hour charts.
Properties visible in this publication
Initial capital 10000. Base currency USD. Order size Percent of equity 3. Pyramiding 0. Commission 0.05 percent. Slippage 5 ticks. Process orders on close OFF. Bar magnifier OFF. Recalculate after order filled OFF. Calc on every tick OFF. No security calls.
Realism and responsible publication
No performance claims. Past results never guarantee future outcomes. Shapes can move while a bar forms and settle on close. Strategies execute only on standard candles.
Honest limitations and failure modes
High impact events and thin books can void assumptions. Gap heavy symbols may prefer longer ATR. Very quiet regimes can reduce contrast and invite false flips.
Open source reuse and credits
Public domain building blocks used: PSAR concept and ATR. Implementation and fusion are original. No borrowed code from other authors.
Strategy notice
Orders are simulated on standard candles. No lookahead.
Entries and exits
Long: flip up plus ATR buffer and all gates true
Short: flip down plus ATR buffer and gates true with bear bias when enabled
Exit: SAR stop per side, optional ATR take profit, optional cooldown after entry
Tie handling: stop first if both stop and target could fill in one bar
Master Trend Strategy - by jake_thebossMaster Trend Strategy
This strategy combines multiple technical indicators to identify high-probability trend entries across all asset classes.
Core Signal Logic:
Entry triggered when EMA 4 crosses above/below EMA 5
Confirmation required from RSI (>50 for long, <50 for short)
Price must be above/below key moving averages: EMA 21, SMA 50, EMA 55, EMA 89, and EMA 750
Additional confirmation from Stochastic (>52 bullish, <48 bearish) or EMA 89 breakout or VWAP cross
Key Features:
VWAP filter: Only takes bullish signals above VWAP and bearish signals below VWAP
Optional pyramiding: Allows multiple entries in the same direction (up to 200 orders)
Individual stop loss and take profit management for each pyramid level
Time filter: Customizable trading hours with timezone offset
Risk management: Adjustable stop loss (default 0.3%) and take profit (default 0.6%)
Visualization:
Entry, stop loss, and take profit levels drawn as horizontal lines
Customizable signal markers (triangles) for bull/bear entries
Optional EMA overlay display
The strategy is designed for trend-following on lower timeframes, with strict multi-indicator confirmation to filter out false signals.
AlgoWay GRSIM🧭 What this strategy tries to do
This strategy detects when a market move is losing strength and prepares for a potential reversal, but it waits for fresh momentum confirmation before acting.
It combines:
• RSI-based divergence (to spot exhaustion and potential turning points),
• Impulse MACD (to verify that the new direction actually has force behind it).
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⚙️ When it takes trades
Long (Buy):
• A bullish RSI divergence appears (a clue that selling pressure is fading);
• Within a short time window, the Impulse MACD turns strongly positive;
• Optionally, the impulse line itself must be rising (if the Impulse Direction Filter is
enabled).
Short (Sell):
• A bearish RSI divergence appears (buying pressure fading);
• Within a short time window, the Impulse MACD turns strongly negative;
• Optionally, the impulse line must be falling (if the Impulse Direction Filter is enabled).
If momentum confirmation happens too late, the divergence “expires” and the signal is ignored.
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🧩 How entries work
1. Reversal clue:
The strategy detects disagreement between price and RSI (price makes a new high/low, RSI doesn’t).
That suggests a shift in underlying strength.
2. Momentum confirmation:
Before entering, the Impulse MACD must agree — showing real push in the same direction.
3. Impulse direction filter (optional):
When enabled, the impulse itself must accelerate (rise for longs, fall for shorts), avoiding fake signals where price diverges but momentum is still fading.
4. No stacking:
It opens only one position at a time.
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🚪 How exits work
Two main exit styles:
Conservative (default):
Longs close when impulse crosses below its signal line.
Shorts close when impulse crosses above its signal line.
✅ Keeps trades as long as momentum agrees.
Color-change (fast):
Longs close immediately when impulse flips bearish.
Shorts close immediately when impulse flips bullish.
⚡ Faster and more defensive.
Plus:
Stop Loss (%) and Take Profit (%) act as fixed-distance protective exits (set to 0 to disable either one).
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📊 What you’ll see on the chart
A thick Impulse MACD line and thin signal line (oscillator view).
Diamonds — detected bullish/bearish divergence points.
Circles — where impulse crosses its signal (momentum change).
A performance panel (top-right) showing Net Profit, Trades, Win Rate, Profit Factor, Pessimistic PF, and Max Drawdown.
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🔧 What you can tune
Signal Lifetime (bars): how long a divergence remains valid.
Impulse Direction Filter: ensure the impulse itself is moving in the trade’s direction.
Stop Loss / Take Profit (%): risk and target in percent.
Exit Style: conservative cross or faster color-change.
RSI / MA / Signal Lengths: adjust responsiveness (defaults are balanced).
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💪 Strengths
Confirms reversals using momentum direction, not just divergence.
Avoids “early” signals where momentum is still fading.
Works symmetrically for longs and shorts.
Built-in stop/target protection.
Clear, visual confirmation of all logic components.
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⚠️ Things to keep in mind
In sideways markets, the impulse can flip often — prefer conservative exits.
Too small SL/TP → constant stop-outs.
Too wide SL/TP → deep drawdowns.
Always test with different timeframes and markets.
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💡 Practical tips
Start with default settings.
Enable “Use Impulse Direction Filter” in trending markets, disable it in very choppy ones.
Focus on Profit Factor, Win Rate, and Max Drawdown after several dozen trades.
Keep SL/TP roughly aligned with typical swing size.
“AlgoWay GRSIM” is a reversal-with-confirmation strategy: it spots likely turns, demands real momentum alignment (optionally verified by impulse direction), and manages exits with clear momentum cues plus built-in protective limits.
Turtle Strategy - Triple EMA Trend with ADX and ATRDescription
The Triple EMA Trend strategy is a directional momentum system built on the alignment of three exponential moving averages and a strong ADX confirmation filter. It is designed to capture established trends while maintaining disciplined risk management through ATR-based stops and targets.
Core Logic
The system activates only under high-trend conditions, defined by the Average Directional Index (ADX) exceeding a configurable threshold (default: 43).
A bullish setup occurs when the short-term EMA is above the mid-term EMA, which in turn is above the long-term EMA, and price trades above the fastest EMA.
A bearish setup is the mirror condition.
Execution Rules
Entry:
• Long when ADX confirms trend strength and EMA alignment is bullish.
• Short when ADX confirms trend strength and EMA alignment is bearish.
Exit:
• Stop Loss: 1.8 × ATR below (for longs) or above (for shorts) the entry price.
• Take Profit: 3.3 × ATR in the direction of the trade.
Both parameters are configurable.
Additional Features
• Start/end date inputs for controlled backtesting.
• Selective activation of long or short trades.
• Built-in commission and position sizing (percent of equity).
• Full visual representation of EMAs, ADX, stop-loss, and target levels.
This strategy emphasizes clean trend participation, strict entry qualification, and consistent reward-to-risk structure. Ideal for swing or medium-term testing across trending assets.
Larry Williams Oops StrategyThis strategy is a modern take on Larry Williams’ classic Oops setup. It trades intraday while referencing daily bars to detect opening gaps and align entries with the prior day’s direction. Risk is managed with day-based stops, and—unlike the original—all positions are closed at the end of the session (or at the last bar’s close), not at a fixed profit target or the first profitable open.
Entry Rules
Long setup (bullish reversion): Today opens below yesterday’s low (down gap) and yesterday’s candle was bearish. Place a buy stop at yesterday’s low + Filter (ticks).
Short setup (bearish reversion): Today opens above yesterday’s high (up gap) and yesterday’s candle was bullish. Place a sell stop at yesterday’s high − Filter (ticks).
Longs are only taken on down-gap days; shorts only on up-gap days.
Protective Stop
If long, stop loss trails the current day’s low.
If short, stop loss trails the current day’s high.
Exit Logic
Positions are force-closed at the end of the session (in the last bar), ensuring no overnight exposure. There is no take-profit; only stop loss or end-of-day flat.
Notes
This strategy is designed for intraday charts (minutes/seconds) using daily data for gaps and prior-day direction.
Longs/shorts can be enabled or disabled independently.
Batman Strategy v1
1. Overview & Core Concept
The "Batman Strategy V1" is a comprehensive trend-following and pyramid-trading framework designed for multiple asset classes. Its core concept is to identify strong, established trends and systematically enter positions in stages (pyramiding) to maximize gains during sustained market movements.
This strategy is built on a proprietary scoring system that synthesizes multiple market dimensions—including stage analysis, relative strength, and volume dynamics—into clear, actionable signals. It is not a simple indicator mashup; it's a complete system with defined entry, exit, and risk management protocols.
2. Key Features
Proprietary Trend Scoring: The strategy grades market conditions from 'A' (strong bull trend) to 'Z' (strong bear trend) using a unique combination of ADX and RSI calculations, providing a nuanced view of trend maturity and strength.
Advanced Relative Strength Analysis: Automatically compares the asset's performance against a relevant market index (e.g., NIFTY for Indian stocks, NDX for US stocks, or a total crypto market cap for crypto) to ensure it is a market leader.
Heikin-Ashi Based Logic: Utilizes Heikin-Ashi candles for its core calculations to filter out market noise and provide smoother trend signals.
Multi-Tranche Pyramiding: The strategy is designed to enter a position with an initial tranche and add up to four subsequent positions if the trend continues favorably, based on a proprietary breakout logic (`ha_close > breakout`).
Dynamic & Multi-Option Exits: Offers three distinct, user-selectable trailing stop mechanisms for exits: SuperTrend, V-Stop, and Chandelier Exit. This allows traders to tailor the exit logic to their risk tolerance and the asset's volatility. The data source for these exits can also be switched between the standard chart and Heikin-Ashi candles.
Integrated Risk Management: Implements a sophisticated stop-loss system that adjusts based on the number of open trades, aiming to move to break-even after the third tranche and protecting capital.
3. How to Use This Strategy
Configuration: In the script settings, first set your desired backtesting date range. Then, configure the "Entry," "Tranching," and "Exit" parameters to suit your trading style. The most important choice is the "Exit Indicator," as this will define how the strategy closes trades.
Interpretation: When applied to a chart, the strategy will plot trend score labels ('A', 'B', 'C' for bullish; 'X', 'Y', 'Z' for bearish), color the background based on relative strength, and color the bars based on volume strength. Backtesting results, including all pyramided trades, will be visible in the "Strategy Tester" panel.
Alerts: The script includes built-in alert conditions for both bullish and bearish trend scores, which can be used to notify you of potential opportunities.
4. Backtesting & Performance
This is a strategy script, and its performance should be thoroughly evaluated in the Strategy Tester. As per TradingView rules, users should use realistic settings for initial capital, commission, and slippage. The default settings are a template; they should be adjusted to reflect the conditions of the market you are testing. Past performance is not indicative of future results.
5. Disclaimer
This strategy is a tool for market analysis and idea validation. It is not financial advice. All trading involves risk, and you should not risk more than you are prepared to lose. This is a closed-source, protected script; its internal calculations are proprietary.
Order Block Volumatic FVG StrategyInspired by: Volumatic Fair Value Gaps —
License: CC BY-NC-SA 4.0 (Creative Commons Attribution–NonCommercial–ShareAlike).
This script is a non-commercial derivative work that credits the original author and keeps the same license.
What this strategy does
This turns BigBeluga’s visual FVG concept into an entry/exit strategy. It scans bullish and bearish FVG boxes, measures how deep price has mitigated into a box (as a percentage), and opens a long/short when your mitigation threshold and filters are satisfied. Risk is managed with a fixed Stop Loss % and a Trailing Stop that activates only after a user-defined profit trigger.
Additions vs. the original indicator
✅ Strategy entries based on % mitigation into FVGs (long/short).
✅ Lower-TF volume split using upticks/downticks; fallback if LTF data is missing (distributes prior bar volume by close’s position in its H–L range) to avoid NaN/0.
✅ Per-FVG total volume filter (min/max) so you can skip weak boxes.
✅ Age filter (min bars since the FVG was created) to avoid fresh/immature boxes.
✅ Bull% / Bear% share filter (the 46%/53% numbers you see inside each FVG).
✅ Optional candle confirmation and cooldown between trades.
✅ Risk management: fixed SL % + Trailing Stop with a profit trigger (doesn’t trail until your trigger is reached).
✅ Pine v6 safety: no unsupported args, no indexof/clamp/when, reverse-index deletes, guards against zero/NaN.
How a trade is decided (logic overview)
Detect FVGs (same rules as the original visual logic).
For each FVG currently intersected by the bar, compute:
Mitigation % (how deep price has entered the box).
Bull%/Bear% split (internal volume share).
Total volume (printed on the box) from LTF aggregation or fallback.
Age (bars) since the box was created.
Apply your filters:
Mitigation ≥ Long/Short threshold.
Volume between your min and max (if enabled).
Age ≥ min bars (if enabled).
Bull% / Bear% within your limits (if enabled).
(Optional) the current candle must be in trade direction (confirm).
If multiple FVGs qualify on the same bar, the strategy uses the most recent one.
Enter long/short (no pyramiding).
Exit with:
Fixed Stop Loss %, and
Trailing Stop that only starts after price reaches your profit trigger %.
Input settings (quick guide)
Mitigation source: close or high/low. Use high/low for intrabar touches; close is stricter.
Mitigation % thresholds: minimal mitigation for Long and Short.
TOTAL Volume filter: skip FVGs with too little/too much total volume (per box).
Bull/Bear share filter: require, e.g., Long only if Bull% ≥ 50; avoid Short when Bull% is high (Short Bull% max).
Age filter (bars): e.g., ≥ 20–30 bars to avoid fresh boxes.
Confirm candle: require candle direction to match the trade.
Cooldown (bars): minimum bars between entries.
Risk:
Stop Loss % (fixed from entry price).
Activate trailing at +% profit (the trigger).
Trailing distance % (the trailing gap once active).
Lower-TF aggregation:
Auto: TF/Divisor → picks 1/3/5m automatically.
Fixed: choose 1/3/5/15m explicitly.
If LTF can’t be fetched, fallback allocates prior bar’s volume by its close position in the bar’s H–L.
Suggested starting presets (you should optimize per market)
Mitigation: 60–80% for both Long/Short.
Bull/Bear share:
Long: Bull% ≥ 50–70, Bear% ≤ 100.
Short: Bull% ≤ 60 (avoid shorting into strong support), Bear% ≥ 0–70 as you prefer.
Age: ≥ 20–30 bars.
Volume: pick a min that filters noise for your symbol/timeframe.
Risk: SL 4–6%, trailing trigger 1–2%, distance 1–2% (crypto example).
Set slippage/fees in Strategy Properties.
Notes, limitations & best practices
Data differences: The LTF split uses request.security_lower_tf. If the exchange/data feed has sparse LTF data, the fallback kicks in (it’s deliberate to avoid NaNs but is a heuristic).
Real-time vs backtest: The current bar can update until close; results on historical bars use closed data. Use “Bar Replay” to understand intrabar effects.
No pyramiding: Only one position at a time. Modify pyramiding in the header if you need scaling.
Assets: For spot/crypto, TradingView “volume” is exchange volume; in some markets it may be tick volume—interpret filters accordingly.
Risk disclosure: Past performance ≠ future results. Use appropriate position sizing and risk controls; this is not financial advice.
Credits
Visual FVG concept and original implementation: BigBeluga.
This derivative strategy adds entry/exit logic, volume/age/share filters, robust LTF handling, and risk management while preserving the original spirit.
License remains CC BY-NC-SA 4.0 (non-commercial, attribution required, share-alike).
Grand Master's Candlestick Dominance (ATR Enhanced)### Grand Master's Candlestick Dominance (ATR Enhanced)
**Overview**
Unleash the ancient wisdom of Japanese candlestick charting with a modern twist! This comprehensive Pine Script v5 strategy and indicator scans for over 75 classic and advanced candlestick patterns (bullish, bearish, and neutral), assigning dynamic strength scores (1-10) to each for precise signal filtering. Enhanced with Average True Range (ATR) for volatility-aware body size validation, it dominates the markets by combining timeless pattern recognition with robust confirmation layers. Whether used as a backtestable strategy or visual indicator, it empowers traders to spot high-probability reversals, continuations, and indecision setups with surgical accuracy.
Inspired by Steve Nison's *Japanese Candlestick Charting Techniques*, this tool elevates pattern analysis beyond basics—think Hammers, Engulfing patterns, Morning Stars, and rare gems like Abandoned Baby or Concealing Baby Swallow—all consolidated into intelligent arrays for real-time averaging and prioritization.
**Key Features**
- **Extensive Pattern Library**:
- **Bullish (25+ patterns)**: Hammer (8.0), Bullish Engulfing (10.0), Morning Star (7.0), Three White Soldiers (9.0), Dragonfly Doji (8.0), and more (e.g., Rising Three, Unique Three River Bottom).
- **Bearish (25+ patterns)**: Hanging Man (8.0), Bearish Engulfing (10.0), Evening Star (7.0), Three Black Crows (9.0), Gravestone Doji (8.0), and exotics like Upside Gap Two Crows or Stalled Pattern.
- **Neutral/Indecision (34+ patterns)**: Doji variants (Long-Legged, Four Price), Spinning Tops, Harami Crosses, and multi-bar setups like Upside Tasuki Gap or Advancing Block.
Each pattern includes duration tracking (1-5 bars) and ATR-adjusted body/shadow criteria for relevance in volatile conditions.
- **Smart Confirmation Filters** (All Toggleable):
- **Trend Alignment**: 20-period SMA (customizable) ensures entries align with the prevailing trend; optional higher timeframe (e.g., Daily) MA crossover for multi-timeframe confluence.
- **Support/Resistance (S/R)**: Pivot-based levels with 0.01% tolerance to confirm bounces or breaks.
- **Volume Surge**: 20-period volume MA with 1.5x spike multiplier to validate momentum.
- **ATR Body Sizing**: Filters small bodies (<0.3x ATR) and long bodies (>0.8x ATR) for context-aware pattern reliability.
- **Follow-Through**: Ensures post-pattern confirmation via bullish/bearish closes or closes beyond prior bars.
Minimum average strength (default 7.0) and individual pattern thresholds (5.0) prevent weak signals.
- **Entry & Exit Logic**:
- **Long Entry**: Bullish average strength ≥7.0 (outweighing bearish), uptrend, volume spike, near support, follow-through, and HTF alignment.
- **Short Entry**: Mirror for bearish dominance in downtrends near resistance.
- **Exits**: Bearish/neutral shift, or fixed TP (5%) / SL (2%)—pyramiding disabled, 10% equity sizing.
- Backtest range: Jan 1, 2020 – Dec 31, 2025 (editable). Initial capital: $10,000.
- **Interactive Dashboard** (Top-Right Panel):
Real-time insights including:
- Market phase (e.g., "Bullish Phase (Avg Str: 8.2)"), active pattern (e.g., "BULLISH: Bullish Engulfing (Str: 10.0, Bars: 2)"), and trend status.
- Strength breakdowns (Bull/Bear/Neutral counts & averages).
- Filter status (e.g., "Volume: ✔ Spike", "ATR: Enabled (L:0.8, S:0.3)").
- Backtest stats: Total trades, win rate, streak, and last entry/exit details (price & timestamp).
Toggle mode: Strategy (live trades) or Indicator (signals only).
- **Advanced Alerts** (15+ Toggleable Types):
Set up via TradingView's "Any alert() function call" for bar-close triggers:
- Entry/Exit signals with strength & pattern details.
- Strong patterns (≥2 bullish/bearish), neutral indecision, volume spikes.
- S/R breakouts, HTF reversals, high-confidence singles (≥8.0 strength).
- Conflicting signals, MA crossovers, ATR volatility bursts, multi-bar completions.
Example: "STRONG BULLISH PATTERN detected! Strength: 9.5 | Top Pattern: Three White Soldiers | Trend: Up".
**Customization & Usage Tips**
- **Inputs Groups**: Strategy toggles, confirmations, exits, backtest dates, and 15+ alert switches—all intuitively grouped.
- **Optimization**: Tune min strengths for aggressive (lower) or conservative (higher) trading; enable/disable filters to suit your style (e.g., disable S/R for scalping).
- **Best For**: Forex, stocks, crypto on 1H–Daily charts. Test on historical data to refine TP/SL.
- **Limitations**: No external data installs; relies on built-in TA functions. Patterns are probabilistic—combine with your risk management.
Master the candles like a grandmaster. Deploy on TradingView, backtest relentlessly, and let dominance begin! Questions? Drop a comment.
*Version: 1.0 | Updated: September 2025 | Credits: Built on Pine Script v5 with nods to Nison's timeless techniques.*
AI Volume-KNN SuperTrend - by Trading Pine Lab🇬🇧 English
The AI Volume-KNN SuperTrend is an advanced trading strategy that combines the robustness of the SuperTrend indicator with a machine-learning inspired KNN (K-Nearest Neighbors) model. The baseline is built from a volume-weighted moving average with ATR-based bands, while the KNN classifier validates trend direction in real time. This dual-layer approach reduces false signals and improves trend confirmation.
Entries are triggered when the SuperTrend flips direction and the KNN classifier confirms the move as bullish or bearish. Exits are managed with a dynamic trailing stop, automatically adjusting to SuperTrend ± ATR × factor. The strategy includes visual markers for AI start/continuation signals, as well as customizable coloring for bullish, bearish, and neutral phases.
All parameters are fully configurable:
-Trading direction filter: Long / Short / Both.
-KNN settings: number of neighbors (K), dataset size (N).
-Label smoothing: price and SuperTrend smoothing lengths (WMAs).
-SuperTrend settings: length, ATR factor, and moving average source.
-Visualization: trend markers and per-trend coloring.
FVG Ultra Assertive - Individual Filters (mtbr)FVG Ultra Assertive - Individual Filters (mtbr)
What this script offers:
This strategy detects and highlights FVGs (Fair Value Gaps) on the chart, providing traders with a visual and systematic approach to identify potential price inefficiencies. The script plots bullish and bearish FVG zones using customizable boxes and labels, allowing users to easily spot high-probability trading areas. In addition, it opens and closes simulated trades based on the detected FVGs, enabling full backtesting and strategy performance evaluation. It integrates multiple independent filters to validate the strength of each FVG signal before entering a trade.
How it works:
The script identifies:
Bullish FVGs when the current low is higher than the high of two bars ago.
Bearish FVGs when the current high is lower than the low of two bars ago.
Once an FVG is detected, it applies three optional independent filters:
GAP/ATR Filter:
Measures the FVG size relative to the Average True Range (ATR). Only gaps exceeding a user-defined multiple of ATR are considered valid.
Support/Resistance (S/R) Filter:
Uses pivot points to check if the FVG overlaps with recent high/low pivot levels within a tolerance percentage. This ensures the gap aligns with meaningful market levels.
Stochastic Filter:
Applies a stochastic oscillator to confirm momentum. Bullish FVGs are validated when stochastic values are oversold, and bearish FVGs when overbought.
After passing the selected filters, the strategy opens trades:
LONG FVG for bullish signals (buy)
SHORT FVG for bearish signals (sell)
The strategy automatically closes positions when an opposite signal appears, generating a backtest report with trades, profits, and statistics. The final bullish or bearish FVG signals are plotted as colored boxes on the chart with labels “BULL FVG” or “BEAR FVG” for immediate visual reference.
How to configure it for use:
Use GAP/ATR Filter: Enable or disable the ATR-based filter and adjust the ATR period (ATR Length) and minimum gap multiplier (Minimum Gap x ATR).
Use S/R Filter: Enable or disable the pivot-based S/R filter. Configure the pivot lookback periods (Pivot Left and Pivot Right) and the tolerance percentage (Gap Tolerance %).
Use Stochastic Filter: Enable or disable stochastic confirmation. Adjust the K and D lengths (Stoch K Length and Stoch D Length) and the overbought/oversold thresholds (Stoch Overbought and Stoch Oversold).
Colors: Customize the colors for bullish and bearish FVGs (FVG Bull and FVG Bear) to match your chart preferences.
Usage Tips:
Apply this strategy to any timeframe; shorter timeframes generate more frequent FVGs, while higher timeframes highlight stronger gaps.
Combine FVG signals with other technical analysis tools for better trade confirmation.
Use the box and label visualization to quickly scan charts for trade opportunities without cluttering the chart.
The strategy’s trades (LONG and SHORT) provide backtesting results and performance statistics for each signal.
RSI Bands With RSI - ATR Trend StrategyRSI Bands With RSI-ATR Trend Line Strategy
Overview
A trend-following strategy that combines RSI regime detection with a smoothed baseline and ATR bands. Works similar to Supertrend: the line flips bullish or bearish only when price closes beyond the band, aiming to filter noise and catch clean moves.
How It Works
RSI above 50 = bullish bias, below 50 = bearish bias
A dynamic baseline is calculated from RSI and price range, then smoothed
ATR bands expand/contract with volatility
Close above the upper band → bullish flip → long entry
Close below the lower band → bearish flip → short entry
Between bands → prior trend continues
Features
Automatic Buy/Sell entries on confirmed flips
Configurable RSI, Smoothing, ATR, and Multiplier inputs
Visual trend line (green = bull, red = bear)
Backtest ready with initial capital and commission settings
Best Use Cases
Trending markets across Forex, Crypto, Indices, Commodities
Works on multiple timeframes (higher TFs = cleaner flips)
Flexible settings for conservative swing trading or aggressive scalping
⚠️ For testing/education only. Always manage risk and confirm with higher-timeframe or structure filters.
Imbalance No SL📊 Strategy Name: Imbalance No SL
This strategy specially trades on price jumps (true imbalances) in the market, takes advantage of momentum only, and as soon as the opposite signal and profit is received, the trade is closed immediately.
Imbalance No SL strategy specially generates buy and sell signals based on "Imbalance" logic, without any fixed Stop Loss.
🔍 Core Logic
Imbalance Detection
Bullish Imbalance : When the low of the current candle is above the high of the previous candle.
(i.e. a jump type gap occurred in the market – demand is high, price went straight up)
Bearish Imbalance : When the high of the current candle is below the low of the previous candle.
(i.e. the market suddenly fell down)
Creating Visual Box and Label on Signal:
As soon as bullish imbalance is found, green box & IMB BULL label is displayed on the chart.
Bearish has red box & IMB BEAR label.
Trade Entry Logic
BUY on Bullish Imbalance: If there is already a buy or neutral position, then a new “BUY” signal will fire.
SELL on Bearish Imbalance: If already in sell or neutral position, then new “SELL” signal will fire.
You can set quantity/lot size from ‘qty’ input field.
Trade Average Calculation
Buy/Sell maintains average price and their count (so that if averaging is done then correct P&L is calculated).
Trade Exit Logic (Profit Booking/Signal Reverse)
If your buy is going on and bearish imbalance is formed + price is above your average, then buy will be closed (profit condition).
If sell is going on and bullish imbalance is formed + price is below average, then sell will be closed.
Chart Cleaning/Management
Only keep the label and box of the latest signal on the chart, old boxes/labels are automatically deleted.
Alert
You can get alert on bullish or bearish signal (by using alert feature of TradingView).
✅ Simple Explanation for User
This strategy buys or sells directly at the gap (imbalance).
Whenever there is a clear signal of momentum in the market (breakout of the gap), then the trade entry takes place.
When there is an imbalance in the opposite direction and profit is made, the system closes the trade (closes).
There is no fixed stop-loss, risk management is handled by trade averaging/close.
You will know at every point on the visually chart that at which bar the buy, sell and exit took place.
⚠️ What to remember?
If the market is in trend then this script gives very good signals.
In choppy/sideways market, some loss trades can also come because there is no SL.
Big profit or big loss – both depend on the imbalance signal and market speed.
Scalping Line Strategy📌 Scalping Line Strategy – A Precision Crossover System
🔎 Overview
The Scalping Line Strategy is a short-term trading system built around the concept of momentum-driven crossovers between a smoothed moving average filter and a fast signal line. It is designed for scalpers and intraday traders who seek clear entry signals, minimal lag, and adaptive filtering to fit volatile market conditions.
At its core, the strategy uses a custom signal line ("Scalping Line"), which is derived from the difference between a double-smoothed moving average and a shorter-period signal line. Trade entries are triggered when this Scalping Line crosses above or below zero, providing a clean and rules-based framework for both long and short setups.
⚙️ Core Logic
Main Trend Filter – A double-smoothed moving average is calculated over a configurable period (default 100). This reduces noise and provides a more robust backbone for scalping signals.
Percent-Based Filter – To avoid false signals, a customizable percentage filter adjusts how closely the system “respects” price deviations from the moving average. This helps filter out insignificant fluctuations.
Signal Line – A shorter-period simple moving average (default 7) provides faster responsiveness to recent price action.
Scalping Line (SLI) – Calculated as the difference between the fast signal line and the smoothed moving average. When the SLI crosses zero, it signals a potential momentum shift.
SLI > 0 → Momentum bias is bullish.
SLI < 0 → Momentum bias is bearish.
🎯 Trade Direction & Flexibility
Trade Direction Control:
Choose between Long Only, Short Only, or Both to tailor the system to your trading style.
Signal Flip Option:
By default, long entries occur when the SLI crosses below zero, and shorts when it crosses above zero. This orientation can be flipped, allowing for alternative interpretations of the signals depending on how you want to capture momentum in your market.
🕒 Time Window Filtering
For intraday traders, a time filter can be enabled to restrict signals to specific trading sessions (e.g., 9 AM – 4 PM EST). This is particularly useful when trading assets such as equities or futures that have strong intraday volatility windows.
📈 Visuals & Clarity
Scalping Line Plot: Displayed as a dynamic oscillator around a zero baseline.
Histogram Fill: Green when above zero (bullish bias), red when below zero (bearish bias).
Signal Markers: Clear arrows mark long and short entries at crossover points.
Zero Line Reference: A flat gray line at zero assists in visually gauging momentum shifts.
🚀 Strategy Execution
Long Entry: Triggered when SLI crosses below zero (or above zero if flip is enabled) within allowed session hours.
Short Entry: Triggered when SLI crosses above zero (or below zero if flip is enabled) within allowed session hours.
Built-in Signal Cancels: Pending entries are canceled if conditions are no longer valid, ensuring no stale trades remain active.
✅ Best Use Cases
Markets: Works across equities, forex, crypto, and futures with sufficient intraday volatility.
Timeframes: Most effective on 1m to 15m charts for scalping setups, but adaptable to higher frames for swing trading.
Style: Traders who appreciate simple, rules-based momentum crossovers will find this system easy to follow and highly adaptable.
⚠️ Risk Management Note
This strategy is strictly an entry signal framework. Position sizing, stop-loss, and take-profit rules must be overlaid based on your risk management style. Always validate results with backtesting and forward testing before applying to live trading accounts.
📜 Final Thoughts
The Scalping Line Strategy offers a refined, easy-to-interpret approach to intraday trading. By combining smoothed moving averages, adaptive filtering, and flexible signal options, it helps traders identify short-term momentum shifts with clarity and confidence, making it a highly configurable tool for scalping-focused strategies.
Engulfing & Pin Bar Breakout StrategyOverview
This strategy automates a classic, powerful trading methodology based on identifying key candlestick reversal patterns and trading the subsequent price breakout. It is designed to be a complete, "set-and-go" system with built-in risk and position size management.
The core logic operates on the 1-Hour timeframe, scanning for four distinct high-probability reversal signals: two bullish and two bearish. An entry is only triggered when the market confirms the signal by breaking a key price level, aiming to capture momentum following a potential shift in market sentiment.
The Strategy Logic
The system is composed of two distinct modules: Bullish (Long) and Bearish (Short).
🐂 Bullish (Long) Setup
The script initiates a long trade based on the following strict criteria:
Signal: Identifies either a Hammer or a Bullish Engulfing pattern. These patterns often indicate that sellers are losing control and buyers are stepping in.
Confirmation: Waits for the very next candle after the signal.
Entry Trigger: A long position is automatically opened as soon as the price breaks above the high of the signal candle.
Stop Loss: Immediately set just below the low of the signal candle.
Take Profit: A fixed target is placed at a 1:5 Risk/Reward Ratio.
🐻 Bearish (Short) Setup
The script initiates a short trade based on the following strict criteria:
Signal: Identifies either a Shooting Star or a Bearish Engulfing pattern. These patterns suggest buying pressure is fading and sellers are taking over.
Confirmation: Waits for the very next candle after the signal.
Entry Trigger: A short position is automatically opened as soon as the price breaks below the low of the signal candle.
Stop Loss: Immediately set just above the high of the signal candle.
Take Profit: A fixed target is placed at a 1:4 Risk/Reward Ratio.
Key Feature: Automated Risk Management
This strategy is designed for disciplined trading. You do not need to calculate position sizes manually.
Fixed Risk: The script automatically calculates the correct position size to risk exactly 2% of your total account equity on every single trade.
Dynamic Sizing: The position size will adjust based on the distance between your entry price and your stop loss for each specific setup, ensuring a consistent risk profile.
How To Use
Apply the script to your chosen chart (e.g., BTC/USD).
Crucially, set your chart's timeframe to 1-Hour (H1). The strategy is specifically calibrated for this interval.
Navigate to the "Strategy Tester" tab below your chart to view backtest results, including net profit, win rate, and individual trades.
Disclaimer: This script is provided for educational and informational purposes only. It is not financial advice. All trading involves substantial risk, and past performance is not indicative of future results. Please use this tool responsibly and at your own risk.
Mutanabby_AI | Algo Pro Strategy# Mutanabby_AI | Algo Pro Strategy: Advanced Candlestick Pattern Trading System
## Strategy Overview
The Mutanabby_AI Algo Pro Strategy represents a systematic approach to automated trading based on advanced candlestick pattern recognition and multi-layered technical filtering. This strategy transforms traditional engulfing pattern analysis into a comprehensive trading system with sophisticated risk management and flexible position sizing capabilities.
The strategy operates on a long-only basis, entering positions when bullish engulfing patterns meet specific technical criteria and exiting when bearish engulfing patterns indicate potential trend reversals. The system incorporates multiple confirmation layers to enhance signal reliability while providing comprehensive customization options for different trading approaches and risk management preferences.
## Core Algorithm Architecture
The strategy foundation relies on bullish and bearish engulfing candlestick pattern recognition enhanced through technical analysis filtering mechanisms. Entry signals require simultaneous satisfaction of four distinct criteria: confirmed bullish engulfing pattern formation, candle stability analysis indicating decisive price action, RSI momentum confirmation below specified thresholds, and price decline verification over adjustable lookback periods.
The candle stability index measures the ratio between candlestick body size and total range including wicks, ensuring only well-formed patterns with clear directional conviction generate trading signals. This filtering mechanism eliminates indecisive market conditions where pattern reliability diminishes significantly.
RSI integration provides momentum confirmation by requiring oversold conditions before entry signal generation, ensuring alignment between pattern formation and underlying momentum characteristics. The RSI threshold remains fully adjustable to accommodate different market conditions and volatility environments.
Price decline verification examines whether current prices have decreased over a specified period, confirming that bullish engulfing patterns occur after meaningful downward movement rather than during sideways consolidation phases. This requirement enhances the probability of successful reversal pattern completion.
## Advanced Position Management System
The strategy incorporates dual position sizing methodologies to accommodate different account sizes and risk management approaches. Percentage-based position sizing calculates trade quantities as equity percentages, enabling consistent risk exposure across varying account balances and market conditions. This approach proves particularly valuable for systematic trading approaches and portfolio management applications.
Fixed quantity sizing provides precise control over trade sizes independent of account equity fluctuations, offering predictable position management for specific trading strategies or when implementing precise risk allocation models. The system enables seamless switching between sizing methods through simple configuration adjustments.
Position quantity calculations integrate seamlessly with TradingView's strategy testing framework, ensuring accurate backtesting results and realistic performance evaluation across different market conditions and time periods. The implementation maintains consistency between historical testing and live trading applications.
## Comprehensive Risk Management Framework
The strategy features dual stop loss methodologies addressing different risk management philosophies and market analysis approaches. Entry price-based stop losses calculate stop levels as fixed percentages below entry prices, providing predictable risk exposure and consistent risk-reward ratio maintenance across all trades.
The percentage-based stop loss system enables precise risk control by limiting maximum loss per trade to predetermined levels regardless of market volatility or entry timing. This approach proves essential for systematic trading strategies requiring consistent risk parameters and capital preservation during adverse market conditions.
Lowest low-based stop losses identify recent price support levels by analyzing minimum prices over adjustable lookback periods, placing stops below these technical levels with additional buffer percentages. This methodology aligns stop placement with market structure rather than arbitrary percentage calculations, potentially improving stop loss effectiveness during normal market fluctuations.
The lookback period adjustment enables optimization for different timeframes and market characteristics, with shorter periods providing tighter stops for active trading and longer periods offering broader stops suitable for position trading approaches. Buffer percentage additions ensure stops remain below obvious support levels where other market participants might place similar orders.
## Visual Customization and Interface Design
The strategy provides comprehensive visual customization through eight predefined color schemes designed for different chart backgrounds and personal preferences. Color scheme options include Classic bright green and red combinations, Ocean themes featuring blue and orange contrasts, Sunset combinations using gold and crimson, and Neon schemes providing high visibility through bright color selections.
Professional color schemes such as Forest, Royal, and Fire themes offer sophisticated alternatives suitable for business presentations and professional trading environments. The Custom color scheme enables precise color selection through individual color picker controls, maintaining maximum flexibility for specific visual requirements.
Label styling options accommodate different chart analysis preferences through text bubble, triangle, and arrow display formats. Size adjustments range from tiny through huge settings, ensuring appropriate visual scaling across different screen resolutions and chart configurations. Text color customization maintains readability across various chart themes and background selections.
## Signal Quality Enhancement Features
The strategy incorporates signal filtering mechanisms designed to eliminate repetitive signal generation during choppy market conditions. The disable repeating signals option prevents consecutive identical signals until opposing conditions occur, reducing overtrading during consolidation phases and improving overall signal quality.
Signal confirmation requirements ensure all technical criteria align before trade execution, reducing false signal occurrence while maintaining reasonable trading frequency for active strategies. The multi-layered approach balances signal quality against opportunity frequency through adjustable parameter optimization.
Entry and exit visualization provides clear trade identification through customizable labels positioned at relevant price levels. Stop loss visualization displays active risk levels through colored line plots, ensuring complete transparency regarding current risk management parameters during live trading operations.
## Implementation Guidelines and Optimization
The strategy performs effectively across multiple timeframes with optimal results typically occurring on intermediate timeframes ranging from fifteen minutes through four hours. Higher timeframes provide more reliable pattern formation and reduced false signal occurrence, while lower timeframes increase trading frequency at the expense of some signal reliability.
Parameter optimization should focus on RSI threshold adjustments based on market volatility characteristics and candlestick pattern timeframe analysis. Higher RSI thresholds generate fewer but potentially higher quality signals, while lower thresholds increase signal frequency with corresponding reliability considerations.
Stop loss method selection depends on trading style preferences and market analysis philosophy. Entry price-based stops suit systematic approaches requiring consistent risk parameters, while lowest low-based stops align with technical analysis methodologies emphasizing market structure recognition.
## Performance Considerations and Risk Disclosure
The strategy operates exclusively on long positions, making it unsuitable for bear market conditions or extended downtrend periods. Users should consider market environment analysis and broader trend assessment before implementing the strategy during adverse market conditions.
Candlestick pattern reliability varies significantly across different market conditions, with higher reliability typically occurring during trending markets compared to ranging or volatile conditions. Strategy performance may deteriorate during periods of reduced pattern effectiveness or increased market noise.
Risk management through stop loss implementation remains essential for capital preservation during adverse market movements. The strategy does not guarantee profitable outcomes and requires proper position sizing and risk management to prevent significant capital loss during unfavorable trading periods.
## Technical Specifications
The strategy utilizes standard TradingView Pine Script functions ensuring compatibility across all supported instruments and timeframes. Default configuration employs 14-period RSI calculations, adjustable candle stability thresholds, and customizable price decline verification periods optimized for general market conditions.
Initial capital settings default to $10,000 with percentage-based equity allocation, though users can adjust these parameters based on account size and risk tolerance requirements. The strategy maintains detailed trade logs and performance metrics through TradingView's integrated backtesting framework.
Alert integration enables real-time notification of entry and exit signals, stop loss executions, and other significant trading events. The comprehensive alert system supports automated trading applications and manual trade management approaches through detailed signal information provision.
## Conclusion
The Mutanabby_AI Algo Pro Strategy provides a systematic framework for candlestick pattern trading with comprehensive risk management and position sizing flexibility. The strategy's strength lies in its multi-layered confirmation approach and sophisticated customization options, enabling adaptation to various trading styles and market conditions.
Successful implementation requires understanding of candlestick pattern analysis principles and appropriate parameter optimization for specific market characteristics. The strategy serves traders seeking automated execution of proven technical analysis techniques while maintaining comprehensive control over risk management and position sizing methodologies.
Breakouts With DXY Filter Strategy [LuciTech]This advanced breakout strategy combines pivot-based breakout detection with an innovative DXY (US Dollar Index) inverse correlation filter to enhance trade selection quality. The strategy identifies breakouts from recent pivot highs and lows while using DXY movements as a confirmation filter, based on the principle that USD strength/weakness often inversely correlates with other asset movements.
Key Features
Core Breakout Logic
- Pivot-Based Detection: Identifies breakouts above recent pivot highs (bullish) and below recent pivot lows (bearish)
- Customizable Lookback: Adjustable pivot length for different market conditions
- Visual Breakout Lines: Optional display of breakout levels with customizable colors
DXY Inverse Correlation Filter
- Smart USD Filter: Uses DXY movements to confirm breakout signals
- Inverse Logic: Long signals require DXY bearishness, short signals require DXY bullishness
- Threshold Control: Minimum DXY movement percentage required for signal confirmation
- Real-time DXY Data: Pulls live DXY data for accurate correlation analysis
Moving Average Filter
- Multiple MA Types: Support for SMA, EMA, WMA, VWMA, and HMA
- Trend Confirmation: Only takes trades in the direction of the selected moving average
- Customizable Parameters: Adjustable length and source for the moving average
Advanced Risk Management
- Multiple Stop Loss Types:
- ATR-based stops with customizable multiplier
- Candle-based stops using previous candle levels
- Fixed point-based stops
- Risk-Reward Optimization: Configurable risk-reward ratios (1:1 to 1:10)
- Breakeven Function: Automatic stop loss adjustment to breakeven after specified R-multiple
- Position Sizing: Percentage-based risk management with automatic position calculation
Time-Based Trading
- Session Filter: Trade only during specified time windows
- London Time Zone: Uses Europe/London timezone for consistency
- Visual Session Highlighting: Optional background fill for active trading hours
Alert System
- Webhook Integration: JSON-formatted alerts for automated trading
- Telegram Support: Pre-formatted messages for Telegram bot integration
- Multiple Formats: Standard, Telegram, and Concise Telegram alert options
- Real-time Notifications: Instant alerts on breakout signals
How It Works
1. Breakout Detection: The script continuously monitors for closes above recent pivot highs or below recent pivot lows
2. DXY Confirmation: When a breakout occurs, the script checks if DXY is moving in the opposite direction with sufficient momentum
3. MA Filter: If enabled, ensures the breakout aligns with the overall trend direction
4. Time Filter: Validates that the signal occurs within the specified trading hours
5. Risk Calculation: Automatically calculates position size based on the defined risk percentage and stop loss distance
6. Trade Execution: Places trades with predetermined stop loss and take profit levels
Unique Advantages
- Multi-Timeframe Approach: Combines asset-specific breakouts with broader USD market sentiment
- False Breakout Reduction: DXY filter helps eliminate breakouts that lack fundamental backing
- Comprehensive Risk Management: Multiple stop loss methods and automatic position sizing
- High Customization: Extensive parameters for different trading styles and market conditions
- Professional Alert System: Ready for automated trading integration
OBV ATR Strategy (OBV Breakout Channel) bas20230503ผมแก้ไขจาก OBV+SMA อันเดิม ของเดิม ดูที่เส้น SMA สองเส้นตัดกันมั่นห่วยแตกสำหรับที่ผมลองเทรดจริง และหลักการเบรค ได้แรงบันดาลใจ ATR จาก เทพคอย ที่ใช้กับราคา แต่นี้ใช้กับ OBV แทน
และผมใช้เจมินี้ เพื่อแก้ ให้ เป็น strategy เพื่อเช็คย้อนหลังได้ง่ายกว่าเดิม
หลักการง่ายคือถ้ามันขึ้น มันจะขึ้นเรื่อยๆ
เขียน แบบสุภาพ (น่าจะอ่านได้ง่ายกว่าผมเขียน)
สคริปต์นี้ได้รับการพัฒนาต่อยอดจากแนวคิด OBV+SMA Crossover แบบดั้งเดิม ซึ่งจากการทดสอบส่วนตัวพบว่าประสิทธิภาพยังไม่น่าพอใจ กลยุทธ์ใหม่นี้จึงเปลี่ยนมาใช้หลักการ "Breakout" ซึ่งได้รับแรงบันดาลใจมาจากการใช้ ATR สร้างกรอบของราคา แต่เราได้นำมาประยุกต์ใช้กับ On-Balance Volume (OBV) แทน นอกจากนี้ สคริปต์ได้ถูกแปลงเป็น Strategy เต็มรูปแบบ (โดยความช่วยเหลือจาก Gemini AI) เพื่อให้สามารถทดสอบย้อนหลัง (Backtest) และประเมินประสิทธิภาพได้อย่างแม่นยำ
หลักการของกลยุทธ์: กลยุทธ์นี้ทำงานบนแนวคิดโมเมนตัมที่ว่า "เมื่อแนวโน้มได้เกิดขึ้นแล้ว มีโอกาสที่มันจะดำเนินต่อไป" โดยจะมองหาการทะลุของพลังซื้อ-ขาย (OBV) ที่แข็งแกร่งเป็นพิเศษเป็นสัญญาณเข้าเทร
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สคริปต์นี้เป็นกลยุทธ์ (Strategy) ที่ใช้ On-Balance Volume (OBV) ซึ่งเป็นอินดิเคเตอร์ที่วัดแรงซื้อและแรงขายสะสม แทนที่จะใช้การตัดกันของเส้นค่าเฉลี่ย (SMA Crossover) ที่เป็นแบบพื้นฐาน กลยุทธ์นี้จะมองหาการ "ทะลุ" (Breakout) ของพลัง OBV ออกจากกรอบสูงสุด-ต่ำสุดของตัวเองในรอบที่ผ่านมา
สัญญาณกระทิง (Bull Signal): เกิดขึ้นเมื่อพลังการซื้อ (OBV) แข็งแกร่งจนสามารถทะลุจุดสูงสุดของตัวเองในอดีตได้ บ่งบอกถึงโอกาสที่แนวโน้มจะเปลี่ยนเป็นขาขึ้น
สัญญาณหมี (Bear Signal): เกิดขึ้นเมื่อพลังการขาย (OBV) รุนแรงจนสามารถกดดันให้ OBV ทะลุจุดต่ำสุดของตัวเองในอดีตได้ บ่งบอกถึงโอกาสที่แนวโน้มจะเปลี่ยนเป็นขาลง
ส่วนประกอบบนกราฟ (Indicator Components)
เส้น OBV
เส้นหลัก ที่เปลี่ยนเขียวเป็นแดง เป็นทั้งแนวรับและแนวต้าน และ จุด stop loss
เส้นนี้คือหัวใจของอินดิเคเตอร์ ที่แสดงถึงพลังสะสมของ Volume
เมื่อเส้นเป็นสีเขียว (แนวรับ): จะปรากฏขึ้นเมื่อกลยุทธ์เข้าสู่ "โหมดกระทิง" เส้นนี้คือระดับต่ำสุดของ OBV ในอดีต และทำหน้าที่เป็นแนวรับไดนามิก
เมื่อเส้นกลายเป็นสีแดงสีแดง (แนวต้าน): จะปรากฏขึ้นเมื่อกลยุทธ์เข้าสู่ "โหมดหมี" เส้นนี้คือระดับสูงสุดของ OBV ในอดีต และทำหน้าที่เป็นแนวต้านไดนามิก
สัญลักษณ์สัญญาณ (Signal Markers):
Bull 🔼 (สามเหลี่ยมขึ้นสีเขียว): คือสัญญาณ "เข้าซื้อ" (Long) จะปรากฏขึ้น ณ จุดที่ OBV ทะลุขึ้นไปเหนือกรอบด้านบนเป็นครั้งแรก
Bear 🔽 (สามเหลี่ยมลงสีแดง): คือสัญญาณ "เข้าขาย" (Short) จะปรากฏขึ้น ณ จุดที่ OBV ทะลุลงไปต่ำกว่ากรอบด้านล่างเป็นครั้งแรก
วิธีการใช้งาน (How to Use)
เพิ่มสคริปต์นี้ลงบนกราฟราคาที่คุณสนใจ
ไปที่แท็บ "Strategy Tester" ด้านล่างของ TradingView เพื่อดูผลการทดสอบย้อนหลัง (Backtest) ของกลยุทธ์บนสินทรัพย์และไทม์เฟรมต่างๆ
ใช้สัญลักษณ์ "Bull" และ "Bear" เป็นตัวช่วยในการตัดสินใจเข้าเทรด
ข้อควรจำ: ไม่มีกลยุทธ์ใดที่สมบูรณ์แบบ 100% ควรใช้สคริปต์นี้ร่วมกับการวิเคราะห์ปัจจัยอื่นๆ เช่น โครงสร้างราคา, แนวรับ-แนวต้านของราคา และการบริหารความเสี่ยง (Risk Management) ของตัวคุณเองเสมอ
การตั้งค่า (Inputs)
SMA Length 1 / SMA Length 2: ใช้สำหรับพล็อตเส้นค่าเฉลี่ยของ OBV เพื่อดูเป็นภาพอ้างอิง ไม่มีผลต่อตรรกะการเข้า-ออกของ Strategy อันใหม่ แต่มันเป็นของเก่า ถ้าชอบ ก็ใช้ได้ เมื่อ SMA สองเส้นตัดกัน หรือตัดกับเส้น OBV
High/Low Lookback Length: (ค่าพื้นฐาน30/แก้ตรงนี้ให้เหมาะสมกับ coin หรือหุ้น ตามความผันผวน ) คือระยะเวลาที่ใช้ในการคำนวณกรอบสูงสุด-ต่ำสุดของ OBV
ค่าน้อย: ทำให้กรอบแคบลง สัญญาณจะเกิดไวและบ่อยขึ้น แต่อาจมีสัญญาณหลอก (False Signal) เยอะขึ้น
ค่ามาก: ทำให้กรอบกว้างขึ้น สัญญาณจะเกิดช้าลงและน้อยลง แต่มีแนวโน้มที่จะเป็นสัญญาณที่แข็งแกร่งกว่า
แน่นอนครับ นี่คือคำแปลฉบับภาษาอังกฤษที่สรุปใจความสำคัญ กระชับ และสุภาพ เหมาะสำหรับนำไปใช้ในคำอธิบายสคริปต์ (Description) ของ TradingView ครับ
---Translate to English---
OBV Breakout Channel Strategy
This script is an evolution of a traditional OBV+SMA Crossover concept. Through personal testing, the original crossover method was found to have unsatisfactory performance. This new strategy, therefore, uses a "Breakout" principle. The inspiration comes from using ATR to create price channels, but this concept has been adapted and applied to On-Balance Volume (OBV) instead.
Furthermore, the script has been converted into a full Strategy (with assistance from Gemini AI) to enable precise backtesting and performance evaluation.
The strategy's core principle is momentum-based: "once a trend is established, it is likely to continue." It seeks to enter trades on exceptionally strong breakouts of buying or selling pressure as measured by OBV.
Core Concept
This is a Strategy that uses On-Balance Volume (OBV), an indicator that measures cumulative buying and selling pressure. Instead of relying on a basic Simple Moving Average (SMA) Crossover, this strategy identifies a "Breakout" of the OBV from its own highest-high and lowest-low channel over a recent period.
Bull Signal: Occurs when the buying pressure (OBV) is strong enough to break above its own recent highest high, indicating a potential shift to an upward trend.
Bear Signal: Occurs when the selling pressure (OBV) is intense enough to push the OBV below its own recent lowest low, indicating a potential shift to a downward trend.
On-Screen Components
1. OBV Line
This is the main indicator line, representing the cumulative volume. Its color changes to green when OBV is rising and red when it is falling.
2. Dynamic Support & Resistance Line
This is the thick Green or Red line that appears based on the strategy's current "mode." This line serves as a dynamic support/resistance level and can be used as a reference for stop-loss placement.
Green Line (Support): Appears when the strategy enters "Bull Mode." This line represents the lowest low of the OBV in the recent past and acts as dynamic support.
Red Line (Resistance): Appears when the strategy enters "Bear Mode." This line represents the highest high of the OBV in the recent past and acts as dynamic resistance.
3. Signal Markers
Bull 🔼 (Green Up Triangle): This is the "Long Entry" signal. It appears at the moment the OBV first breaks out above its high-low channel.
Bear 🔽 (Red Down Triangle): This is the "Short Entry" signal. It appears at the moment the OBV first breaks down below its high-low channel.
How to Use
Add this script to the price chart of your choice.
Navigate to the "Strategy Tester" panel at the bottom of TradingView to view the backtesting results for the strategy on different assets and timeframes.
Use the "Bull" and "Bear" signals as aids in your trading decisions.
Disclaimer: No strategy is 100% perfect. This script should always be used in conjunction with other forms of analysis, such as price structure, key price-based support/resistance levels, and your own personal risk management rules.
Inputs
SMA Length 1 / SMA Length 2: These are used to plot moving averages on the OBV for visual reference. They are part of the legacy logic and do not affect the new breakout strategy. However, they are kept for traders who may wish to observe their crossovers for additional confirmation.
High/Low Lookback Length: (Most Important Setting) This determines the period used to calculate the highest-high and lowest-low OBV channel. (Default is 30; adjust this to suit the asset's volatility).
A smaller value: Creates a narrower channel, leading to more frequent and faster signals, but potentially more false signals.
A larger value: Creates a wider channel, leading to fewer and slower signals, which are likely to be more significant.
Anomalous Holonomy Field Theory🌌 Anomalous Holonomy Field Theory (AHFT) - Revolutionary Quantum Market Analysis
Where Theoretical Physics Meets Trading Reality
A Groundbreaking Synthesis of Differential Geometry, Quantum Field Theory, and Market Dynamics
🔬 THEORETICAL FOUNDATION - THE MATHEMATICS OF MARKET REALITY
The Anomalous Holonomy Field Theory represents an unprecedented fusion of advanced mathematical physics with practical market analysis. This isn't merely another indicator repackaging old concepts - it's a fundamentally new lens through which to view and understand market structure .
1. HOLONOMY GROUPS (Differential Geometry)
In differential geometry, holonomy measures how vectors change when parallel transported around closed loops in curved space. Applied to markets:
Mathematical Formula:
H = P exp(∮_C A_μ dx^μ)
Where:
P = Path ordering operator
A_μ = Market connection (price-volume gauge field)
C = Closed price path
Market Implementation:
The holonomy calculation measures how price "remembers" its journey through market space. When price returns to a previous level, the holonomy captures what has changed in the market's internal geometry. This reveals:
Hidden curvature in the market manifold
Topological obstructions to arbitrage
Geometric phase accumulated during price cycles
2. ANOMALY DETECTION (Quantum Field Theory)
Drawing from the Adler-Bell-Jackiw anomaly in quantum field theory:
Mathematical Formula:
∂_μ j^μ = (e²/16π²)F_μν F̃^μν
Where:
j^μ = Market current (order flow)
F_μν = Field strength tensor (volatility structure)
F̃^μν = Dual field strength
Market Application:
Anomalies represent symmetry breaking in market structure - moments when normal patterns fail and extraordinary opportunities arise. The system detects:
Spontaneous symmetry breaking (trend reversals)
Vacuum fluctuations (volatility clusters)
Non-perturbative effects (market crashes/melt-ups)
3. GAUGE THEORY (Theoretical Physics)
Markets exhibit gauge invariance - the fundamental physics remains unchanged under certain transformations:
Mathematical Formula:
A'_μ = A_μ + ∂_μΛ
This ensures our signals are gauge-invariant observables , immune to arbitrary market "coordinate changes" like gaps or reference point shifts.
4. TOPOLOGICAL DATA ANALYSIS
Using persistent homology and Morse theory:
Mathematical Formula:
β_k = dim(H_k(X))
Where β_k are the Betti numbers describing topological features that persist across scales.
🎯 REVOLUTIONARY SIGNAL CONFIGURATION
Signal Sensitivity (0.5-12.0, default 2.5)
Controls the responsiveness of holonomy field calculations to market conditions. This parameter directly affects the threshold for detecting quantum phase transitions in price action.
Optimization by Timeframe:
Scalping (1-5min): 1.5-3.0 for rapid signal generation
Day Trading (15min-1H): 2.5-5.0 for balanced sensitivity
Swing Trading (4H-1D): 5.0-8.0 for high-quality signals only
Score Amplifier (10-200, default 50)
Scales the raw holonomy field strength to produce meaningful signal values. Higher values amplify weak signals in low-volatility environments.
Signal Confirmation Toggle
When enabled, enforces additional technical filters (EMA and RSI alignment) to reduce false positives. Essential for conservative strategies.
Minimum Bars Between Signals (1-20, default 5)
Prevents overtrading by enforcing quantum decoherence time between signals. Higher values reduce whipsaws in choppy markets.
👑 ELITE EXECUTION SYSTEM
Execution Modes:
Conservative Mode:
Stricter signal criteria
Higher quality thresholds
Ideal for stable market conditions
Adaptive Mode:
Self-adjusting parameters
Balances signal frequency with quality
Recommended for most traders
Aggressive Mode:
Maximum signal sensitivity
Captures rapid market moves
Best for experienced traders in volatile conditions
Dynamic Position Sizing:
When enabled, the system scales position size based on:
Holonomy field strength
Current volatility regime
Recent performance metrics
Advanced Exit Management:
Implements trailing stops based on ATR and signal strength, with mode-specific multipliers for optimal profit capture.
🧠 ADAPTIVE INTELLIGENCE ENGINE
Self-Learning System:
The strategy analyzes recent trade outcomes and adjusts:
Risk multipliers based on win/loss ratios
Signal weights according to performance
Market regime detection for environmental adaptation
Learning Speed (0.05-0.3):
Controls adaptation rate. Higher values = faster learning but potentially unstable. Lower values = stable but slower adaptation.
Performance Window (20-100 trades):
Number of recent trades analyzed for adaptation. Longer windows provide stability, shorter windows increase responsiveness.
🎨 REVOLUTIONARY VISUAL SYSTEM
1. Holonomy Field Visualization
What it shows: Multi-layer quantum field bands representing market resonance zones
How to interpret:
Blue/Purple bands = Primary holonomy field (strongest resonance)
Band width = Field strength and volatility
Price within bands = Normal quantum state
Price breaking bands = Quantum phase transition
Trading application: Trade reversals at band extremes, breakouts on band violations with strong signals.
2. Quantum Portals
What they show: Entry signals with recursive depth patterns indicating momentum strength
How to interpret:
Upward triangles with portals = Long entry signals
Downward triangles with portals = Short entry signals
Portal depth = Signal strength and expected momentum
Color intensity = Probability of success
Trading application: Enter on portal appearance, with size proportional to portal depth.
3. Field Resonance Bands
What they show: Fibonacci-based harmonic price zones where quantum resonance occurs
How to interpret:
Dotted circles = Minor resonance levels
Solid circles = Major resonance levels
Color coding = Resonance strength
Trading application: Use as dynamic support/resistance, expect reactions at resonance zones.
4. Anomaly Detection Grid
What it shows: Fractal-based support/resistance with anomaly strength calculations
How to interpret:
Triple-layer lines = Major fractal levels with high anomaly probability
Labels show: Period (H8-H55), Price, and Anomaly strength (φ)
⚡ symbol = Extreme anomaly detected
● symbol = Strong anomaly
○ symbol = Normal conditions
Trading application: Expect major moves when price approaches high anomaly levels. Use for precise entry/exit timing.
5. Phase Space Flow
What it shows: Background heatmap revealing market topology and energy
How to interpret:
Dark background = Low market energy, range-bound
Purple glow = Building energy, trend developing
Bright intensity = High energy, strong directional move
Trading application: Trade aggressively in bright phases, reduce activity in dark phases.
📊 PROFESSIONAL DASHBOARD METRICS
Holonomy Field Strength (-100 to +100)
What it measures: The Wilson loop integral around price paths
>70: Strong positive curvature (bullish vortex)
<-70: Strong negative curvature (bearish collapse)
Near 0: Flat connection (range-bound)
Anomaly Level (0-100%)
What it measures: Quantum vacuum expectation deviation
>70%: Major anomaly (phase transition imminent)
30-70%: Moderate anomaly (elevated volatility)
<30%: Normal quantum fluctuations
Quantum State (-1, 0, +1)
What it measures: Market wave function collapse
+1: Bullish eigenstate |↑⟩
0: Superposition (uncertain)
-1: Bearish eigenstate |↓⟩
Signal Quality Ratings
LEGENDARY: All quantum fields aligned, maximum probability
EXCEPTIONAL: Strong holonomy with anomaly confirmation
STRONG: Good field strength, moderate anomaly
MODERATE: Decent signals, some uncertainty
WEAK: Minimal edge, high quantum noise
Performance Metrics
Win Rate: Rolling performance with emoji indicators
Daily P&L: Real-time profit tracking
Adaptive Risk: Current risk multiplier status
Market Regime: Bull/Bear classification
🏆 WHY THIS CHANGES EVERYTHING
Traditional technical analysis operates on 100-year-old principles - moving averages, support/resistance, and pattern recognition. These work because many traders use them, creating self-fulfilling prophecies.
AHFT transcends this limitation by analyzing markets through the lens of fundamental physics:
Markets have geometry - The holonomy calculations reveal this hidden structure
Price has memory - The geometric phase captures path-dependent effects
Anomalies are predictable - Quantum field theory identifies symmetry breaking
Everything is connected - Gauge theory unifies disparate market phenomena
This isn't just a new indicator - it's a new way of thinking about markets . Just as Einstein's relativity revolutionized physics beyond Newton's mechanics, AHFT revolutionizes technical analysis beyond traditional methods.
🔧 OPTIMAL SETTINGS FOR MNQ 10-MINUTE
For the Micro E-mini Nasdaq-100 on 10-minute timeframe:
Signal Sensitivity: 2.5-3.5
Score Amplifier: 50-70
Execution Mode: Adaptive
Min Bars Between: 3-5
Theme: Quantum Nebula or Dark Matter
💭 THE JOURNEY - FROM IMPOSSIBLE THEORY TO TRADING REALITY
Creating AHFT was a mathematical odyssey that pushed the boundaries of what's possible in Pine Script. The journey began with a seemingly impossible question: Could the profound mathematical structures of theoretical physics be translated into practical trading tools?
The Theoretical Challenge:
Months were spent diving deep into differential geometry textbooks, studying the works of Chern, Simons, and Witten. The mathematics of holonomy groups and gauge theory had never been applied to financial markets. Translating abstract mathematical concepts like parallel transport and fiber bundles into discrete price calculations required novel approaches and countless failed attempts.
The Computational Nightmare:
Pine Script wasn't designed for quantum field theory calculations. Implementing the Wilson loop integral, managing complex array structures for anomaly detection, and maintaining computational efficiency while calculating geometric phases pushed the language to its limits. There were moments when the entire project seemed impossible - the script would timeout, produce nonsensical results, or simply refuse to compile.
The Breakthrough Moments:
After countless sleepless nights and thousands of lines of code, breakthrough came through elegant simplifications. The realization that market anomalies follow patterns similar to quantum vacuum fluctuations led to the revolutionary anomaly detection system. The discovery that price paths exhibit holonomic memory unlocked the geometric phase calculations.
The Visual Revolution:
Creating visualizations that could represent 4-dimensional quantum fields on a 2D chart required innovative approaches. The multi-layer holonomy field, recursive quantum portals, and phase space flow representations went through dozens of iterations before achieving the perfect balance of beauty and functionality.
The Balancing Act:
Perhaps the greatest challenge was maintaining mathematical rigor while ensuring practical trading utility. Every formula had to be both theoretically sound and computationally efficient. Every visual had to be both aesthetically pleasing and information-rich.
The result is more than a strategy - it's a synthesis of pure mathematics and market reality that reveals the hidden order within apparent chaos.
📚 INTEGRATED DOCUMENTATION
Once applied to your chart, AHFT includes comprehensive tooltips on every input parameter. The source code contains detailed explanations of the mathematical theory, practical applications, and optimization guidelines. This published description provides the overview - the indicator itself is a complete educational resource.
⚠️ RISK DISCLAIMER
While AHFT employs advanced mathematical models derived from theoretical physics, markets remain inherently unpredictable. No mathematical model, regardless of sophistication, can guarantee future results. This strategy uses realistic commission ($0.62 per contract) and slippage (1 tick) in all calculations. Past performance does not guarantee future results. Always use appropriate risk management and never risk more than you can afford to lose.
🌟 CONCLUSION
The Anomalous Holonomy Field Theory represents a quantum leap in technical analysis - literally. By applying the profound insights of differential geometry, quantum field theory, and gauge theory to market analysis, AHFT reveals structure and opportunities invisible to traditional methods.
From the holonomy calculations that capture market memory to the anomaly detection that identifies phase transitions, from the adaptive intelligence that learns and evolves to the stunning visualizations that make the invisible visible, every component works in mathematical harmony.
This is more than a trading strategy. It's a new lens through which to view market reality.
Trade with the precision of physics. Trade with the power of mathematics. Trade with AHFT.
I hope this serves as a good replacement for Quantum Edge Pro - Adaptive AI until I'm able to fix it.
— Dskyz, Trade with insight. Trade with anticipation.
Bober XM v2.0# ₿ober XM v2.0 Trading Bot Documentation
**Developer's Note**: While our previous Bot 1.3.1 was removed due to guideline violations, this setback only fueled our determination to create something even better. Rising from this challenge, Bober XM 2.0 emerges not just as an update, but as a complete reimagining with multi-timeframe analysis, enhanced filters, and superior adaptability. This adversity pushed us to innovate further and deliver a strategy that's smarter, more agile, and more powerful than ever before. Challenges create opportunity - welcome to Cryptobeat's finest work yet.
## !!!!You need to tune it for your own pair and timeframe and retune it periodicaly!!!!!
## Overview
The ₿ober XM v2.0 is an advanced dual-channel trading bot with multi-timeframe analysis capabilities. It integrates multiple technical indicators, customizable risk management, and advanced order execution via webhook for automated trading. The bot's distinctive feature is its separate channel systems for long and short positions, allowing for asymmetric trade strategies that adapt to different market conditions across multiple timeframes.
### Key Features
- **Multi-Timeframe Analysis**: Analyze price data across multiple timeframes simultaneously
- **Dual Channel System**: Separate parameter sets for long and short positions
- **Advanced Entry Filters**: RSI, Volatility, Volume, Bollinger Bands, and KEMAD filters
- **Machine Learning Moving Average**: Adaptive prediction-based channels
- **Multiple Entry Strategies**: Breakout, Pullback, and Mean Reversion modes
- **Risk Management**: Customizable stop-loss, take-profit, and trailing stop settings
- **Webhook Integration**: Compatible with external trading bots and platforms
### Strategy Components
| Component | Description |
|---------|-------------|
| **Dual Channel Trading** | Uses either Keltner Channels or Machine Learning Moving Average (MLMA) with separate settings for long and short positions |
| **MLMA Implementation** | Machine learning algorithm that predicts future price movements and creates adaptive bands |
| **Pivot Point SuperTrend** | Trend identification and confirmation system based on pivot points |
| **Three Entry Strategies** | Choose between Breakout, Pullback, or Mean Reversion approaches |
| **Advanced Filter System** | Multiple customizable filters with multi-timeframe support to avoid false signals |
| **Custom Exit Logic** | Exits based on OBV crossover of its moving average combined with pivot trend changes |
### Note for Novice Users
This is a fully featured real trading bot and can be tweaked for any ticker — SOL is just an example. It follows this structure:
1. **Indicator** – gives the initial signal
2. **Entry strategy** – decides when to open a trade
3. **Exit strategy** – defines when to close it
4. **Trend confirmation** – ensures the trade follows the market direction
5. **Filters** – cuts out noise and avoids weak setups
6. **Risk management** – controls losses and protects your capital
To tune it for a different pair, you'll need to start from scratch:
1. Select the timeframe (candle size)
2. Turn off all filters and trend entry/exit confirmations
3. Choose a channel type, channel source and entry strategy
4. Adjust risk parameters
5. Tune long and short settings for the channel
6. Fine-tune the Pivot Point Supertrend and Main Exit condition OBV
This will generate a lot of signals and activity on the chart. Your next task is to find the right combination of filters and settings to reduce noise and tune it for profitability.
### Default Strategy values
Default values are tuned for: Symbol BITGET:SOLUSDT.P 5min candle
Filters are off by default: Try to play with it to understand how it works
## Configuration Guide
### General Settings
| Setting | Description | Default Value |
|---------|-------------|---------------|
| **Long Positions** | Enable or disable long trades | Enabled |
| **Short Positions** | Enable or disable short trades | Enabled |
| **Risk/Reward Area** | Visual display of stop-loss and take-profit zones | Enabled |
| **Long Entry Source** | Price data used for long entry signals | hl2 (High+Low/2) |
| **Short Entry Source** | Price data used for short entry signals | hl2 (High+Low/2) |
The bot allows you to trade long positions, short positions, or both simultaneously. Each direction has its own set of parameters, allowing for fine-tuned strategies that recognize the asymmetric nature of market movements.
### Multi-Timeframe Settings
1. **Enable Multi-Timeframe Analysis**: Toggle 'Enable Multi-Timeframe Analysis' in the Multi-Timeframe Settings section
2. **Configure Timeframes**: Set appropriate higher timeframes based on your trading style:
- Timeframe 1: Default is now 15 minutes (intraday confirmation)
- Timeframe 2: Default is 4 hours (trend direction)
3. **Select Sources per Indicator**: For each indicator (RSI, KEMAD, Volume, etc.), choose:
- The desired timeframe (current, mtf1, or mtf2)
- The appropriate price type (open, high, low, close, hl2, hlc3, ohlc4)
### Entry Strategies
- **Breakout**: Enter when price breaks above/below the channel
- **Pullback**: Enter when price pulls back to the channel
- **Mean Reversion**: Enter when price is extended from the channel
You can enable different strategies for long and short positions.
### Core Components
### Risk Management
- **Position Size**: Control risk with percentage-based position sizing
- **Stop Loss Options**:
- Fixed: Set a specific price or percentage from entry
- ATR-based: Dynamic stop-loss based on market volatility
- Swing: Uses recent swing high/low points
- **Take Profit**: Multiple targets with percentage allocation
- **Trailing Stop**: Dynamic stop that follows price movement
## Advanced Usage Strategies
### Moving Average Type Selection Guide
- **SMA**: More stable in choppy markets, good for higher timeframes
- **EMA/WMA**: More responsive to recent price changes, better for entry signals
- **VWMA**: Adds volume weighting for stronger trends, use with Volume filter
- **HMA**: Balance between responsiveness and noise reduction, good for volatile markets
### Multi-Timeframe Strategy Approaches
- **Trend Confirmation**: Use higher timeframe RSI (mtf2) for overall trend, current timeframe for entries
- **Entry Precision**: Use KEMAD on current timeframe with volume filter on mtf1
- **False Signal Reduction**: Apply RSI filter on mtf1 with strict KEMAD settings
### Market Condition Optimization
| Market Condition | Recommended Settings |
|------------------|----------------------|
| **Trending** | Use Breakout strategy with KEMAD filter on higher timeframe |
| **Ranging** | Use Mean Reversion with strict RSI filter (mtf1) |
| **Volatile** | Increase ATR multipliers, use HMA for moving averages |
| **Low Volatility** | Decrease noise parameters, use pullback strategy |
## Webhook Integration
The strategy features a professional webhook system that allows direct connectivity to your exchange or trading platform of choice through third-party services like 3commas, Alertatron, or Autoview.
The webhook payload includes all necessary parameters for automated execution:
- Entry price and direction
- Stop loss and take profit levels
- Position size
- Custom identifier for webhook routing
## Performance Optimization Tips
1. **Start with Defaults**: Begin with the default settings for your timeframe before customizing
2. **Adjust One Component at a Time**: Make incremental changes and test the impact
3. **Match MA Types to Market Conditions**: Use appropriate moving average types based on the Market Condition Optimization table
4. **Timeframe Synergy**: Create logical relationships between timeframes (e.g., 5min chart with 15min and 4h higher timeframes)
5. **Periodic Retuning**: Markets evolve - regularly review and adjust parameters
## Common Setups
### Crypto Trend-Following
- MLMA with EMA or HMA
- Higher RSI thresholds (75/25)
- KEMAD filter on mtf1
- Breakout entry strategy
### Stock Swing Trading
- MLMA with SMA for stability
- Volume filter with higher threshold
- KEMAD with increased filter order
- Pullback entry strategy
### Forex Scalping
- MLMA with WMA and lower noise parameter
- RSI filter on current timeframe
- Use highest timeframe for trend direction only
- Mean Reversion strategy
## Webhook Configuration
- **Benefits**:
- Automated trade execution without manual intervention
- Immediate response to market conditions
- Consistent execution of your strategy
- **Implementation Notes**:
- Requires proper webhook configuration on your exchange or platform
- Test thoroughly with small position sizes before full deployment
- Consider latency between signal generation and execution
### Backtesting Period
Define a specific historical period to evaluate the bot's performance:
| Setting | Description | Default Value |
|---------|-------------|---------------|
| **Start Date** | Beginning of backtest period | January 1, 2025 |
| **End Date** | End of backtest period | December 31, 2026 |
- **Best Practice**: Test across different market conditions (bull markets, bear markets, sideways markets)
- **Limitation**: Past performance doesn't guarantee future results
## Entry and Exit Strategies
### Dual-Channel System
A key innovation of the Bober XM is its dual-channel approach:
- **Independent Parameters**: Each trade direction has its own channel settings
- **Asymmetric Trading**: Recognizes that markets often behave differently in uptrends versus downtrends
- **Optimized Performance**: Fine-tune settings for both bullish and bearish conditions
This approach allows the bot to adapt to the natural asymmetry of markets, where uptrends often develop gradually while downtrends can be sharp and sudden.
### Channel Types
#### 1. Keltner Channels
Traditional volatility-based channels using EMA and ATR:
| Setting | Long Default | Short Default |
|---------|--------------|---------------|
| **EMA Length** | 37 | 20 |
| **ATR Length** | 13 | 17 |
| **Multiplier** | 1.4 | 1.9 |
| **Source** | low | high |
- **Strengths**:
- Reliable in trending markets
- Less prone to whipsaws than Bollinger Bands
- Clear visual representation of volatility
- **Weaknesses**:
- Can lag during rapid market changes
- Less effective in choppy, non-trending markets
#### 2. Machine Learning Moving Average (MLMA)
Advanced predictive model using kernel regression (RBF kernel):
| Setting | Description | Options |
|---------|-------------|--------|
| **Source MA** | Price data used for MA calculations | Any price source (low/high/close/etc.) |
| **Moving Average Type** | Type of MA algorithm for calculations | SMA, EMA, WMA, VWMA, RMA, HMA |
| **Trend Source** | Price data used for trend determination | Any price source (close default) |
| **Window Size** | Historical window for MLMA calculations | 5+ (default: 16) |
| **Forecast Length** | Number of bars to forecast ahead | 1+ (default: 3) |
| **Noise Parameter** | Controls smoothness of prediction | 0.01+ (default: ~0.43) |
| **Band Multiplier** | Multiplier for channel width | 0.1+ (default: 0.5-0.6) |
- **Strengths**:
- Predictive rather than reactive
- Adapts quickly to changing market conditions
- Better at identifying trend reversals early
- **Weaknesses**:
- More computationally intensive
- Requires careful parameter tuning
- Can be sensitive to input data quality
### Entry Strategies
| Strategy | Description | Ideal Market Conditions |
|----------|-------------|-------------------------|
| **Breakout** | Enters when price breaks through channel bands, indicating strong momentum | High volatility, emerging trends |
| **Pullback** | Enters when price retraces to the middle band after testing extremes | Established trends with regular pullbacks |
| **Mean Reversion** | Enters at channel extremes, betting on a return to the mean | Range-bound or oscillating markets |
#### Breakout Strategy (Default)
- **Implementation**: Enters long when price crosses above the upper band, short when price crosses below the lower band
- **Strengths**: Captures strong momentum moves, performs well in trending markets
- **Weaknesses**: Can lead to late entries, higher risk of false breakouts
- **Optimization Tips**:
- Increase channel multiplier for fewer but more reliable signals
- Combine with volume confirmation for better accuracy
#### Pullback Strategy
- **Implementation**: Enters long when price pulls back to middle band during uptrend, short during downtrend pullbacks
- **Strengths**: Better entry prices, lower risk, higher probability setups
- **Weaknesses**: Misses some strong moves, requires clear trend identification
- **Optimization Tips**:
- Use with trend filters to confirm overall direction
- Adjust middle band calculation for market volatility
#### Mean Reversion Strategy
- **Implementation**: Enters long at lower band, short at upper band, expecting price to revert to the mean
- **Strengths**: Excellent entry prices, works well in ranging markets
- **Weaknesses**: Dangerous in strong trends, can lead to fighting the trend
- **Optimization Tips**:
- Implement strong trend filters to avoid counter-trend trades
- Use smaller position sizes due to higher risk nature
### Confirmation Indicators
#### Pivot Point SuperTrend
Combines pivot points with ATR-based SuperTrend for trend confirmation:
| Setting | Default Value |
|---------|---------------|
| **Pivot Period** | 25 |
| **ATR Factor** | 2.2 |
| **ATR Period** | 41 |
- **Function**: Identifies significant market turning points and confirms trend direction
- **Implementation**: Requires price to respect the SuperTrend line for trade confirmation
#### Weighted Moving Average (WMA)
Provides additional confirmation layer for entries:
| Setting | Default Value |
|---------|---------------|
| **Period** | 15 |
| **Source** | ohlc4 (average of Open, High, Low, Close) |
- **Function**: Confirms trend direction and filters out low-quality signals
- **Implementation**: Price must be above WMA for longs, below for shorts
### Exit Strategies
#### On-Balance Volume (OBV) Based Exits
Uses volume flow to identify potential reversals:
| Setting | Default Value |
|---------|---------------|
| **Source** | ohlc4 |
| **MA Type** | HMA (Options: SMA, EMA, WMA, RMA, VWMA, HMA) |
| **Period** | 22 |
- **Function**: Identifies divergences between price and volume to exit before reversals
- **Implementation**: Exits when OBV crosses its moving average in the opposite direction
- **Customizable MA Type**: Different MA types provide varying sensitivity to OBV changes:
- **SMA**: Traditional simple average, equal weight to all periods
- **EMA**: More weight to recent data, responds faster to price changes
- **WMA**: Weighted by recency, smoother than EMA
- **RMA**: Similar to EMA but smoother, reduces noise
- **VWMA**: Factors in volume, helpful for OBV confirmation
- **HMA**: Reduces lag while maintaining smoothness (default)
#### ADX Exit Confirmation
Uses Average Directional Index to confirm trend exhaustion:
| Setting | Default Value |
|---------|---------------|
| **ADX Threshold** | 35 |
| **ADX Smoothing** | 60 |
| **DI Length** | 60 |
- **Function**: Confirms trend weakness before exiting positions
- **Implementation**: Requires ADX to drop below threshold or DI lines to cross
## Filter System
### RSI Filter
- **Function**: Controls entries based on momentum conditions
- **Parameters**:
- Period: 15 (default)
- Overbought level: 71
- Oversold level: 23
- Multi-timeframe support: Current, MTF1 (15min), or MTF2 (4h)
- Customizable price source (open, high, low, close, hl2, hlc3, ohlc4)
- **Implementation**: Blocks long entries when RSI > overbought, short entries when RSI < oversold
### Volatility Filter
- **Function**: Prevents trading during excessive market volatility
- **Parameters**:
- Measure: ATR (Average True Range)
- Period: Customizable (default varies by timeframe)
- Threshold: Adjustable multiplier
- Multi-timeframe support
- Customizable price source
- **Implementation**: Blocks trades when current volatility exceeds threshold × average volatility
### Volume Filter
- **Function**: Ensures adequate market liquidity for trades
- **Parameters**:
- Threshold: 0.4× average (default)
- Measurement period: 5 (default)
- Moving average type: Customizable (HMA default)
- Multi-timeframe support
- Customizable price source
- **Implementation**: Requires current volume to exceed threshold × average volume
### Bollinger Bands Filter
- **Function**: Controls entries based on price relative to statistical boundaries
- **Parameters**:
- Period: Customizable
- Standard deviation multiplier: Adjustable
- Moving average type: Customizable
- Multi-timeframe support
- Customizable price source
- **Implementation**: Can require price to be within bands or breaking out of bands depending on strategy
### KEMAD Filter (Kalman EMA Distance)
- **Function**: Advanced trend confirmation using Kalman filter algorithm
- **Parameters**:
- Process Noise: 0.35 (controls smoothness)
- Measurement Noise: 24 (controls reactivity)
- Filter Order: 6 (higher = more smoothing)
- ATR Length: 8 (for bandwidth calculation)
- Upper Multiplier: 2.0 (for long signals)
- Lower Multiplier: 2.7 (for short signals)
- Multi-timeframe support
- Customizable visual indicators
- **Implementation**: Generates signals based on price position relative to Kalman-filtered EMA bands
## Risk Management System
### Position Sizing
Automatically calculates position size based on account equity and risk parameters:
| Setting | Default Value |
|---------|---------------|
| **Risk % of Equity** | 50% |
- **Implementation**:
- Position size = (Account equity × Risk %) ÷ (Entry price × Stop loss distance)
- Adjusts automatically based on volatility and stop placement
- **Best Practices**:
- Start with lower risk percentages (1-2%) until strategy is proven
- Consider reducing risk during high volatility periods
### Stop-Loss Methods
Multiple stop-loss calculation methods with separate configurations for long and short positions:
| Method | Description | Configuration |
|--------|-------------|---------------|
| **ATR-Based** | Dynamic stops based on volatility | ATR Period: 14, Multiplier: 2.0 |
| **Percentage** | Fixed percentage from entry | Long: 1.5%, Short: 1.5% |
| **PIP-Based** | Fixed currency unit distance | 10.0 pips |
- **Implementation Notes**:
- ATR-based stops adapt to changing market volatility
- Percentage stops maintain consistent risk exposure
- PIP-based stops provide precise control in stable markets
### Trailing Stops
Locks in profits by adjusting stop-loss levels as price moves favorably:
| Setting | Default Value |
|---------|---------------|
| **Stop-Loss %** | 1.5% |
| **Activation Threshold** | 2.1% |
| **Trailing Distance** | 1.4% |
- **Implementation**:
- Initial stop remains fixed until profit reaches activation threshold
- Once activated, stop follows price at specified distance
- Locks in profit while allowing room for normal price fluctuations
### Risk-Reward Parameters
Defines the relationship between risk and potential reward:
| Setting | Default Value |
|---------|---------------|
| **Risk-Reward Ratio** | 1.4 |
| **Take Profit %** | 2.4% |
| **Stop-Loss %** | 1.5% |
- **Implementation**:
- Take profit distance = Stop loss distance × Risk-reward ratio
- Higher ratios require fewer winning trades for profitability
- Lower ratios increase win rate but reduce average profit
### Filter Combinations
The strategy allows for simultaneous application of multiple filters:
- **Recommended Combinations**:
- Trending markets: RSI + KEMAD filters
- Ranging markets: Bollinger Bands + Volatility filters
- All markets: Volume filter as minimum requirement
- **Performance Impact**:
- Each additional filter reduces the number of trades
- Quality of remaining trades typically improves
- Optimal combination depends on market conditions and timeframe
### Multi-Timeframe Filter Applications
| Filter Type | Current Timeframe | MTF1 (15min) | MTF2 (4h) |
|-------------|-------------------|-------------|------------|
| RSI | Quick entries/exits | Intraday trend | Overall trend |
| Volume | Immediate liquidity | Sustained support | Market participation |
| Volatility | Entry timing | Short-term risk | Regime changes |
| KEMAD | Precise signals | Trend confirmation | Major reversals |
## Visual Indicators and Chart Analysis
The bot provides comprehensive visual feedback on the chart:
- **Channel Bands**: Keltner or MLMA bands showing potential support/resistance
- **Pivot SuperTrend**: Colored line showing trend direction and potential reversal points
- **Entry/Exit Markers**: Annotations showing actual trade entries and exits
- **Risk/Reward Zones**: Visual representation of stop-loss and take-profit levels
These visual elements allow for:
- Real-time strategy assessment
- Post-trade analysis and optimization
- Educational understanding of the strategy logic
## Implementation Guide
### TradingView Setup
1. Load the script in TradingView Pine Editor
2. Apply to your preferred chart and timeframe
3. Adjust parameters based on your trading preferences
4. Enable alerts for webhook integration
### Webhook Integration
1. Configure webhook URL in TradingView alerts
2. Set up receiving endpoint on your trading platform
3. Define message format matching the bot's output
4. Test with small position sizes before full deployment
### Optimization Process
1. Backtest across different market conditions
2. Identify parameter sensitivity through multiple tests
3. Focus on risk management parameters first
4. Fine-tune entry/exit conditions based on performance metrics
5. Validate with out-of-sample testing
## Performance Considerations
### Strengths
- Adaptability to different market conditions through dual channels
- Multiple layers of confirmation reducing false signals
- Comprehensive risk management protecting capital
- Machine learning integration for predictive edge
### Limitations
- Complex parameter set requiring careful optimization
- Potential over-optimization risk with so many variables
- Computational intensity of MLMA calculations
- Dependency on proper webhook configuration for execution
### Best Practices
- Start with conservative risk settings (1-2% of equity)
- Test thoroughly in demo environment before live trading
- Monitor performance regularly and adjust parameters
- Consider market regime changes when evaluating results
## Conclusion
The ₿ober XM v2.0 represents a significant evolution in trading strategy design, combining traditional technical analysis with machine learning elements and multi-timeframe analysis. The core strength of this system lies in its adaptability and recognition of market asymmetry.
### Market Asymmetry and Adaptive Approach
The strategy acknowledges a fundamental truth about markets: bullish and bearish phases behave differently and should be treated as distinct environments. The dual-channel system with separate parameters for long and short positions directly addresses this asymmetry, allowing for optimized performance regardless of market direction.
### Targeted Backtesting Philosophy
It's counterproductive to run backtests over excessively long periods. Markets evolve continuously, and strategies that worked in previous market regimes may be ineffective in current conditions. Instead:
- Test specific market phases separately (bull markets, bear markets, range-bound periods)
- Regularly re-optimize parameters as market conditions change
- Focus on recent performance with higher weight than historical results
- Test across multiple timeframes to ensure robustness
### Multi-Timeframe Analysis as a Game-Changer
The integration of multi-timeframe analysis fundamentally transforms the strategy's effectiveness:
- **Increased Safety**: Higher timeframe confirmations reduce false signals and improve trade quality
- **Context Awareness**: Decisions made with awareness of larger trends reduce adverse entries
- **Adaptable Precision**: Apply strict filters on lower timeframes while maintaining awareness of broader conditions
- **Reduced Noise**: Higher timeframe data naturally filters market noise that can trigger poor entries
The ₿ober XM v2.0 provides traders with a framework that acknowledges market complexity while offering practical tools to navigate it. With proper setup, realistic expectations, and attention to changing market conditions, it delivers a sophisticated approach to systematic trading that can be continuously refined and optimized.
Alpha Trigger CoreAlpha Trigger Core — Trend Momentum Strategy with Dual Take Profit System
Alpha Trigger Core is a precision-engineered trend-following strategy developed for crypto and altcoin markets. Unlike simple indicator mashups, this system was built from the ground up with a specific logic framework that integrates trend, momentum, volatility, and structure validation into a single unified strategy.
It is not a random combination of indicators, but rather a coordinated system of filters that work together to increase signal quality and minimize false positives. This makes it especially effective on trending assets like BTC, ETH, AVAX, and SOL on the 1-hour chart.
🔍 How It Works
This strategy fuses multiple advanced filters into a cohesive signal engine:
🔹 Trend Identification
A hybrid model combining:
Kalman Filter — Smooths price noise with predictive tracking.
SuperTrend Overlay — Confirms directional bias using ATR.
ZLEMA Envelope — Defines dynamic upper/lower bounds based on price velocity.
🔹 Momentum Filter
Uses a ZLEMA-smoothed CCI to identify accelerating moves.
Long entries require a rising 3-bar CCI sequence.
Short entries require a falling 3-bar CCI sequence.
🔹 Volatility Strength Filter (Vortex Indicator)
Validates entries only when Vortex Diff exceeds a customizable threshold.
Prevents low-volatility "chop zone" trades.
🔹 Wick Trap Filter
Filters out false breakouts driven by liquidity wicks.
Validates that body structure supports the breakout.
📈 Entry & Exit Logic
Long Entry: All trend, momentum, volatility filters must align bullishly and wick traps must be absent.
Short Entry: All filters must align bearishly, with no wick rejection.
Early Exit: Uses ZLEMA slope crossover to exit before a full trend reversal is confirmed.
🎯 Take Profit System
TP1: Takes 50% profit at a user-defined % target.
TP2: Closes remaining 100% at second target.
Cooldown: Prevents immediate reentry and ensures clean position transitions.
📊 Real-Time Strategy Dashboard
Tracks and displays:
Position status (Long, Short, Flat)
Entry Price
TP1/TP2 Hit status
Win Rate (%)
Profit Factor
Bars Since Entry
Fully customizable position & font size
🤖 Bot-Ready Multi-Exchange Alerts
Compatible with WonderTrading, 3Commas, Binance, Bybit, and more.
Customizable comment= tags for entry, exit, TP1, and TP2.
Fully alert-compatible for webhook integrations.
📌 Suggested Use
Best used on trending crypto pairs with moderate-to-high volatility. Recommended on the 1H timeframe for altcoins and majors. Can be used for manual confirmation or automated trading.
🔒 Script Transparency
This is a closed-source script. However, the description above provides a transparent breakdown of the strategy’s core logic, filters, and execution model — ensuring compliance with TradingView’s publishing guidelines.
⚠️ Trading Disclaimer
This script is for educational purposes only and is not financial advice. Always conduct your own analysis before making investment decisions. Past performance does not guarantee future results. Use this strategy at your own risk.
AI Volume StrategyAI Volume Strategy detects significant volume spikes and combines them with trend direction and candlestick color to generate buy and sell signals. The strategy uses an Exponential Moving Average (EMA) of volume to identify abnormal volume spikes that may indicate strong market activity. Additionally, it uses a 50-period EMA of price to filter the trend and decide on entry direction.
Key Features:
Volume Spike Detection: The strategy detects when the current volume exceeds the EMA of volume by a user-defined multiplier, signaling abnormal increases in market activity.
Trend Direction Filter: The strategy uses a 50-period EMA of price to determine the market trend. Buy signals are generated when the price is above the EMA (uptrend), and sell signals are generated when the price is below the EMA (downtrend).
Candle Color Filter: The strategy generates a buy signal only when the current candle is bullish (green) and a sell signal only when the current candle is bearish (red).
Exit after X Bars: The strategy automatically closes the position after a specified number of bars (default is 5 bars), but the exit condition can be adjusted based on user preference, timeframe, and backtesting results. The default exit is after 5 bars, but users can set it to 1 bar or any other number depending on their preferences and strategy.
Signals:
Buy Signal: Generated when a volume spike occurs, the trend is upward, and the current candle is bullish.
Sell Signal: Generated when a volume spike occurs, the trend is downward, and the current candle is bearish.
Alerts:
Buy Alert: Alerts the user when a buy signal is triggered.
Sell Alert: Alerts the user when a sell signal is triggered.
Visualization:
Buy Signal: A green label appears below the bar when the buy conditions are met.
Sell Signal: A red label appears above the bar when the sell conditions are met.
Volume EMA: Optionally, the Volume EMA line can be plotted on the chart to visualize volume trends.
This strategy helps traders identify potential entry points based on increased volume activity while considering trend direction and candlestick patterns. With the ability to adjust the exit condition, users can fine-tune the strategy to their specific needs and backtest results.
02 SMC + BB Breakout (Improved)This strategy combines Smart Money Concepts (SMC) with Bollinger Band breakouts to identify potential trading opportunities. SMC focuses on identifying key price levels and market structure shifts, while Bollinger Bands help pinpoint overbought/oversold conditions and potential breakout points. The strategy also incorporates higher timeframe trend confirmation to filter out trades that go against the prevailing trend.
Key Components:
Bollinger Bands:
Calculated using a Simple Moving Average (SMA) of the closing price and a standard deviation multiplier.
The strategy uses the upper and lower bands to identify potential breakout points.
The SMA (basis) acts as a centerline and potential support/resistance level.
The fill between the upper and lower bands can be toggled by the user.
Higher Timeframe Trend Confirmation:
The strategy allows for optional confirmation of the current trend using a higher timeframe (e.g., daily).
It calculates the SMA of the higher timeframe's closing prices.
A bullish trend is confirmed if the higher timeframe's closing price is above its SMA.
This helps filter out trades that go against the prevailing long-term trend.
Smart Money Concepts (SMC):
Order Blocks:
Simplified as recent price clusters, identified by the highest high and lowest low over a specified lookback period.
These levels are considered potential areas of support or resistance.
Liquidity Zones (Swing Highs/Lows):
Identified by recent swing highs and lows, indicating areas where liquidity may be present.
The Swing highs and lows are calculated based on user defined lookback periods.
Market Structure Shift (MSS):
Identifies potential changes in market structure.
A bullish MSS occurs when the closing price breaks above a previous swing high.
A bearish MSS occurs when the closing price breaks below a previous swing low.
The swing high and low values used for the MSS are calculated based on the user defined swing length.
Entry Conditions:
Long Entry:
The closing price crosses above the upper Bollinger Band.
If higher timeframe confirmation is enabled, the higher timeframe trend must be bullish.
A bullish MSS must have occurred.
Short Entry:
The closing price crosses below the lower Bollinger Band.
If higher timeframe confirmation is enabled, the higher timeframe trend must be bearish.
A bearish MSS must have occurred.
Exit Conditions:
Long Exit:
The closing price crosses below the Bollinger Band basis.
Or the Closing price falls below 99% of the order block low.
Short Exit:
The closing price crosses above the Bollinger Band basis.
Or the closing price rises above 101% of the order block high.
Position Sizing:
The strategy calculates the position size based on a fixed percentage (5%) of the strategy's equity.
This helps manage risk by limiting the potential loss per trade.
Visualizations:
Bollinger Bands (upper, lower, and basis) are plotted on the chart.
SMC elements (order blocks, swing highs/lows) are plotted as lines, with user-adjustable visibility.
Entry and exit signals are plotted as shapes on the chart.
The Bollinger band fill opacity is adjustable by the user.
Trading Logic:
The strategy aims to capitalize on Bollinger Band breakouts that are confirmed by SMC signals and higher timeframe trend. It looks for breakouts that align with potential market structure shifts and key price levels (order blocks, swing highs/lows). The higher timeframe filter helps avoid trades that go against the overall trend.
In essence, the strategy attempts to identify high-probability breakout trades by combining momentum (Bollinger Bands) with structural analysis (SMC) and trend confirmation.
Key User-Adjustable Parameters:
Bollinger Bands Length
Standard Deviation Multiplier
Higher Timeframe
Higher Timeframe Confirmation (on/off)
SMC Elements Visibility (on/off)
Order block lookback length.
Swing lookback length.
Bollinger band fill opacity.
This detailed description should provide a comprehensive understanding of the strategy's logic and components.
***DISCLAIMER: This strategy is for educational purposes only. It is not financial advice. Past performance is not indicative of future results. Use at your own risk. Always perform thorough backtesting and forward testing before using any strategy in live trading.***
