ICT Judas Swing | Flux Charts💎 GENERAL OVERVIEW
Introducing our new ICT Judas Swing Indicator! This indicator is built around the ICT's "Judas Swing" strategy. The strategy looks for a liquidity grab around NY 9:30 session and a Fair Value Gap for entry confirmation. For more information about the process, check the "HOW DOES IT WORK" section.
Features of the new ICT Judas Swing :
Implementation of ICT's Judas Swing Strategy
2 Different TP / SL Methods
Customizable Execution Settings
Customizable Backtesting Dashboard
Alerts for Buy, Sell, TP & SL Signals
📌 HOW DOES IT WORK ?
The strategy begins by identifying the New York session from 9:30 to 9:45 and marking recent liquidity zones. These liquidity zones are determined by locating high and low pivot points: buyside liquidity zones are identified using high pivots that haven't been invalidated, while sellside liquidity zones are found using low pivots. A break of either buyside or sellside liquidity must occur during the 9:30-9:45 session, which is interpreted as a liquidity grab by smart money. The strategy assumes that after this liquidity grab, the price will reverse and move in the opposite direction. For entry confirmation, a fair value gap (FVG) in the opposite direction of the liquidity grab is required. A buyside liquidity grab calls for a bearish FVG, while a sellside grab requires a bullish FVG. Based on the type of FVG—bullish for buys and bearish for sells—the indicator will then generate a Buy or Sell signal.
After the Buy or Sell signal, the indicator immediately draws the take-profit (TP) and stop-loss (SL) targets. The indicator has three different TP & SL modes, explained in the "Settings" section of this write-up.
You can set up alerts for entry and TP & SL signals, and also check the current performance of the indicator and adjust the settings accordingly to the current ticker using the backtesting dashboard.
🚩 UNIQUENESS
This indicator is an all-in-one suit for the ICT's Judas Swing concept. It's capable of plotting the strategy, giving signals, a backtesting dashboard and alerts feature. Different and customizable algorithm modes will help the trader fine-tune the indicator for the asset they are currently trading. Three different TP / SL modes are available to suit your needs. The backtesting dashboard allows you to see how your settings perform in the current ticker. You can also set up alerts to get informed when the strategy is executable for different tickers.
⚙️ SETTINGS
1. General Configuration
Swing Length -> The swing length for pivot detection. Higher settings will result in
FVG Detection Sensitivity -> You may select between Low, Normal, High or Extreme FVG detection sensitivity. This will essentially determine the size of the spotted FVGs, with lower sensitivies resulting in spotting bigger FVGs, and higher sensitivies resulting in spotting all sizes of FVGs.
2. TP / SL
TP / SL Method ->
a) Dynamic: The TP / SL zones will be auto-determined by the algorithm based on the Average True Range (ATR) of the current ticker.
b) Fixed : You can adjust the exact TP / SL ratios from the settings below.
Dynamic Risk -> The risk you're willing to take if "Dynamic" TP / SL Method is selected. Higher risk usually means a better winrate at the cost of losing more if the strategy fails. This setting is has a crucial effect on the performance of the indicator, as different tickers may have different volatility so the indicator may have increased performance when this setting is correctly adjusted.
在腳本中搜尋"Buy sell"
Buyside/Sellside Liquidity [Real-Time] (Expo)█ Overview
Buyside/Sellside Liquidity (Expo) is an indicator that identifies buy-side and sell-side liquidity in real time. Buy-side liquidity represents a level on the chart where short sellers will have their stops positioned. Sell-side liquidity represents a level on the chart where long-buyers will place their stops. These levels are found in areas where traders are "proven wrong" and, therefore, want to get out of their trades. Smart money will accumulate or distribute positions near these levels where many stops are placed and absorb all provided liquidity.
█ What is Buy-side and Sell-side liquidity?
Liquidity is the ability of a market to absorb large orders without significantly affecting the asset's price. Buy-side liquidity refers to the ability of buyers to buy large amounts of contracts without significantly affecting the price. Sell-side liquidity refers to the ability of sellers to sell large amounts of contracts without significantly affecting the price. This type of liquidity is important for large institutional investors, such as hedge funds and investment banks, who need to buy/sell large amounts of contracts without significantly affecting the price.
█ How to use
The price will always seek liquidity to either reverse or continue in the current move.
Reversals
Reversals are common around these levels since many traders are forced to close their positions, pushing the price in the other direction. Look for price actions that confirm a reversal around those levels.
Continuations
Liquidity is also a must for a trend to continue. If the price pushes through the liquidity levels and the current order flow structure is intact, traders should look for a continuation setup.
Inducement
Inducement is the act where smart money manipulates the price to access liquidity. Buy-side and Sell-side liquidity levels can be used to identify potential areas of inducement.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Accumulated Net ValueThe Concept:
Accumulated Net Value (ANV) is an indicator that gauges buying/selling strength by looking at whether the closing price is closer to the high or the low. It’s like a tug of war - if buyers are more dominant, then the closing price should be closer to the high; and if sellers are more dominant, then the closing price should be closer to the low.
Additional adjustments are implemented to address price gaps. The indicator first compares the high and low of the current bar with the previous bar, and then use the higher high/lower low among the current and previous bars to calculate the distance from the closing price.
Price is only part of the equation. We know that volume is also an important factor when considering the strength of buyers and sellers. The ANV indicator takes volume into account by multiplying volume with the difference between the closing price and the high or low (depending on which one is more dominant). This generates the ANV for one bar, where such one-bar ANV will have a positive value during buyer-dominant conditions, and a negative value during seller-dominant conditions.
Since ANV for only one bar can be quite choppy, this indicator further adds the ANV of N bars together to get the final ANV signal, and then applies a simple moving average (SMA) to it.
The Variables:
This indicator has two inputs: (1) N bars of Accumulation, and (2) SMA Length.
N bars of Accumulation determines how many bars of ANV values are added together. SMA Length determines the length of SMA applied to the final ANV.
For daily charts, I use “5” or “10” for N bars of accumulation and “20” for SMA length.
For weekly charts, I use “4” for N bars of accumulation and “10” for SMA length.
The user will have to do some testing to see which numbers suit their needs. Smaller values are more sensitive and move faster, but show more choppiness and false signals. Larger values tend to be more reliable, but are slow to react to price movements.
The Signals:
Trading signals can be generated by comparing the ANV with either the SMA or the zero line:
- ANV above SMA: bullish;
- ANV below SMA: bearish;
- ANV above zero: bullish;
- ANV below zero: bearish.
Given that SMA signals are generally triggered earlier than the zero line signals, aggressive traders can trade based on the SMA line, while more conservative traders can trade based on the zero line (i.e., waiting for ANV to turn positive or negative).
Whale Trading SystemThis script is an advanced version of the distributional blocks script.
In distributional buys and sells:
I used a high - low cloud filter, which makes it more prudent to sell the next sell higher for sells and to buy the next purchase lower for buys.
I also used the Stochastic Money Flow Index function because it also uses volume to separate regions.
The long period is 52 weeks, which is equal to one year,
The short period is one-fourth of its value, which is equal to a financial quarter.
Then the values calculated with these periods are calculated by stochastic - rsi logic within the function, giving us two averages and separating the regions according to crossovers and crossunders .
In buys and sales, the higher your next distributional position size makes your profit more .
In the old system, there was a confusion as it was not divided into zones.
Because we divide into zones here, zone changes are the last stop to free up existing positions, and you must reopen each time you change zones.
And I changed standard distribution days, depending on the price change and the histogram, as StochMFI also took into account the volume.
In this way, there is sustainability.
I am also sharing my educational idea that explains the logic of this system in more detail :
Now that we have been divided into regions, a maximum of 10 pieces will suffice us.
And the regional shifts will allow us to sell and buy all of our position size, and now we will feel much more comfortable.
The most timeframe I find most accurate are the weekly bars.
Even in the example, we see how we have benefited from the sharp drop in bitcoin, while the price is falling, and we have lowered the average with higher-weight purchases than the previous one.
In both buys and sales here, both the histogram intensities and the average of the purchases you have reduced with the transactions, or the earnings you have increased with the sales, guide you.
In areas with high volatility ,if we adjust our positions properly, even if we follow the changes in the region, we will get rid of those situations with few wounds and we will surely catch the trend!
NOTE : Crossover/crossunder and distributional buy/sell alerts added.
Best regards , Noldo.
Power Trader Study The Power Trader is an indicator based around the Balance of Power Oscillator. Balance of Power is a price-based measurement that evaluates and compares the strength of buyers and sellers by assessing their respective abilities to push prices to extreme points(both extreme highs and extreme lows).
BoP values fluctuate between a maximum value of 100 and a minimum value of -100. When the BoP value is greater than 0, it indicates that buying pressure is greater than selling pressure. Conversely, negative BoP readings mean that selling pressure is greater than buying pressure.
The exponential moving average of Balance of Power values is displayed as a gray line on the chart. The upper red line represents the upper bound at which a security is considered overbought. The lower green line represents the threshold where we start to consider a security to be in an oversold state.
When the gray BoP EMA line crosses below the lower green line, it changes color to green then changes back to gray once it crosses back above that lower threshold. Similarly, the line turns red when it crosses above the upper red line.
When the EMA line is between the upper and lower bounds, it signifies that there is no significant difference between the power of buyers versus the power of sellers. The top red area indicates that the amount of buying pressure is relatively high. The lower green area means that selling pressure is abnormally high.
When the BoP line falls between the red and green areas, do not take action. When the BoP line turns green and is inside the green area, enter a long position. When the BoP line rises above the red line and into the upper red area, exit the long position.
Entry signals are displayed as vertical green lines that extend the length of the chart. Exit signals are represented by the same lines, except in red.
Users can decide the order of signals in the input option menu through the ‘allow repeat signals’ parameter. If this is set to false, the study will generate signals in the logical chronologic order of . If it is set to true, then signals will be generated as they come, regardless of whether the last signal was its inverse. This means that it could generate sequences like this for example .
Additionally, the stop and limit can also be set in the input menu through the ‘stop’ and ‘limit’ options. This input option accepts parameters of type float (ie: numbers that contain decimals).
The 'Upper Bound for BoP Values' and 'Lower Bound for BoP Values' input options gives traders the option to adjust the upper and lower thresholds for buy and sell signals. It is important to note that setting the upper bound higher or the lower bound lower will result in less frequent signals (and vice versa).
When it is time to enter a long position, an alert with the following message is sent “Power Trader - High Sell Pressure, Enter Long”.
When it is time to exit a long position, an alert with the following message is sent “Power Trader - High Buy Pressure, Exit Long”.
The Power Trader, along with all of our other invite-only scripts, can be found on our website:
profitprogrammers.com
Institutional Dominance/Trapped Trader Profile @MaxMaserati 3.0📊 Institutional Dominance & Trapped Trader Delta Profile
@MaxMaserati 3.0
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🎯 OVERVIEW
The IDT Auction Profile is a professional-grade volume order flow analysis tool that reveals where institutional traders hold Positional Advantage and where retail participants are Trapped. Unlike traditional Volume Profile indicators, the IDT Profile integrates Volume Point Delta (VPD) analysis with advanced pattern recognition to identify the exact price levels where profitable institutional positions create support/resistance, and where losing positions are forced to exit.
This indicator answers the critical questions: Who is in profit? Who is trapped? And where will they defend or exit their positions?
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✨ FEATURES
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⚡ Quick Presets - One-click configuration for:
• Scalper (1m-5m): 75 bars, 50 rows, ★3 confluence
• Day Trader (15m-1h): 150 bars, 60 rows, ★3 confluence
• Swing Trader (4h-D): 300 bars, 80 rows, ★4 confluence
🔔 Price Alerts - Get notified when price touches:
• VAH (Value Area High) - Resistance zone
• VAL (Value Area Low) - Support zone
• Adjustable sensitivity (0.05% - 1.0%)
📏 POC Line Extensions - Historical context lines extending left from key institutional levels
👻 Previous Session POCs - Dotted reference lines showing prior period levels (carry-over zones)
📊 Real-Time Statistics Panel:
• Total Volume
• Net Delta
• Buy/Sell Pressure %
🎨 Visual Enhancements:
• Column dividers for clarity
• Transparency controls
• Profile auto-hide when price moves away
• Cached color schemes for 30% performance boost
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🧠 CORE CONCEPT: DOMINANCE VS TRAPPED POSITIONING
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The indicator categorizes all market participants into two strategic positions based on their entry price relative to current market price:
📍 ABOVE CURRENT PRICE (Resistance Zones)
🔴 Aggressive Sellers in Profit - Sold higher, currently winning. Will defend positions or add to winners.
🟥 Trapped Buyers at Loss - Bought higher, currently losing. Must exit at breakeven, creating resistance.
📍 BELOW CURRENT PRICE (Support Zones)
🟢 Aggressive Buyers in Profit - Bought lower, currently winning. Will defend positions or add to winners.
🟩 Trapped Sellers at Loss - Sold lower, currently losing. Must cover at breakeven, creating support.
⚡ MAXIMUM CONFLUENCE ZONES
When Dominant (Profitable) and Trapped (Loss) positions align at the same level, you get the strongest support/resistance zones:
🟧 Orange Boxes (Above Price) = Aggressive Sellers + Trapped Buyers = STRONGEST RESISTANCE
🟨 Yellow Boxes (Below Price) = Aggressive Buyers + Trapped Sellers = STRONGEST SUPPORT
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📊 VOLUME ANALYSIS COLUMNS
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1️⃣ VPD Column (Volume Point Delta)
Net aggressive pressure at each price level (Buying Volume - Selling Volume)
- Bullish Delta (Green): Buyers dominated the auction at this level
- Bearish Delta (Red): Sellers dominated the auction at this level
- Smart Coloring: Automatically highlights institutional patterns
2️⃣ VPS Column (Volume Point of Sell - ASK Volume)
Aggressive buying volume that "lifted the offer" by hitting ask prices
- Represents participants who paid the ask price to enter long
- When price is below this level = These buyers are in profit
- When price is above this level = These sellers who got hit are in profit
- Shows institutional bid volume absorption
3️⃣ VPB Column (Volume Point of Buy - BID Volume)
Aggressive selling volume that "hit the bid" by taking bid prices
- Represents participants who sold at bid price to enter short
- When price is above this level = These sellers are in profit
- When price is below this level = These buyers who got hit are in profit
- Shows institutional ask volume absorption
4️⃣ SVP Column (Optional - Session Volume Profile)
Traditional combined volume profile without bid/ask separation
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🔍 ADVANCED INSTITUTIONAL PATTERNS DETECTION
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The indicator uses statistical analysis (standard deviation, moving averages, hit counting) to identify institutional footprints:
⚡ Failed Auctions - "BUYERS TRAPPED" or "SELLERS TRAPPED" labels
• High volume entered, but price immediately reversed
• Creates extreme concentrations of losing positions
• Trading Implication: High-probability reversal zones where trapped participants must exit
📈 Volume Spikes - Bright green/red bars in VPD column
• Volume exceeds average by 2+ standard deviations
• Represents aggressive institutional entry
• Trading Implication: Potential trend continuation or setup for failed auction
🛡️ Absorption Zones - Yellow/Orange colored bars
• Large passive orders absorbing aggressive volume without price movement
• Indicates accumulation (bullish) or distribution (bearish)
• Trading Implication: Institutional positioning before major moves
🧊 Iceberg Orders - Cyan colored bars with high hit counts
• Same price level shows repeated volume without clearing
• Reveals hidden institutional limit orders split into small pieces
• Trading Implication: Strong liquidity magnets, price often returns here
💜 Volume Exhaustion - Purple colored bars
• Sharp volume drop (50%+) after spike
• Momentum exhausted, participants depleted
• Trading Implication: Potential reversal or consolidation ahead
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🎨 SMART INSTITUTIONAL COLORING
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Colors bars based on detected patterns vs simple red/green:
🟨 Yellow = Bullish battles won (buyers + trapped sellers)
🟧 Orange = Bearish battles won (sellers + trapped buyers)
🔵 Cyan = Iceberg orders (hidden liquidity)
🟣 Purple = Large passive orders
🟢 Bright Green = Buying spikes (institutional aggression)
🔴 Bright Red = Selling spikes (institutional aggression)
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⭐ CONFLUENCE SCORING SYSTEM
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Each price level receives 1-5 stars based on:
★★ Volume spike presence (+2 stars)
★ Absorption pattern (+1 star)
★ Large passive orders (+1 star)
★ Proximity to Value Area (+1 star)
★★ Iceberg detection (+2 stars)
★★ Failed auction (+2 stars)
Minimum Signal Strength filter lets you show only levels with ★3+ confluence for highest-quality signals.
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🎯 VALUE AREA ANALYSIS
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VAH (Value Area High) - Blue Line
- Top of the 70% volume acceptance zone
- Price at VAH often rejects downward (resistance)
- Alert triggers when price approaches
VAL (Value Area Low) - Red Line
- Bottom of the 70% volume acceptance zone
- Price at VAL often bounces upward (support)
- Alert triggers when price approaches
Trading Applications:
- Price outside Value Area → Mean reversion opportunity
- Price breaks VA with volume → Trend continuation
- Price oscillates within VA → Range-bound, fade extremes
- Previous session VA lines show carryover levels
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📋 EXPECTED PRICE BEHAVIOR AT KEY LEVELS
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⚠️ IMPORTANT: These are observed behavioral patterns for educational purposes and backtesting research. Always validate with 250-500+ backtest trades before risking capital.
1️⃣ POC BOX ZONES (Highest Statistical Relevance)
🟨 Yellow Boxes (Below Current Price - SUPPORT)
Expected Behavior:
- Price approaching from above typically encounters buying pressure
- Both profitable institutional buyers and trapped short sellers create demand
- Common reaction: Price slows, consolidates, or bounces
- Failed bounces often lead to rapid breakdown (trapped buyers capitulate)
What Often Happens:
- Initial dip into zone → Weak bounce attempt
- Second test → Stronger bounce (trapped sellers covering + buyers defending)
- Break below → Quick acceleration as both groups exit
🟧 Orange Boxes (Above Current Price - RESISTANCE)
Expected Behavior:
- Price rallying into zone typically encounters selling pressure
- Both profitable institutional sellers and trapped long buyers create supply
- Common reaction: Price stalls, consolidates, or rejects
What Often Happens:
- Initial push into zone → Weak rejection
- Second test → Stronger rejection (trapped buyers exiting + sellers defending)
- Break above → Quick acceleration as resistance becomes support
2️⃣ FAILED AUCTION ZONES
"SELLERS TRAPPED" Labels (Below Price):
- High-volume selling that immediately reversed = maximum trapped shorts
- When price returns, trapped sellers face pressure to cover
- Typical pattern: Price approaches → Initial hesitation → Sharp bounce
"BUYERS TRAPPED" Labels (Above Price):
- High-volume buying that immediately failed = maximum trapped longs
- Price returning forces trapped buyers to exit at breakeven
- Typical pattern: Price approaches → Distribution → Rejection
3️⃣ VALUE AREA DYNAMICS
Price Outside Value Area (VAH/VAL):
- Price beyond 70% volume zone = statistical outlier
- Two outcomes: Mean reversion OR trend continuation
- Key differentiator: Presence of confluence zones
Mean Reversion Pattern (No Strong Confluence):
- Price extends 1-2% beyond VA → Typically reverts toward POC
- Weak volume on extension → Higher probability of reversal
Breakout Pattern (With ★4+ Confluence):
- Price breaks VA with institutional patterns → Often continues
- Strong volume + confluence = New value area forming
4️⃣ ICEBERG ORDER BEHAVIOR
Cyan Bars with High Hit Counts:
- Repeated volume at same level = Large hidden order absorbing
- Price typically "tests" iceberg multiple times before resolution
- Two outcomes: Absorption complete (break) OR rejection (bounce)
5️⃣ VOLUME SPIKE PATTERNS
Bright Green/Red Bars (Institutional Aggression):
- Extreme delta spikes indicate institutional entry
- Trend Continuation Spikes: Spike aligned with trend = Often continues
- Exhaustion Spikes: Spike against trend = Failed auction forming
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⚙️ CONFIGURATION GUIDE
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🎯 QUICK START
1. Select your trading style preset (Scalper/Day/Swing)
2. Enable VAH/VAL alerts in settings
3. Adjust alert sensitivity (0.1% recommended)
4. Add alert condition to TradingView alert system
📊 CORE SETTINGS
- Lookback Period: How many bars to analyze
- Scalping: 50-100 bars
- Day Trading: 100-200 bars
- Swing Trading: 200-500 bars
- Price Row Granularity: How finely to divide price
- 40-50 rows = Fast markets
- 60-80 rows = Balanced (RECOMMENDED)
- 100+ rows = Maximum precision
- Minimum Signal Strength: Filter weak signals
- ★3 = Balanced quality/quantity (RECOMMENDED)
- ★4-5 = Highest quality, fewer opportunities
🎨 VISUAL SETTINGS
- Color Theme: Classic/Institutional/Monochrome/Bold/Minimal/Custom
- Smart Coloring: ON (recommended) - Shows institutional patterns
- Transparency: Adjust profile opacity
- Column Dividers: Visual separators between columns
- POC Extensions: Show historical level significance
📈 ADVANCED FEATURES
- Auto-Hide Distance: Hide profile when price moves X% away
- Statistics Panel: Real-time metrics display
- Previous POCs: Show prior session levels
- Alert Sensitivity: How close price must be to trigger alerts
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💡 BEST PRACTICES
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✅ Start with defaults (200 lookback, 60 rows, ★3 confluence, Smart Coloring ON)
✅ Focus on POC boxes first - These are your highest-probability zones
✅ Combine with price action - Use the profile to explain WHY support/resistance exists
✅ Watch for alignment - Yellow/Orange boxes = strongest levels
✅ Respect failed auctions - "TRAPPED" labels are extreme reversal setups
✅ Use Value Area for context - Price outside VA = mean reversion opportunity
✅ Trust confluence scores - ★4-5 signals are institutional-grade setups
✅ Set up alerts for VAH/VAL touches - Don't miss key levels
✅ Check previous session POCs - Institutions defend same zones across sessions
✅ Monitor statistics panel - Understand market conviction in real-time
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🔧 TECHNICAL SPECIFICATIONS
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Calculation Method: Enhanced delta using OHLC and volume with wick ratio analysis
Update Frequency: Real-time on every bar close
Performance: Optimized with color caching and pre-calculated values (~30% faster)
Max Capacity: Supports up to 1500 bars lookback and 250 price rows
Compatibility: Works on all symbols and timeframes
Memory Usage: Efficient array management with proper initialization
Alert System: Built-in VAH/VAL touch detection with visual markers
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🎯 UNIQUE VALUE PROPOSITION
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Unlike standard Volume Profile indicators that only show where volume occurred, the IDT Auction Profile:
✅ Separates bid vs ask volume to reveal true order flow
✅ Identifies who is profitable vs who is trapped at each level
✅ Detects institutional patterns (icebergs, absorption, failed auctions)
✅ Calculates confluence scores combining multiple factors
✅ Provides clear POC boxes showing exact institutional positioning
✅ Maps positional advantage rather than just volume density
✅ Alerts you to key level touches in real-time
✅ Shows historical context with POC extensions
✅ Displays live statistics for market conviction
This transforms Volume Profile from a historical volume chart into a strategic positioning map showing institutional dominance and trapped participants.
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📖 HOW TO INTEGRATE WITH YOUR STRATEGY
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✅ PROPER USES:
- Entry refinement within your existing setups
- Intelligent stop placement beyond institutional levels
- Objective profit targets at next confluence zones
- Trade filtering (only take setups at ★4+ zones)
- Understanding market positioning before entry
- Alert-based monitoring of key support/resistance levels
❌ WHAT IT CANNOT DO:
- Predict direction with certainty
- Replace risk management
- Account for news/external events
- Guarantee profitability
- Work in all market conditions
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📚 DEVELOPMENT PATH (12-16 Weeks)
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Weeks 1-2: Observation Only
- Watch price behavior at key levels
- Document patterns without trading
- Set up alerts and observe responses
Weeks 3-8: Paper Trading
- Simulate trades, track all metrics
- Minimum 100 paper trades
- Test different confluence thresholds
Weeks 9-16: Small Size Testing
- Minimal capital, real market conditions
- Continue tracking, refine rules
- Adjust alert sensitivity based on results
After Proven Edge you could potentially include it in your set-up
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⚠️ CRITICAL DISCLAIMERS
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⚠️ Past volume ≠ Future price action
⚠️ Institutional positions change rapidly - these are static snapshots
⚠️ No indicator works 100% - risk management is mandatory
⚠️ Market conditions change - adapt your approach
⚠️ Backtest with YOUR style, YOUR timeframe, YOUR risk tolerance
⚠️ Alerts are notifications, not trade signals - you decide the action
The indicator reveals WHERE institutions are positioned and HOW they might behave. YOU decide IF, WHEN, and HOW to trade that information.
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📞 SUPPORT & UPDATES
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For questions, suggestions, or bug reports:
- Comment below the indicator
- Follow for updates and new features
- Check documentation for detailed examples
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Not financial advice. For educational and research purposes only.
FCPO MASTER v6 – Sideway + Breakout + OB + FVG (TUPLE SAFE)TL;DR cepat
1. Gunakan M5 untuk entry & OB/FVG confirmation.
2. Gunakan M15 untuk confirm trend/false breakout.
3. Gunakan H1 untuk bias arah (overall market).
4. Entry hanya bila signal + OB/FVG/candle rejection (script buatkan).
5. SL 5–8 tick, TP 10–25 tick ikut setup (sideway vs breakout).
6. Follow checklist setiap trade — jangan lompat.
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Setup awal (1–2 min)
1. Pasang script FCPO Sideway MASTER – OB + Imbalance + Confirmation di TradingView.
2. Timeframes: buka M5, M15, H1 (susun 3 chart atau 1 chart multi-timeframe).
3. Input default: ATR14, Breakout Buffer 5 tick, RangeLen 20, ADX14, TP12, SL8. (Kau boleh tweak nanti).
4. Aktifkan alerts pada BUY Confirm / SELL Confirm / Sideway Buy / Sideway Sell.
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Step-by-step trading process
1) Mulakan dengan H1 — tentukan bias HTF
• Lihat H1 untuk jawapan: Trend Up / Down / Sideway.
• Rule ringkas:
o ADX H1 > 20 + price above H1 EMA → bias Bull
o ADX H1 > 20 + price below H1 EMA → bias Bear
o ADX H1 < 20 → market HTF sideway (no strong bias)
Kenapa: H1 bagi kau idea “kalau breakout pada M5, patut follow atau tolak”.
________________________________________
2) Pergi ke M15 — confirm trend & valid breakout
• M15 kena setuju dengan idea breakout.
o Untuk strong breakout: M15 kena tunjuk candle close di atas/bawah range + volume naik.
o Kalau M5 breakout tapi M15 tak setuju (M15 masih sideway) → treat as fakeout. Jangan masuk.
________________________________________
3) M5 — cari entry & confirmation (OB/FVG + candle)
• M5 adalah tempat kau buat keputusan masuk.
• Tunggu script keluarkan Sideway Buy/Sell atau Breakout Buy/Sell.
• CONFIRM entry mesti ada sekurang-kurangnya 1 dari:
o Bull/Bear Order Block searah signal (script detect).
o FVG / Imbalance zone dipenuhi & price retest.
o Candle rejection (pinbar / bearish/bullish engulfing) pada zone.
Jika tiada confirmation → no trade.
________________________________________
4) Checklist sebelum tekan Buy/Sell (MUST)
• H1 bias tidak melawan trade (prefer sama arah).
• M15 confirm breakout / trend or neutral.
• Script keluarkan signal (sideway or breakout).
• OB or FVG atau candle rejection ada.
• ATR kenaikan jika breakout (untuk breakout trade).
• Volume spike jika breakout.
• Risk:SL <= 2% akaun (position sizing).
Kalau semua ticked → boleh entry.
________________________________________
5) Setting SL / TP & position sizing
• Sideway (scalp): SL = 5–8 tick, TP = 8–12 tick.
• Breakout (trend): SL = 8–12 tick, TP = 15–25+ tick (trail later).
• Position sizing: Risk per trade 1–2%.
o Lot size = (Account Risk RM × 1 tick value) / (SL ticks × tickValue) — (kalau kau gunakan fixed tick value, adjust ikut lot).
(Script tunjuk SL & TP label — follow itu.)
________________________________________
6) Entry types
• A. Sideway Reversal (M5)
o Signal: Sideway Buy / Sideway Sell
o Confirm: OB/FVG or rejection candle at range bottom/top
o Trade: scalp target 8–12 tick, tight SL 5–8 tick
• B. Breakout (M5 entry, M15 confirm)
o Signal: Breakout Buy/Sell (Strong)
o Confirm: ATR expanding + volume spike + M15 alignment
o Trade: trend follow, TP 15–25 tick, trailing stop active
• C. Retest Entry
o Breakout happens, price returns to retest range / OB / FVG → wait for rejection candle then enter. Safer.
________________________________________
7) Trailing & exit rules
• Jika useTrail = true script plots trailing stop (ATR × multiplier).
• Exit rules:
1. Hit TP → close.
2. Hit SL → close.
3. If trailing stop hit → close.
4. If opposing confirmed signal muncul (e.g., SELL confirm while long) → consider close early.
5. If H1 bias flips strongly vs trade → tighten stop or close.
________________________________________
8) Multiple signals & scaling
• Never add to losing position (no averaging down).
• If want scale-in on confirmed trend: add 1 partial size after price moves +10–12 tick in favor and shows continuation candle + no bearish OB/FVG.
• Keep aggregated risk within your max (2–3%).
________________________________________
9) Example trade walkthrough (concrete)
• RangeHigh = 4065, RangeLow = 4035 (contoh).
• Market sideway M5.
Case A — Sideway Sell:
1. Price touches 4064–4065, script shows sidewaySell.
2. Lihat OB: ada bear OB zone di 4062–4066 → confirm.
3. Candle rejection (bearish pinbar) muncul → enter SELL M5.
4. Set SL = 5 tick above rangeHigh = 4070, TP = 10 tick → 4055.
5. Trail jika price turun > 8 tick: aktifkan trailing.
6. Close at TP or trail/SL.
Case B — Breakout Buy:
1. Price closes above 4065 + 5 tick buffer = 4070 on M5. Script shows trueBreakUp.
2. M15 shows candle close above M15 resistance + volume spike → confirm.
3. Enter BUY, SL = 8 tick below entry, TP initial 20 tick, trail with ATR×1.5.
4. Move stop to breakeven after +10 tick, scale out half at +12 tick, leave rest to trail.
________________________________________
10) Journal & review
• Semua trade: record entry time, TF, reason (which confirmations), SL/TP, result, lesson.
• Weekly review: check which confirmation worked best (OB vs FVG vs candle) and tweak settings.
________________________________________
11) Tweaks / optimisations cepat
• Jika terlalu banyak false sideway signals → kurangkan touchDist ke 2 tick.
• Kalau fakeout breakout banyak → tambah tickBuf ke 6–8.
• Nak lebih konservatif → cuma trade breakout yang juga setuju M15.
________________________________________
12) Alerts & execution (practical)
• Pasang alert pada BUY Confirm / SELL Confirm (script).
• Kalau kau guna broker yang support one-click order, siap sediakan template order (SL/TP default).
• Kalau manual, bila alert masuk: buka M5, cepat confirm OB/FVG & candle rejection → entry.
________________________________________
Quick reference table (handy)
• TF utama entry: M5
• Confirm mid-TF: M15
• Bias HTF: H1
• Sideway SL/TP: SL 5–8, TP 8–12
• Breakout SL/TP: SL 8–12, TP 15–25+
• Mandatory confirmation: (Script signal) + (OB or FVG or candle)
PRO Trade Manager//@version=5
indicator("PRO Trade Manager", shorttitle="PRO Trade Manager", overlay=false)
// ============================================================================
// INPUTS
//This code and all related materials are the exclusive property of Trade Confident LLC. Any reproduction, distribution, modification, or unauthorized use of this code, in whole or in part, is strictly prohibited without the express written consent of Trade Confident LLC. Violations may result in civil and/or criminal penalties to the fullest extent of the law.
// © Trade Confident LLC. All rights reserved.
// ============================================================================
// Moving Average Settings
maLength = input.int(15, "Signal Strength", minval=1, tooltip="Length of the moving average to measure deviation from (lower = more sensitive)")
maType = "SMA" // Fixed to SMA, no longer user-selectable
// Deviation Settings
deviationLength = input.int(20, "Deviation Period", minval=1, tooltip="Lookback period for standard deviation calculation")
// Signal Frequency dropdown - controls both upper and lower thresholds
signalFrequency = input.string("More/Good Accuracy", "Signal Frequency", options= ,
tooltip="Normal/Highest Accuracy = ±2.0 StdDev | More/Good Accuracy = ±1.5 StdDev | Most/Moderate Accuracy = ±1.0 StdDev")
// Set thresholds based on selected frequency
upperThreshold = signalFrequency == "Most/Moderate Accuracy" ? 1.0 : signalFrequency == "More/Good Accuracy" ? 1.5 : 2.0
lowerThreshold = signalFrequency == "Most/Moderate Accuracy" ? -1.0 : signalFrequency == "More/Good Accuracy" ? -1.5 : -2.0
// Continuation Signal Settings
atrMultiplier = input.float(2.0, "TP/DCA Market Breakout Detection", minval=0, step=0.5, tooltip="Number of ATR moves required to trigger continuation signals (Set to 0 to disable)")
// Visual Settings
showMA = false // MA display removed from settings
showSignals = input.bool(true, "Show Alert Signals", tooltip="Show visual signals when price is overextended")
// ============================================================================
// CALCULATIONS
// ============================================================================
// Calculate Moving Average based on type
ma = switch maType
"SMA" => ta.sma(close, maLength)
"EMA" => ta.ema(close, maLength)
"WMA" => ta.wma(close, maLength)
"VWMA" => ta.vwma(close, maLength)
=> ta.sma(close, maLength)
// Calculate deviation from MA
deviation = close - ma
// Calculate standard deviation
stdDev = ta.stdev(close, deviationLength)
// Calculate number of standard deviations away from MA
deviationScore = stdDev != 0 ? deviation / stdDev : 0
// Smooth the deviation score slightly for cleaner signals
smoothedDeviation = ta.ema(deviationScore, 3)
// ============================================================================
// SIGNALS
// ============================================================================
// Overextended conditions
overextendedHigh = smoothedDeviation >= upperThreshold
overextendedLow = smoothedDeviation <= lowerThreshold
// Signal triggers (crossing into overextended territory)
bullishSignal = ta.crossunder(smoothedDeviation, lowerThreshold)
bearishSignal = ta.crossover(smoothedDeviation, upperThreshold)
// Track if we're in bright histogram zones
isBrightGreen = smoothedDeviation <= lowerThreshold
isBrightRed = smoothedDeviation >= upperThreshold
// Track if we were in bright zone on previous bar
wasBrightGreen = smoothedDeviation <= lowerThreshold
wasBrightRed = smoothedDeviation >= upperThreshold
// Detect oscillator turning up after bright green (buy signal)
// Trigger if we were in bright green and oscillator turns up, even if no longer bright green
oscillatorTurningUp = smoothedDeviation > smoothedDeviation
buySignal = barstate.isconfirmed and wasBrightGreen and oscillatorTurningUp and smoothedDeviation <= smoothedDeviation
// Detect oscillator turning down after bright red (sell signal)
// Trigger if we were in bright red and oscillator turns down, even if no longer bright red
oscillatorTurningDown = smoothedDeviation < smoothedDeviation
sellSignal = barstate.isconfirmed and wasBrightRed and oscillatorTurningDown and smoothedDeviation >= smoothedDeviation
// ============================================================================
// ATR-BASED CONTINUATION SIGNALS
// ============================================================================
// Calculate ATR for distance measurement
atrLength = 14
atr = ta.atr(atrLength)
// Track price levels when ANY sell or buy signal occurs (original or continuation)
var float lastSellPrice = na
var float lastBuyPrice = na
// Initialize tracking on original signals
if sellSignal
lastSellPrice := close
if buySignal
lastBuyPrice := close
// Continuation Sell Signal: Price moved up by ATR multiplier from last red dot
// Disabled when atrMultiplier is set to 0
continuationSell = atrMultiplier > 0 and barstate.isconfirmed and not na(lastSellPrice) and close >= lastSellPrice + (atrMultiplier * atr)
// Continuation Buy Signal: Price moved down by ATR multiplier from last green dot
// Disabled when atrMultiplier is set to 0
continuationBuy = atrMultiplier > 0 and barstate.isconfirmed and not na(lastBuyPrice) and close <= lastBuyPrice - (atrMultiplier * atr)
// Update reference prices when continuation signals trigger (reset the 3 ATR counter)
if continuationSell
lastSellPrice := close
if continuationBuy
lastBuyPrice := close
// Combine original and continuation signals for plotting
allBuySignals = buySignal or continuationBuy
allSellSignals = sellSignal or continuationSell
// Track if a signal occurred to keep it visible on dashboard
// Signals trigger at barstate.isconfirmed (bar close)
var bool showBuyOnDashboard = false
var bool showSellOnDashboard = false
// Update dashboard flags immediately when signals occur
if allBuySignals
showBuyOnDashboard := true
showSellOnDashboard := false
else if allSellSignals
showSellOnDashboard := true
showBuyOnDashboard := false
else if barstate.isconfirmed
// Reset flags on bar close if no new signal
showBuyOnDashboard := false
showSellOnDashboard := false
// ============================================================================
// PLOTTING
// ============================================================================
// Professional color scheme
var color colorBullish = #00C853 // Professional green
var color colorBearish = #FF1744 // Professional red
var color colorNeutral = #2962FF // Professional blue
var color colorGrid = #363A45 // Dark gray for lines
var color colorBackground = #1E222D // Chart background
// Dynamic line color based on value
lineColor = smoothedDeviation > upperThreshold ? colorBearish :
smoothedDeviation < lowerThreshold ? colorBullish :
smoothedDeviation > 0 ? color.new(colorBearish, 50) :
color.new(colorBullish, 50)
// Plot the deviation oscillator with dynamic coloring
plot(smoothedDeviation, "Deviation Score", color=lineColor, linewidth=2)
// Plot zero line
hline(0, "Zero Line", color=color.new(colorGrid, 0), linestyle=hline.style_solid, linewidth=1)
// Subtle fill for overextended zones (without visible threshold lines)
upperLine = hline(upperThreshold, "Upper Threshold", color=color.new(color.gray, 100), linestyle=hline.style_dashed, linewidth=1)
lowerLine = hline(lowerThreshold, "Lower Threshold", color=color.new(color.gray, 100), linestyle=hline.style_dashed, linewidth=1)
fill(upperLine, hline(3), color=color.new(colorBearish, 95), title="Overextended High Zone")
fill(lowerLine, hline(-3), color=color.new(colorBullish, 95), title="Overextended Low Zone")
// Histogram style visualization (optional alternative)
histogramColor = smoothedDeviation >= upperThreshold ? color.new(colorBearish, 20) :
smoothedDeviation <= lowerThreshold ? color.new(colorBullish, 20) :
smoothedDeviation > 0 ? color.new(colorBearish, 80) :
color.new(colorBullish, 80)
plot(smoothedDeviation, "Histogram", color=histogramColor, style=plot.style_histogram, linewidth=3)
// ============================================================================
// BUY/SELL SIGNAL MARKERS
// ============================================================================
// Plot buy signals at -3.5 level (includes both initial and extended signals)
plot(allBuySignals ? -3.5 : na, title="Buy Signal", style=plot.style_circles,
color=color.new(colorBullish, 0), linewidth=4)
// Plot sell signals at 3.5 level (includes both initial and extended signals)
plot(allSellSignals ? 3.5 : na, title="Sell Signal", style=plot.style_circles,
color=color.new(colorBearish, 0), linewidth=4)
// ============================================================================
// ALERTS - SIMPLIFIED TO ONLY TWO ALERTS
// ============================================================================
// Alert 1: Long Entry/Short TP - fires on ANY green dot (original or continuation)
alertcondition(allBuySignals, "Long Entry/Short TP", "Long Entry/Short TP")
// Alert 2: Long TP/Short Entry - fires on ANY red dot (original or continuation)
alertcondition(allSellSignals, "Long TP/Short Entry", "Long TP/Short Entry")
// ============================================================================
// DATA DISPLAY
// ============================================================================
// Create a professional table for current readings
var color tableBgColor = #1a2332 // Dark blue background
var table infoTable = table.new(position.middle_right, 2, 2, border_width=1,
border_color=color.new(#2962FF, 30),
frame_width=1,
frame_color=color.new(#2962FF, 30))
if barstate.islast
// Determine status
statusText = overextendedHigh ? "OVEREXTENDED ↓" :
overextendedLow ? "OVEREXTENDED ↑" :
smoothedDeviation > 0 ? "Buyers In Control" : "Sellers In Control"
statusColor = overextendedHigh ? color.new(colorBearish, 0) :
overextendedLow ? color.new(colorBullish, 0) :
color.white
// Background color for status cell
statusBgColor = color.new(tableBgColor, 0)
// Status Row
table.cell(infoTable, 0, 0, "Status",
bgcolor=color.new(tableBgColor, 0),
text_color=color.white,
text_size=size.normal)
table.cell(infoTable, 1, 0, statusText,
bgcolor=statusBgColor,
text_color=statusColor,
text_size=size.normal)
// Signal Row - always show
table.cell(infoTable, 0, 1, "Signal",
bgcolor=color.new(tableBgColor, 0),
text_color=color.white,
text_size=size.normal)
// Show signal if flags are set (will stay visible during the bar)
if showBuyOnDashboard or showSellOnDashboard
// Green dot (buy signal) = "Long Entry/Short TP" with arrow up, white text on green background
// Red dot (sell signal) = "Long TP/Short Entry" with arrow down, white text on red background
signalText = showBuyOnDashboard ? "↑ Long Entry/Short TP" : "↓ Long TP/Short Entry"
signalColor = showBuyOnDashboard ? color.new(colorBullish, 0) : color.new(colorBearish, 0)
table.cell(infoTable, 1, 1, signalText,
bgcolor=signalColor,
text_color=color.white,
text_size=size.normal)
else
table.cell(infoTable, 1, 1, "Watching...",
bgcolor=color.new(tableBgColor, 0),
text_color=color.new(color.white, 60),
text_size=size.normal)
Heatmap.v4-EN [Elykia]// 🚀 Heatmap Pro v4 – Ultimate Order Flow & Scalping
🔎 Description
Heatmap Pro v4 is an Order Flow visualization tool designed for precision scalpers. It transforms raw volume data into a dynamic Heatmap (Bubbles) directly on your chart.
Unlike classic candlesticks that hide internal information, this indicator offers "X-Ray" vision of the market. It allows you to instantly identify:
Where trading is taking place (Liquidity).
Who controls the price (Buyers vs. Sellers).
The intensity of the aggression.
🔥 WHY USE THIS TOOL ON A 1-SECOND CHART?
Trading on a 1-second chart is often considered "noise," but with Heatmap Pro v4, it becomes the ultimate weapon for scalpers on Indices (Nasdaq, ES) and Futures.
1. Surgical Precision: The algorithm slices volume second by second, revealing imbalances invisible on higher timeframes.
2. Immediate Responsiveness: You see "Walls" (Absorption) and "Attacks" (Aggression) forming in real-time, even before a minute candle closes.
3. Preserved Context: Thanks to the HTF Candles function, you trade the second while keeping an eye on the 1-minute or 5-minute structure.
🛠️ KEY FEATURES
1. Dynamic Heatmap (Bubbles)
Size: Proportional to the traded volume (Delta). The bigger the circle, the more contested or liquid the zone is.
Color (Delta):
🟢 Green / Lime: Aggressive buyers dominate.
🔴 Red: Aggressive sellers dominate.
Noise Filter: The "Minimum Volume" option allows you to hide insignificant small volumes to keep only institutional movements.
2. HTF Candles (Context Overlay)
Overlays candles from a higher timeframe (e.g., 1min candle on a 1s chart) in the background. This allows you to always know where you stand in the background trend (Open/Close/Wicks) without switching screens.
3. Smart Synthetic Delta Algorithm
This indicator goes beyond displaying raw volume. It uses a directional classification algorithm with memory, flow continuity, and trend memory to estimate Buyer vs. Seller pressure.
4. Automatic Calibration (Auto-Tuner)
The script automatically detects the asset and adjusts sensitivity (Range Vol) for optimal display on:
Indices: NQ (Nasdaq), ES (S&P 500), YM (Dow Jones)
Futures: GC (Gold), CL (Oil), 6E (Euro)
💡 HOW TO USE IT? (STRATEGY)
The indicator is optimized for very short timeframes (1s, 5s, 15s).
1. Trend Setup: A succession of large green circles pushing the price up = Healthy trend (Buying aggression).
2. Absorption Setup (Reversal): Price rises, but a huge red circle appears at the top. This means passive sellers are absorbing all the buying. If price rejects this level, it's a selling opportunity.
3. Using Context: Only take 1s trades on key zones (high/low) of the HTF candles (1min or 5min) displayed in the background.
⚙️ CONFIGURATION GUIDE
1. Essential Parameters
TF Candle: Choose the background structure timeframe (e.g., "1" to see 1-minute candles).
Range détection volume (pts/ticks): This is the "Zoom" of the Heatmap.
Small value (e.g., 0.25 on ES): To see every fine detail.
Large value (e.g., 2.5 or 5 on NQ): To see large blocking zones and filter noise.
Volume minimum: Increase this value to see only "Whales" (Large Lots).
2. Manual Calibration (Crypto/Forex/Stocks)
If trading an asset not recognized by the Auto-Tuner (e.g., BTCUSD), manually adjust the "Range détection":
Bubbles too small/numerous ➔ Increase the value.
Bubbles too big/rare ➔ Decrease the value.
⚠️ IMPORTANT TECHNICAL NOTE
Data & Subscription:
The precision of the Heatmap depends on the granularity of the underlying data.
Recommended (Premium): To optimize the tool and precisely separate Buy/Sell bubbles, using second-based charts (1s, 5s) via a TradingView Premium subscription is highly recommended.
Standard Use: On minute charts (1m), circles will represent the aggregation of the whole minute, offering less fine resolution than in seconds.
Hidden Volume Profile[52Signal Recipe]─────────────────────────────────────
52SIGNAL RECIPE Hidden Volume Profile
◆ Overview
52SIGNAL RECIPE Smart Volume Profile is an advanced volume distribution indicator that visualizes buying and selling strength across different price levels. Unlike traditional volume profiles that only display total volume, this enhanced version separates buy volume and sell volume at each price level, revealing the hidden balance of market forces at specific prices.
Built on the same sophisticated calculation methodology as our Hidden Volume Detector, this indicator applies enhanced volume analysis to the Volume Profile framework. By displaying horizontal volume bars (green for buying, red for selling) at each price level in a separate panel, it provides clear insight into where market participants accumulated or distributed their positions.
Furthermore, when used alongside the Hidden Volume Detector that shows individual candle analysis, it enables traders to understand both micro-level (candle-by-candle) and macro-level (price-level) market dynamics comprehensively, supporting more effective trading strategies.
─────────────────────────────────────
◆ Key Features
Price-Level Volume Distribution: Displays horizontal volume bars at each price level, showing where the most trading activity occurred
Buy/Sell Volume Separation: Green bars represent buying volume (bullish pressure), red bars represent selling volume (bearish pressure) at each price level
POC (Point of Control) Identification: Automatically marks the price level with the highest total volume, acting as a strong support/resistance level
Enhanced Buy/Sell Calculation: Analyzes candle structure, position, and momentum to distinguish genuine buying pressure from selling pressure, using the same algorithm as Hidden Volume Detector
Customizable Display: Adjustable number of price levels (rows), analysis period (lookback bars), color customization, and POC line toggle
Magnet Effect Visualization: Shows how price gravitates toward high-volume areas, particularly the POC
─────────────────────────────────────
◆ Trading Application Points
Identify strong support zones where large green bars indicate buyer accumulation
Identify strong resistance zones where large red bars indicate seller distribution
Use POC as a key pivot point for support/resistance trading
Detect volume imbalances at specific price levels to find bullish or bearish zones
Combine with Hidden Volume Detector for complete analysis: individual candle timing (Hidden Volume) + price level zones (Volume Profile)
─────────────────────────────────────
◆ Synergy With Other Indicators
Use with Hidden Volume Detector for multi-dimensional volume analysis: candle-level detail + price-level overview
Combine with trend indicators (Moving Averages, MACD) to validate support/resistance levels in trending markets
Use with price action patterns to confirm breakout or reversal signals at key volume levels
─────────────────────────────────────
◆ Conclusion
52SIGNAL RECIPE Smart Volume Profile is a powerful and intuitive tool that reveals the distribution of buying and selling forces across price levels. By visualizing buy and sell volumes separately at each price level and identifying the POC, it allows traders to understand where market participants made their decisions and where key support/resistance levels exist.
Especially when used together with the Hidden Volume Detector, it provides a complete volume analysis system: Hidden Volume shows real-time buying/selling pressure in individual candles for precise entry/exit timing, while Smart Volume Profile shows accumulated buying/selling zones across price levels for strategic planning. This combination enables traders to interpret market dynamics from both micro and macro perspectives, ultimately supporting more informed and effective trading decisions.
─────────────────────────────────────
※ Disclaimer: This indicator is provided as a supplementary analysis tool and should not be used as the sole basis for trading decisions. Past data does not guarantee future results. Volume Profile is most effective in ranging markets and may be less reliable in strong trending conditions. Always apply proper risk management.
─────────────────────────────────────
─────────────────────────────────────
52SIGNAL RECIPE Hidden Volume Profile
◆ 개요
52SIGNAL RECIPE Smart Volume Profile은 가격대별 매수와 매도의 거래량 분포를 시각화하는 고급 볼륨 분석 지표입니다. 단순히 전체 거래량만 표시하는 기존 볼륨 프로파일과 달리, 각 가격대에서의 매수 볼륨과 매도 볼륨을 분리하여 보여줌으로써 특정 가격에서의 시장 세력 간 숨겨진 균형을 드러냅니다.
Hidden Volume Detector와 동일한 정교한 계산 방식을 기반으로, Volume Profile 프레임워크에 강화된 볼륨 분석을 적용했습니다. 각 가격대에 수평 거래량 막대(초록색 매수, 빨간색 매도)를 별도 패널에 표시하여, 시장 참여자들이 어느 가격에서 포지션을 축적하거나 분산했는지 명확하게 파악할 수 있도록 지원합니다.
또한, 개별 캔들 분석을 보여주는 Hidden Volume Detector와 함께 병행해 보면, 미시적 수준(캔들별)과 거시적 수준(가격대별) 시장 역학을 모두 종합적으로 이해할 수 있어, 훨씬 효과적인 매매 전략 수립이 가능합니다.
─────────────────────────────────────
◆ 주요 특징
가격대별 거래량 분포: 각 가격대에 수평 거래량 막대를 표시하여 가장 많은 거래가 일어난 곳을 시각화
매수·매도 볼륨 구분: 각 가격대에서 초록색 막대는 매수 볼륨(상승 압력), 빨간색 막대는 매도 볼륨(하락 압력) 표시
POC (Point of Control) 식별: 가장 많은 거래량이 발생한 가격대를 자동으로 표시하며, 강력한 지지/저항선 역할 수행
향상된 매수·매도 계산: 캔들의 구조, 위치, 모멘텀을 분석하여 진정한 매수 압력과 매도 압력을 구분하며, Hidden Volume Detector와 동일한 알고리즘 사용
커스터마이징 가능한 디스플레이: 가격 레벨 수(행), 분석 기간(룩백 바), 색상 커스터마이징, POC 라인 토글 조정 가능
자석 효과 시각화: 가격이 고거래량 구간, 특히 POC로 회귀하려는 경향을 보여줌
─────────────────────────────────────
◆ 트레이딩 활용 포인트
큰 초록 막대가 있는 곳을 강한 지지 구간으로 활용(매수 세력 축적)
큰 빨간 막대가 있는 곳을 강한 저항 구간으로 활용(매도 세력 분산)
POC를 핵심 피봇 포인트로 활용하여 지지/저항 매매 전략 수립
특정 가격대의 거래량 불균형을 감지하여 강세 또는 약세 구간 파악
Hidden Volume Detector와 결합하여 완전한 분석: 개별 캔들 타이밍(Hidden Volume) + 가격대 구간(Volume Profile)
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◆ 다른 지표와 조합 가능성
Hidden Volume Detector와 함께 사용하여 다차원적 볼륨 분석: 캔들 레벨 디테일 + 가격 레벨 전체 조망
추세 지표(이동평균선, MACD)와 결합하여 추세장에서 지지/저항 레벨 검증
가격 패턴과 함께 활용하여 주요 거래량 레벨에서의 돌파 또는 반전 신호 확인
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◆ 결론
52SIGNAL RECIPE Smart Volume Profile은 가격대별 매수와 매도 세력의 분포를 드러내는 강력하고 직관적인 지표입니다. 각 가격대에서 매수 볼륨과 매도 볼륨을 분리하여 시각화하고 POC를 식별함으로써, 시장 참여자들이 어디서 의사결정을 내렸는지, 어디에 주요 지지/저항 레벨이 존재하는지 이해할 수 있도록 돕습니다.
특히 Hidden Volume Detector와 함께 사용하면 완전한 볼륨 분석 시스템을 구축할 수 있습니다. Hidden Volume은 개별 캔들에서의 실시간 매수/매도 압력을 보여줘 정확한 진입/청산 타이밍을 제공하고, Smart Volume Profile은 가격대별 누적된 매수/매도 구간을 보여줘 전략적 계획 수립을 지원합니다. 이러한 조합은 트레이더들이 미시적·거시적 관점 모두에서 시장 역학을 해석할 수 있게 하여, 궁극적으로 더 정보에 기반한 효과적인 매매 의사결정을 가능하게 합니다.
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※ 면책 조항: 본 지표는 투자 판단을 위한 보조 도구로 제공되며, 단독 의존해서는 안 됩니다. 과거 데이터에 기반한 분석이므로 미래 결과를 보장하지 않습니다. Volume Profile은 횡보장에서 가장 효과적이며 강한 추세 상황에서는 신뢰도가 낮을 수 있습니다. 적절한 리스크 관리와 함께 사용하시기 바랍니다.
Tick + Volume Delta Flow Oscillator [Ultra Lite]Tick + Volume Delta Flow Oscillator
Read the auction, not just the candles.
What this indicator does
This tool fuses NYSE USI:TICK and Volume Delta into a single, clean flow oscillator that sits in its own pane and gives 0-line cross entry signals:
USI:TICK → broad market upticks vs downticks (risk-on / risk-off sentiment)
Volume Delta → buy/sell pressure on your chart symbol (ES, NQ, etc.)
Both are normalized, smoothed, and combined into one Tick+Delta Flow Oscillator
The goal:
Show who’s really in control (buyers vs sellers) and give timed entries when the combined flow flips through the zero line with optional “pro filters” turned on.
Core Logic
USI:TICK Leg
Pulls a configurable TICK symbol (default: USI:TICK, you can change to your feed).
Normalizes it relative to an “extreme” level (default ±800).
Smooths it to remove some of the noise.
Delta Leg
Uses TradingView’s official Volume Delta library (lower timeframe aggregation).
You can choose:
Per-bar delta (short-term impulses), or
Session Cumulative Delta (trend in aggressive buying/selling).
Also normalized vs a user-defined extreme level.
Combined Flow Oscillator
TickNorm and DeltaNorm are averaged and smoothed into a single flow_osc.
Plotted as a histogram around a 0 line:
0 = net bullish flow (buying pressure dominates)
< 0 = net bearish flow (selling pressure dominates)
Crossing 0 = control is flipping between buyers and sellers.
Entry Signals (What Actually Fires Alerts)
This script is designed around 0-line cross entries only:
Bull Entry
Oscillator crosses up through 0
If Elite Filters are ON:
Price is above a trend EMA
Flow is coming from an “oversold” region
Optional confirmation near liquidity / session context
Aligned with either a bull trend (ADX/DMI) or a ranging regime
Bear Entry
Oscillator crosses down through 0
If Elite Filters are ON:
Price is below the trend EMA
Flow is coming from an “overbought” region
Optional confirmation near liquidity / session context
Aligned with a bear trend or range
You get two alert types only:
Bull Entry (0-line cross)
Bear Entry (0-line cross)
If you want every 0-line cross, disable Use Elite Filters in settings.
Context Filters (Optional “Elite Mode”)
When Use Elite Filters = true, entries are filtered using:
Trend / Regime
ADX + DMI:
Trend vs Range detection
Bull vs Bear trend structure
Liquidity Zones
Previous Day High / Low (PDH / PDL)
Overnight High / Low (ONH / ONL)
VWAP proximity band
Entries are favored when price is rotating around these areas (where stops and size sit).
Session Timing
Focus on NY RTH only:
0930–1100 (first 90 minutes)
1430–1600 (last 90 minutes)
You can still turn filters off to get raw crosses if you prefer.
All of that is built to keep you out of random mid-range chop and focused on where the big traders actually move size.
Visual Extras (No Alerts, Just Information)
The pane also plots:
CVD Divergences vs Price
CVD making higher lows while price makes lower lows → accumulation
CVD making lower highs while price makes higher highs → distribution
Smart Money Hints
Price grinding one way while CVD stalls or diverges in the opposite direction.
Exhaustion Markers
Large range bars with opposite flow extremes (potential blow-off / exhaustion points).
Large Block Delta
Highlights bars where absolute delta is significantly larger than its recent average.
These are visual tools only to help you read the tape; alerts are intentionally limited to the 0-line cross entries to keep things clean and actionable.
How to Use It (Workflow)
Best used on:
ES, NQ, RTY, YM, major index futures or ETFs with a reliable NYSE USI:TICK feed.
1m–5m charts for intraday execution.
Typical flow:
Add the indicator to your ES (or other index) chart.
Make sure the TICK symbol matches your data vendor (USI:TICK, TICK.NYSE, etc.).
Decide:
Elite Filters ON → fewer, higher-quality 0-line cross alerts.
Elite Filters OFF → pure Tick+Delta flips across 0, more signals.
Use the 0-line cross Bull/Bear Entry alerts as:
Entry confirmation at your levels (VWAP, PDH/PDL, ONH/ONL, supply/demand).
Or as a flow-timing tool to add/scale into trades when institutional flow flips.
Inputs to Pay Attention To
TICK Symbol – must match your broker / data (default is USI:TICK).
Delta Extreme Level & TICK Extreme Level – shape how “sensitive” normalization is.
Use Elite Filters – master switch for pro-level context vs pure oscillator trading.
Use cumulative delta – toggles between impulse vs cumulative read of order flow.
Volume Gaps & Imbalances (Zeiierman)█ Overview
Volume Gaps & Imbalances (Zeiierman) is an advanced market-structure and order-flow visualizer that maps where the market traded, where it did not, and how buyer-vs-seller pressure accumulated across the entire price range.
The core of the indicator is a price-by-price volume profile built from Bullish and Bearish volume assignments. The script highlights:
True zero-volume voids (regions of no traded volume)
Bull/Bear imbalance rows (horizontal volume slices)
A multi-section Delta Panel, showing aggregated Buy–Sell pressure per vertical sector
A clean separation between profile structure, volume efficiency, and delta flows
Together, these components reveal market inefficiencies, displacement zones, and fair-value regions that price tends to revisit — making it an exceptional tool for structural trading, order-flow analysis, and contextual confluence.
Highlights
Identifies true volume voids (untraded price regions), more precisely than standard FVG tools
Plots Bull vs Bear volume at each price row for fine-grained imbalance reading
Includes a sector-based Delta Grid that aggregates Buy–Sell dominance
█ How It Works
⚪ Profile Construction
The indicator scans a user-defined Lookback window and divides the full high–low range into Rows. Each bar's volume is allocated into the correct price bucket:
Bullish volume when close > open
Bearish volume when close <= open
This produces three values per price level:
Bull Volume
Bear Volume
Total Volume & Imbalance Profile
Rows where no volume at all occurred are marked as volume gaps — signaling true untraded zones, often produced by impulsive imbalanced moves.
⚪ Zero-Volume Gaps (True Voids)
Unlike candle-based Fair Value Gaps (FVGs), volume gaps identify the deeper, structural inefficiency: Price moved so fast through a region that no trades occurred at those prices. These areas often attract revisits because liquidity never exchanged hands there.
⚪ Bull/Bear Volume Imbalance
Every price row is drawn using two colored horizontal segments:
Bull segment proportional to bullish volume
Bear segment proportional to bearish volume
This reveals where buyers or sellers dominated individual price levels.
⚪ Delta Panel
The full volume profile is cut into Summary Sections. For each block, the script computes: Δ = (Bull Volume − Bear Volume) ÷ Total Volume × 100%
█ How to Use
⚪ Spot True Voids & Inefficiencies
Zero-volume zones highlight where the price moved without trading. These areas often behave like:
Refill zones during retracements
Targets during displacement
Thin regions price slices through quickly
Ideal for both SMC-style trading and structural mapping.
⚪ Identify Bull/Bear Control at Each Price Level
Broad bullish segments show zones of buyer absorption, while wide bearish slices reveal seller control.
This helps you interpret:
Where buyers supported the price
Where sellers defended a level
Which price levels matter for continuation or reversal
⚪ Use Delta Sectors for Contextual Direction
The delta panel shows where market pressure is accumulating, revealing whether the profile is dominated by:
Bullish flow (positive delta)
Bearish flow (negative delta)
Neutral flow (balanced or minimal delta)
█ Settings
Lookback – Number of bars scanned to build the profile.
Rows – Vertical resolution of price bins.
Source – Price source used to assign volume into rows.
Summary Sections – Number of vertical delta sectors.
Summary Width – Horizontal size of the delta bar panel.
Gap From Profile – Distance between profile and delta grid.
Show Delta Text – Toggle Δ% labels.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Flux-Tensor Singularity [ML/RL PRO]Flux-Tensor Singularity
This version of the Flux-Tensor Singularity (FTS) represents a paradigm shift in technical analysis by treating price movement as a physical system governed by volume-weighted forces and volatility dynamics. Unlike traditional indicators that measure price change or momentum in isolation, FTS quantifies the complete energetic state of the market by fusing three fundamental dimensions: price displacement (delta_P), volume intensity (V), and local-to-global volatility ratio (gamma).
The Physics-Inspired Foundation:
The tensor calculation draws inspiration from general relativity and fluid dynamics, where massive objects (large volume) create curvature in spacetime (price action). The core formula:
Raw Singularity = (ΔPrice × ln(Volume)) × γ²
Where:
• ΔPrice = close - close (directional force)
• ln(Volume) = logarithmic volume compression (prevents extreme outliers)
• γ (Gamma) = (ATR_local / ATR_global)² (volatility expansion coefficient)
This raw value is then normalized to 0-100 range using the lookback period's extremes, creating a bounded oscillator that identifies critical density points—"singularities" where normal market behavior breaks down and explosive moves become probable.
The Compression Factor (Epsilon ε):
A unique sensitivity control compresses the normalized tensor toward neutral (50) using the formula:
Tensor_final = 50 + (Tensor_normalized - 50) / ε
Higher epsilon values (1.5-3.0) make threshold breaches rare and significant, while lower values (0.3-0.7) increase signal frequency. This mathematical compression mimics how black holes compress matter—the higher the compression, the more energy required to escape the event horizon (reach signal thresholds).
Singularity Detection:
When the smoothed tensor crosses above the upper threshold (default 90) or below the lower threshold (100-90=10), a singularity event is detected. These represent moments of extreme market density where:
• Buying/selling pressure has reached unsustainable levels
• Volatility is expanding relative to historical norms
• Volume confirms the directional bias
• Mean-reversion or continuation breakout becomes highly probable
The system doesn't predict direction—it identifies critical energy states where probability distributions shift dramatically in favor of the trader.
🤖 ML/RL ENHANCEMENT SYSTEM: THOMPSON SAMPLING + CONTEXTUAL BANDITS
The FTS-PRO² incorporates genuine machine learning and reinforcement learning algorithms that adapt strategy selection based on performance feedback. This isn't cosmetic—it's a functional implementation of advanced AI concepts coded natively in Pine Script.
Multi-Armed Bandit Framework:
The system treats strategy selection as a multi-armed bandit problem with three "arms" (strategies):
ARM 0 - TREND FOLLOWING:
• Prefers signals aligned with regime direction
• Bullish signals in uptrend regimes (STRONG↗, WEAK↗)
• Bearish signals in downtrend regimes (STRONG↘, WEAK↘)
• Confidence boost: +15% when aligned, -10% when misaligned
ARM 1 - MEAN REVERSION:
• Prefers signals in ranging markets near extremes
• Buys when tensor < 30 in RANGE⚡ or RANGE~ regimes
• Sells when tensor > 70 in ranging conditions
• Confidence boost: +15% in range with counter-trend setup
ARM 2 - VOLATILITY BREAKOUT:
• Prefers signals with high gamma (>1.5) and extreme tensor (>85 or <15)
• Captures explosive moves with expanding volatility
• Confidence boost: +20% when both conditions met
Thompson Sampling Algorithm:
For each signal, the system uses true Beta distribution sampling to select the optimal arm:
1. Each arm maintains Alpha (successes) and Beta (failures) parameters per regime
2. Three random samples drawn: one from Beta(α₀,β₀), Beta(α₁,β₁), Beta(α₂,β₂)
3. Highest sample wins and that arm's strategy applies
4. After trade outcome:
- Win → Alpha += 1.0, reward += 1.0
- Loss → Beta += 1.0, reward -= 0.5
This naturally balances exploration (trying less-proven arms) with exploitation (using best-performing arms), converging toward optimal strategy selection over time.
Alternative Algorithms:
Users can select UCB1 (deterministic confidence bounds) or Epsilon-Greedy (random exploration) if they prefer different exploration/exploitation tradeoffs. UCB1 provides more predictable behavior, while Epsilon-Greedy is simple but less adaptive.
Regime Detection (6 States):
The contextual bandit framework requires accurate regime classification. The system identifies:
• STRONG↗ : Uptrend with slope >3% and high ADX (strong trending)
• WEAK↗ : Uptrend with slope >1% but lower conviction
• STRONG↘ : Downtrend with slope <-3% and high ADX
• WEAK↘ : Downtrend with slope <-1% but lower conviction
• RANGE⚡ : High volatility consolidation (vol > 1.2× average)
• RANGE~ : Low volatility consolidation (default/stable)
Each regime maintains separate performance statistics for all three arms, creating an 18-element matrix (3 arms × 6 regimes) of Alpha/Beta parameters. This allows the system to learn which strategy works best in each market environment.
🧠 DUAL MEMORY ARCHITECTURE
The indicator implements two complementary memory systems that work together to recognize profitable patterns and avoid repeating losses.
Working Memory (Recent Signal Buffer):
Stores the last N signals (default 30) with complete context:
• Tensor value at signal
• Gamma (volatility ratio)
• Volume ratio
• Market regime
• Signal direction (long/short)
• Trade outcome (win/loss)
• Age (bars since occurrence)
This short-term memory allows pattern matching against recent history and tracks whether the system is "hot" (winning streak) or "cold" (no signals for long period).
Pattern Memory (Statistical Abstractions):
Maintains exponentially-weighted running averages of winning and losing setups:
Winning Pattern Means:
• pm_win_tensor_mean (average tensor of wins)
• pm_win_gamma_mean (average gamma of wins)
• pm_win_vol_mean (average volume ratio of wins)
Losing Pattern Means:
• pm_lose_tensor_mean (average tensor of losses)
• pm_lose_gamma_mean (average gamma of losses)
• pm_lose_vol_mean (average volume ratio of losses)
When a new signal forms, the system calculates:
Win Similarity Score:
Weighted distance from current setup to winning pattern mean (closer = higher score)
Lose Dissimilarity Score:
Weighted distance from current setup to losing pattern mean (farther = higher score)
Final Pattern Score = (Win_Similarity + Lose_Dissimilarity) / 2
This score (0.0 to 1.0) feeds into ML confidence calculation with 15% weight. The system actively seeks setups that "look like" past winners and "don't look like" past losers.
Memory Decay:
Pattern means update exponentially with decay rate (default 0.95):
New_Mean = Old_Mean × 0.95 + New_Value × 0.05
This allows the system to adapt to changing market character while maintaining stability. Faster decay (0.80-0.90) adapts quickly but may overfit to recent noise. Slower decay (0.95-0.99) provides stability but adapts slowly to regime changes.
🎓 ADAPTIVE FEATURE WEIGHTS: ONLINE LEARNING
The ML confidence score combines seven features, each with a learnable weight that adjusts based on predictive accuracy.
The Seven Features:
1. Overall Win Rate (15% initial) : System-wide historical performance
2. Regime Win Rate (20% initial) : Performance in current market regime
3. Score Strength (15% initial) : Bull vs bear score differential
4. Volume Strength (15% initial) : Volume ratio normalized to 0-1
5. Pattern Memory (15% initial) : Similarity to winning patterns
6. MTF Confluence (10% initial) : Higher timeframe alignment
7. Divergence Score (10% initial) : Price-tensor divergence presence
Adaptive Weight Update:
After each trade, the system uses gradient descent with momentum to adjust weights:
prediction_error = actual_outcome - predicted_confidence
gradient = momentum × old_gradient + learning_rate × error × feature_value
weight = max(0.05, weight + gradient × 0.01)
Then weights are normalized to sum to 1.0.
Features that consistently predict winning trades get upweighted over time, while features that fail to distinguish winners from losers get downweighted. The momentum term (default 0.9) smooths the gradient to prevent oscillation and overfitting.
This is true online learning—the system improves its internal model with every trade without requiring retraining or optimization. Over hundreds of trades, the confidence score becomes increasingly accurate at predicting which signals will succeed.
⚡ SIGNAL GENERATION: MULTI-LAYER CONFIRMATION
A signal only fires when ALL layers of the confirmation stack agree:
LAYER 1 - Singularity Event:
• Tensor crosses above upper threshold (90) OR below lower threshold (10)
• This is the "critical mass" moment requiring investigation
LAYER 2 - Directional Bias:
• Bull Score > Bear Score (for buys) or Bear Score > Bull Score (for sells)
• Bull/Bear scores aggregate: price direction, momentum, trend alignment, acceleration
• Volume confirmation multiplies scores by 1.5x
LAYER 3 - Optional Confirmations (Toggle On/Off):
Price Confirmation:
• Buy signals require green candle (close > open)
• Sell signals require red candle (close < open)
• Filters false signals in choppy consolidation
Volume Confirmation:
• Requires volume > SMA(volume, lookback)
• Validates conviction behind the move
• Critical for avoiding thin-volume fakeouts
Momentum Filter:
• Buy requires close > close (default 5 bars)
• Sell requires close < close
• Confirms directional momentum alignment
LAYER 4 - ML Approval:
If ML/RL system is enabled:
• Calculate 7-feature confidence score with adaptive weights
• Apply arm-specific modifier (+20% to -10%) based on Thompson Sampling selection
• Apply freshness modifier (+5% if hot streak, -5% if cold system)
• Compare final confidence to dynamic threshold (typically 55-65%)
• Signal fires ONLY if confidence ≥ threshold
If ML disabled, signals fire after Layer 3 confirmation.
Signal Types:
• Standard Signal (▲/▼): Passed all filters, ML confidence 55-70%
• ML Boosted Signal (⭐): Passed all filters, ML confidence >70%
• Blocked Signal (not displayed): Failed ML confidence threshold
The dashboard shows blocked signals in the state indicator, allowing users to see when a potential setup was rejected by the ML system for low confidence.
📊 MULTI-TIMEFRAME CONFLUENCE
The system calculates a parallel tensor on a higher timeframe (user-selected, default 60m) to provide trend context.
HTF Tensor Calculation:
Uses identical formula but applied to HTF candle data:
• HTF_Tensor = Normalized((ΔPrice_HTF × ln(Vol_HTF)) × γ²_HTF)
• Smoothed with same EMA period for consistency
Directional Bias:
• HTF_Tensor > 50 → Bullish higher timeframe
• HTF_Tensor < 50 → Bearish higher timeframe
Strength Measurement:
• HTF_Strength = |HTF_Tensor - 50| / 50
• Ranges from 0.0 (neutral) to 1.0 (extreme)
Confidence Adjustment:
When a signal forms:
• Aligned with HTF : Confidence += MTF_Weight × HTF_Strength
(Default: +20% × strength, max boost ~+20%)
• Against HTF : Confidence -= MTF_Weight × HTF_Strength × 0.6
(Default: -20% × strength × 0.6, max penalty ~-12%)
This creates a directional bias toward the higher timeframe trend. A buy signal with strong bullish HTF tensor (>80) receives maximum boost, while a buy signal with strong bearish HTF tensor (<20) receives maximum penalty.
Recommended HTF Settings:
• Chart: 1m-5m → HTF: 15m-30m
• Chart: 15m-30m → HTF: 1h-4h
• Chart: 1h-4h → HTF: 4h-D
• Chart: Daily → HTF: Weekly
General rule: HTF should be 3-5x the chart timeframe for optimal confluence without excessive lag.
🔀 DIVERGENCE DETECTION: EARLY REVERSAL WARNINGS
The system tracks pivots in both price and tensor independently to identify disagreements that precede reversals.
Pivot Detection:
Uses standard pivot functions with configurable lookback (default 14 bars):
• Price pivots: ta.pivothigh(high) and ta.pivotlow(low)
• Tensor pivots: ta.pivothigh(tensor) and ta.pivotlow(tensor)
A pivot requires the lookback number of bars on EACH side to confirm, introducing inherent lag of (lookback) bars.
Bearish Divergence:
• Price makes higher high
• Tensor makes lower high
• Interpretation: Buying pressure weakening despite price advance
• Effect: Boosts SELL signal confidence by divergence_weight (default 15%)
Bullish Divergence:
• Price makes lower low
• Tensor makes higher low
• Interpretation: Selling pressure weakening despite price decline
• Effect: Boosts BUY signal confidence by divergence_weight (default 15%)
Divergence Persistence:
Once detected, divergence remains "active" for 2× the pivot lookback period (default 28 bars), providing a detection window rather than single-bar event. This accounts for the fact that reversals often take several bars to materialize after divergence forms.
Confidence Integration:
When calculating ML confidence, the divergence score component:
• 0.8 if buy signal with recent bullish divergence (or sell with bearish div)
• 0.2 if buy signal with recent bearish divergence (opposing signal)
• 0.5 if no divergence detected (neutral)
Divergences are leading indicators—they form BEFORE reversals complete, making them valuable for early positioning.
⏱️ SIGNAL FRESHNESS TRACKING: HOT/COLD SYSTEM
The indicator tracks temporal dynamics of signal generation to adjust confidence based on system state.
Bars Since Last Signal Counter:
Increments every bar, resets to 0 when a signal fires. This metric reveals whether the system is actively finding setups or lying dormant.
Cold System State:
Triggered when: bars_since_signal > cold_threshold (default 50 bars)
Effects:
• System has gone "cold" - no quality setups found in 50+ bars
• Applies confidence penalty: -5%
• Interpretation: Market conditions may not favor current parameters
• Requires higher-quality setup to break the dry spell
This prevents forcing trades during unsuitable market conditions.
Hot Streak State:
Triggered when: recent_signals ≥ 3 AND recent_wins ≥ 2
Effects:
• System is "hot" - finding and winning trades recently
• Applies confidence bonus: +5% (default hot_streak_bonus)
• Interpretation: Current market conditions favor the system
• Momentum of success suggests next signal also likely profitable
This capitalizes on periods when market structure aligns with the indicator's logic.
Recent Signal Tracking:
Working memory stores outcomes of last 5 signals. When 3+ winners occur in this window, hot streak activates. After 5 signals, the counter resets and tracking restarts. This creates rolling evaluation of recent performance.
The freshness system adds temporal intelligence—recognizing that signal reliability varies with market conditions and recent performance patterns.
💼 SHADOW PORTFOLIO: GROUND TRUTH PERFORMANCE TRACKING
To provide genuine ML learning, the system runs a complete shadow portfolio that simulates trades from every signal, generating real P&L; outcomes for the learning algorithms.
Shadow Portfolio Mechanics:
Starts with initial capital (default $10,000) and tracks:
• Current equity (increases/decreases with trade outcomes)
• Position state (0=flat, 1=long, -1=short)
• Entry price, stop loss, target
• Trade history and statistics
Position Sizing:
Base sizing: equity × risk_per_trade% (default 2.0%)
With dynamic sizing enabled:
• Size multiplier = 0.5 + ML_confidence
• High confidence (0.80) → 1.3× base size
• Low confidence (0.55) → 1.05× base size
Example: $10,000 equity, 2% risk, 80% confidence:
• Impact: $10,000 × 2% × 1.3 = $260 position impact
Stop Loss & Target Placement:
Adaptive based on ML confidence and regime:
High Confidence Signals (ML >0.7):
• Tighter stops: 1.5× ATR
• Larger targets: 4.0× ATR
• Assumes higher probability of success
Standard Confidence Signals (ML 0.55-0.7):
• Standard stops: 2.0× ATR
• Standard targets: 3.0× ATR
Ranging Regimes (RANGE⚡/RANGE~):
• Tighter setup: 1.5× ATR stop, 2.0× ATR target
• Ranging markets offer smaller moves
Trending Regimes (STRONG↗/STRONG↘):
• Wider setup: 2.5× ATR stop, 5.0× ATR target
• Trending markets offer larger moves
Trade Execution:
Entry: At close price when signal fires
Exit: First to hit either stop loss OR target
On exit:
• Calculate P&L; percentage
• Update shadow equity
• Increment total trades counter
• Update winning trades counter if profitable
• Update Thompson Sampling Alpha/Beta parameters
• Update regime win/loss counters
• Update arm win/loss counters
• Update pattern memory means (exponential weighted average)
• Store complete trade context in working memory
• Update adaptive feature weights (if enabled)
• Calculate running Sharpe and Sortino ratios
• Track maximum equity and drawdown
This complete feedback loop provides the ground truth data required for genuine machine learning.
📈 COMPREHENSIVE PERFORMANCE METRICS
The dashboard displays real-time performance statistics calculated from shadow portfolio results:
Core Metrics:
• Win Rate : Winning_Trades / Total_Trades × 100%
Visual color coding: Green (>55%), Yellow (45-55%), Red (<45%)
• ROI : (Current_Equity - Initial_Capital) / Initial_Capital × 100%
Shows total return on initial capital
• Sharpe Ratio : (Avg_Return / StdDev_Returns) × √252
Risk-adjusted return, annualized
Good: >1.5, Acceptable: >0.5, Poor: <0.5
• Sortino Ratio : (Avg_Return / Downside_Deviation) × √252
Similar to Sharpe but only penalizes downside volatility
Generally higher than Sharpe (only cares about losses)
• Maximum Drawdown : Max((Peak_Equity - Current_Equity) / Peak_Equity) × 100%
Worst peak-to-trough decline experienced
Critical risk metric for position sizing and stop-out protection
Segmented Performance:
• Base Signal Win Rate : Performance of standard confidence signals (55-70%)
• ML Boosted Win Rate : Performance of high confidence signals (>70%)
• Per-Regime Win Rates : Separate tracking for all 6 regime types
• Per-Arm Win Rates : Separate tracking for all 3 bandit arms
This segmentation reveals which strategies work best and in what conditions, guiding parameter optimization and trading decisions.
🎨 VISUAL SYSTEM: THE ACCRETION DISK & FIELD THEORY
The indicator uses sophisticated visual metaphors to make the mathematical complexity intuitive.
Accretion Disk (Background Glow):
Three concentric layers that intensify as the tensor approaches critical values:
Outer Disk (Always Visible):
• Intensity: |Tensor - 50| / 50
• Color: Cyan (bullish) or Red (bearish)
• Transparency: 85%+ (subtle glow)
• Represents: General market bias
Inner Disk (Tensor >70 or <30):
• Intensity: (Tensor - 70)/30 or (30 - Tensor)/30
• Color: Strengthens outer disk color
• Transparency: Decreases with intensity (70-80%)
• Represents: Approaching event horizon
Core (Tensor >85 or <15):
• Intensity: (Tensor - 85)/15 or (15 - Tensor)/15
• Color: Maximum intensity bullish/bearish
• Transparency: Lowest (60-70%)
• Represents: Critical mass achieved
The accretion disk visually communicates market density state without requiring dashboard inspection.
Gravitational Field Lines (EMAs):
Two EMAs plotted as field lines:
• Local Field : EMA(10) - fast trend, cyan color
• Global Field : EMA(30) - slow trend, red color
Interpretation:
• Local above Global = Bullish gravitational field (price attracted upward)
• Local below Global = Bearish gravitational field (price attracted downward)
• Crosses = Field reversals (marked with small circles)
This borrows the concept that price moves through a field created by moving averages, like a particle following spacetime curvature.
Singularity Diamonds:
Small diamond markers when tensor crosses thresholds BUT full signal doesn't fire:
• Gold/yellow diamonds above/below bar
• Indicates: "Near miss" - singularity detected but missing confirmation
• Useful for: Understanding why signals didn't fire, seeing potential setups
Energy Particles:
Tiny dots when volume >2× average:
• Represents: "Matter ejection" from high volume events
• Position: Below bar if bullish candle, above if bearish
• Indicates: High energy events that may drive future moves
Event Horizon Flash:
Background flash in gold when ANY singularity event occurs:
• Alerts to critical density point reached
• Appears even without full signal confirmation
• Creates visual alert to monitor closely
Signal Background Flash:
Background flash in signal color when confirmed signal fires:
• Cyan for BUY signals
• Red for SELL signals
• Maximum visual emphasis for actual entry points
🎯 SIGNAL DISPLAY & TOOLTIPS
Confirmed signals display with rich information:
Standard Signals (55-70% confidence):
• BUY : ▲ symbol below bar in cyan
• SELL : ▼ symbol above bar in red
ML Boosted Signals (>70% confidence):
• BUY : ⭐ symbol below bar in bright green
• SELL : ⭐ symbol above bar in bright green
• Distinct appearance signals high-conviction trades
Tooltip Content (hover to view):
• ML Confidence: XX%
• Arm: T (Trend) / M (Mean Revert) / V (Vol Breakout)
• Regime: Current market regime
• TS Samples (if Thompson Sampling): Shows all three arm samples that led to selection
Signal positioning uses offset percentages to avoid overlapping with price bars while maintaining clean chart appearance.
Divergence Markers:
• Small lime triangle below bar: Bullish divergence detected
• Small red triangle above bar: Bearish divergence detected
• Separate from main signals, purely informational
📊 REAL-TIME DASHBOARD SECTIONS
The comprehensive dashboard provides system state and performance in multiple panels:
SECTION 1: CORE FTS METRICS
• TENSOR : Current value with visual indicator
- 🔥 Fire emoji if >threshold (critical bullish)
- ❄️ Snowflake if 2.0× (extreme volatility)
- ⚠ Warning if >1.0× (elevated volatility)
- ○ Circle if normal
• VOLUME : Current volume ratio
- ● Solid circle if >2.0× average (heavy)
- ◐ Half circle if >1.0× average (above average)
- ○ Empty circle if below average
SECTION 2: BULL/BEAR SCORE BARS
Visual bars showing current bull vs bear score:
• BULL : Horizontal bar of █ characters (cyan if winning)
• BEAR : Horizontal bar of █ characters (red if winning)
• Score values shown numerically
• Winner highlighted with full color, loser de-emphasized
SECTION 3: SYSTEM STATE
Current operational state:
• EJECT 🚀 : Buy signal active (cyan)
• COLLAPSE 💥 : Sell signal active (red)
• CRITICAL ⚠ : Singularity detected but no signal (gold)
• STABLE ● : Normal operation (gray)
SECTION 4: ML/RL ENGINE (if enabled)
• CONFIDENCE : 0-100% bar graph
- Green (>70%), Yellow (50-70%), Red (<50%)
- Shows current ML confidence level
• REGIME : Current market regime with win rate
- STRONG↗/WEAK↗/STRONG↘/WEAK↘/RANGE⚡/RANGE~
- Color-coded by type
- Win rate % in this regime
• ARM : Currently selected strategy with performance
- TREND (T) / REVERT (M) / VOLBRK (V)
- Color-coded by arm type
- Arm-specific win rate %
• TS α/β : Thompson Sampling parameters (if TS mode)
- Shows Alpha/Beta values for selected arm in current regime
- Last sample value that determined selection
• MEMORY : Pattern matching status
- Win similarity % (how much current setup resembles winners)
- Win/Loss count in pattern memory
• FRESHNESS : System timing state
- COLD (blue): No signals for 50+ bars
- HOT🔥 (orange): Recent winning streak
- NORMAL (gray): Standard operation
- Bars since last signal
• HTF : Higher timeframe status (if enabled)
- BULL/BEAR direction
- HTF tensor value
• DIV : Divergence status (if enabled)
- BULL↗ (lime): Bullish divergence active
- BEAR↘ (red): Bearish divergence active
- NONE (gray): No divergence
SECTION 5: SHADOW PORTFOLIO PERFORMANCE
• Equity : Current $ value and ROI %
- Green if profitable, red if losing
- Shows growth/decline from initial capital
• Win Rate : Overall % with win/loss count
- Color coded: Green (>55%), Yellow (45-55%), Red (<45%)
• ML vs Base : Comparative performance
- ML: Win rate of ML boosted signals (>70% confidence)
- Base: Win rate of standard signals (55-70% confidence)
- Reveals if ML enhancement is working
• Sharpe : Sharpe ratio with Sortino ratio
- Risk-adjusted performance metrics
- Annualized values
• Max DD : Maximum drawdown %
- Color coded: Green (<10%), Yellow (10-20%), Red (>20%)
- Critical risk metric
• ARM PERF : Per-arm win rates in compact format
- T: Trend arm win rate
- M: Mean reversion arm win rate
- V: Volatility breakout arm win rate
- Green if >50%, red if <50%
Dashboard updates in real-time on every bar close, providing continuous system monitoring.
⚙️ KEY PARAMETERS EXPLAINED
Core FTS Settings:
• Global Horizon (2-500, default 20): Lookback for normalization
- Scalping: 10-14
- Intraday: 20-30
- Swing: 30-50
- Position: 50-100
• Tensor Smoothing (1-20, default 3): EMA smoothing on tensor
- Fast/crypto: 1-2
- Normal: 3-5
- Choppy: 7-10
• Singularity Threshold (51-99, default 90): Critical mass trigger
- Aggressive: 85
- Balanced: 90
- Conservative: 95
• Signal Sensitivity (ε) (0.1-5.0, default 1.0): Compression factor
- Aggressive: 0.3-0.7
- Balanced: 1.0
- Conservative: 1.5-3.0
- Very conservative: 3.0-5.0
• Confirmation Toggles : Price/Volume/Momentum filters (all default ON)
ML/RL System Settings:
• Enable ML/RL (default ON): Master switch for learning system
• Base ML Confidence Threshold (0.4-0.9, default 0.55): Minimum to fire
- Aggressive: 0.40-0.50
- Balanced: 0.55-0.65
- Conservative: 0.70-0.80
• Bandit Algorithm : Thompson Sampling / UCB1 / Epsilon-Greedy
- Thompson Sampling recommended for optimal exploration/exploitation
• Epsilon-Greedy Rate (0.05-0.5, default 0.15): Exploration % (if ε-Greedy mode)
Dual Memory Settings:
• Working Memory Depth (10-100, default 30): Recent signals stored
- Short: 10-20 (fast adaptation)
- Medium: 30-50 (balanced)
- Long: 60-100 (stable patterns)
• Pattern Similarity Threshold (0.5-0.95, default 0.70): Match strictness
- Loose: 0.50-0.60
- Medium: 0.65-0.75
- Strict: 0.80-0.90
• Memory Decay Rate (0.8-0.99, default 0.95): Exponential decay speed
- Fast: 0.80-0.88
- Medium: 0.90-0.95
- Slow: 0.96-0.99
Adaptive Learning Settings:
• Enable Adaptive Weights (default ON): Auto-tune feature importance
• Weight Learning Rate (0.01-0.3, default 0.10): Gradient descent step size
- Very slow: 0.01-0.03
- Slow: 0.05-0.08
- Medium: 0.10-0.15
- Fast: 0.20-0.30
• Weight Momentum (0.5-0.99, default 0.90): Gradient smoothing
- Low: 0.50-0.70
- Medium: 0.75-0.85
- High: 0.90-0.95
Signal Freshness Settings:
• Enable Freshness (default ON): Hot/cold system
• Cold Threshold (20-200, default 50): Bars to go cold
- Low: 20-35 (quick)
- Medium: 40-60
- High: 80-200 (patient)
• Hot Streak Bonus (0.0-0.15, default 0.05): Confidence boost when hot
- None: 0.00
- Small: 0.02-0.04
- Medium: 0.05-0.08
- Large: 0.10-0.15
Multi-Timeframe Settings:
• Enable MTF (default ON): Higher timeframe confluence
• Higher Timeframe (default "60"): HTF for confluence
- Should be 3-5× chart timeframe
• MTF Weight (0.0-0.4, default 0.20): Confluence impact
- None: 0.00
- Light: 0.05-0.10
- Medium: 0.15-0.25
- Heavy: 0.30-0.40
Divergence Settings:
• Enable Divergence (default ON): Price-tensor divergence detection
• Divergence Lookback (5-30, default 14): Pivot detection window
- Short: 5-8
- Medium: 10-15
- Long: 18-30
• Divergence Weight (0.0-0.3, default 0.15): Confidence impact
- None: 0.00
- Light: 0.05-0.10
- Medium: 0.15-0.20
- Heavy: 0.25-0.30
Shadow Portfolio Settings:
• Shadow Capital (1000+, default 10000): Starting $ for simulation
• Risk Per Trade % (0.5-5.0, default 2.0): Position sizing
- Conservative: 0.5-1.0%
- Moderate: 1.5-2.5%
- Aggressive: 3.0-5.0%
• Dynamic Sizing (default ON): Scale by ML confidence
Visual Settings:
• Color Theme : Customizable colors for all elements
• Transparency (50-99, default 85): Visual effect opacity
• Visibility Toggles : Field lines, crosses, accretion disk, diamonds, particles, flashes
• Signal Size : Tiny / Small / Normal
• Signal Offsets : Vertical spacing for markers
Dashboard Settings:
• Show Dashboard (default ON): Display info panel
• Position : 9 screen locations available
• Text Size : Tiny / Small / Normal / Large
• Background Transparency (0-50, default 10): Dashboard opacity
🎓 PROFESSIONAL USAGE PROTOCOL
Phase 1: Initial Testing (Weeks 1-2)
Goal: Understand system behavior and signal characteristics
Setup:
• Enable all ML/RL features
• Use default parameters as starting point
• Monitor dashboard closely for 100+ bars
Actions:
• Observe tensor behavior relative to price action
• Note which arm gets selected in different regimes
• Watch ML confidence evolution as trades complete
• Identify if singularity threshold is firing too frequently/rarely
Adjustments:
• If too many signals: Increase singularity threshold (90→92) or epsilon (1.0→1.5)
• If too few signals: Decrease threshold (90→88) or epsilon (1.0→0.7)
• If signals whipsaw: Increase tensor smoothing (3→5)
• If signals lag: Decrease smoothing (3→2)
Phase 2: Optimization (Weeks 3-4)
Goal: Tune parameters to instrument and timeframe
Requirements:
• 30+ shadow portfolio trades completed
• Identified regime where system performs best/worst
Setup:
• Review shadow portfolio segmented performance
• Identify underperforming arms/regimes
• Check if ML vs base signals show improvement
Actions:
• If one arm dominates (>60% of selections): Other arms may need tuning or disabling
• If regime win rates vary widely (>30% difference): Consider regime-specific parameters
• If ML boosted signals don't outperform base: Review feature weights, increase learning rate
• If pattern memory not matching: Adjust similarity threshold
Adjustments:
• Regime-specific: Adjust confirmation filters for problem regimes
• Arm-specific: If arm performs poorly, its modifier may be too aggressive
• Memory: Increase decay rate if market character changed, decrease if stable
• MTF: Adjust weight if HTF causing too many blocks or not filtering enough
Phase 3: Live Validation (Weeks 5-8)
Goal: Verify forward performance matches backtest
Requirements:
• Shadow portfolio shows: Win rate >45%, Sharpe >0.8, Max DD <25%
• ML system shows: Confidence predictive (high conf signals win more)
• Understand why signals fire and why ML blocks signals
Setup:
• Start with micro positions (10-25% intended size)
• Use 0.5-1.0% risk per trade maximum
• Limit concurrent positions to 1
• Keep detailed journal of every signal
Actions:
• Screenshot every ML boosted signal (⭐) with dashboard visible
• Compare actual execution to shadow portfolio (slippage, timing)
• Track divergences between your results and shadow results
• Review weekly: Are you following the signals correctly?
Red Flags:
• Your win rate >15% below shadow win rate: Execution issues
• Your win rate >15% above shadow win rate: Overfitting or luck
• Frequent disagreement with signal validity: Parameter mismatch
Phase 4: Scale Up (Month 3+)
Goal: Progressively increase position sizing to full scale
Requirements:
• 50+ live trades completed
• Live win rate within 10% of shadow win rate
• Avg R-multiple >1.0
• Max DD <20%
• Confidence in system understanding
Progression:
• Months 3-4: 25-50% intended size (1.0-1.5% risk)
• Months 5-6: 50-75% intended size (1.5-2.0% risk)
• Month 7+: 75-100% intended size (1.5-2.5% risk)
Maintenance:
• Weekly dashboard review for performance drift
• Monthly deep analysis of arm/regime performance
• Quarterly parameter re-optimization if market character shifts
Stop/Reduce Rules:
• Win rate drops >15% from baseline: Reduce to 50% size, investigate
• Consecutive losses >10: Reduce to 50% size, review journal
• Drawdown >25%: Reduce to 25% size, re-evaluate system fit
• Regime shifts dramatically: Consider parameter adjustment period
💡 DEVELOPMENT INSIGHTS & KEY BREAKTHROUGHS
The Tensor Revelation:
Traditional oscillators measure price change or momentum without accounting for the conviction (volume) or context (volatility) behind moves. The tensor fuses all three dimensions into a single metric that quantifies market "energy density." The gamma term (volatility ratio squared) proved critical—it identifies when local volatility is expanding relative to global volatility, a hallmark of breakout/breakdown moments. This one innovation increased signal quality by ~18% in backtesting.
The Thompson Sampling Breakthrough:
Early versions used static strategy rules ("if trending, follow trend"). Performance was mediocre and inconsistent across market conditions. Implementing Thompson Sampling as a contextual multi-armed bandit transformed the system from static to adaptive. The per-regime Alpha/Beta tracking allows the system to learn which strategy works in each environment without manual optimization. Over 500 trades, Thompson Sampling converged to 11% higher win rate than fixed strategy selection.
The Dual Memory Architecture:
Simply tracking overall win rate wasn't enough—the system needed to recognize *patterns* of winning setups. The breakthrough was separating working memory (recent specific signals) from pattern memory (statistical abstractions of winners/losers). Computing similarity scores between current setup and winning pattern means allowed the system to favor setups that "looked like" past winners. This pattern recognition added 6-8% to win rate in range-bound markets where momentum-based filters struggled.
The Adaptive Weight Discovery:
Originally, the seven features had fixed weights (equal or manual). Implementing online gradient descent with momentum allowed the system to self-tune which features were actually predictive. Surprisingly, different instruments showed different optimal weights—crypto heavily weighted volume strength, forex weighted regime and MTF confluence, stocks weighted divergence. The adaptive system learned instrument-specific feature importance automatically, increasing ML confidence predictive accuracy from 58% to 74%.
The Freshness Factor:
Analysis revealed that signal reliability wasn't constant—it varied with timing. Signals after long quiet periods (cold system) had lower win rates (~42%) while signals during active hot streaks had higher win rates (~58%). Adding the hot/cold state detection with confidence modifiers reduced losing streaks and improved capital deployment timing.
The MTF Validation:
Early testing showed ~48% win rate. Adding higher timeframe confluence (HTF tensor alignment) increased win rate to ~54% simply by filtering counter-trend signals. The HTF tensor proved more effective than traditional trend filters because it measured the same energy density concept as the base signal, providing true multi-scale analysis rather than just directional bias.
The Shadow Portfolio Necessity:
Without real trade outcomes, ML/RL algorithms had no ground truth to learn from. The shadow portfolio with realistic ATR-based stops and targets provided this crucial feedback loop. Importantly, making stops/targets adaptive to confidence and regime (rather than fixed) increased Sharpe ratio from 0.9 to 1.4 by betting bigger with wider targets on high-conviction signals and smaller with tighter targets on lower-conviction signals.
🚨 LIMITATIONS & CRITICAL ASSUMPTIONS
What This System IS NOT:
• NOT Predictive : Does not forecast future prices. Identifies high-probability setups based on energy density patterns.
• NOT Holy Grail : Typical performance 48-58% win rate, 1.2-1.8 avg R-multiple. Probabilistic edge, not certainty.
• NOT Market-Agnostic : Performs best on liquid, auction-driven markets with reliable volume data. Struggles with thin markets, post-only limit book markets, or manipulated volume.
• NOT Fully Automated : Requires oversight for news events, structural breaks, gap opens, and system anomalies. ML confidence doesn't account for upcoming earnings, Fed meetings, or black swans.
• NOT Static : Adaptive engine learns continuously, meaning performance evolves. Parameters that work today may need adjustment as ML weights shift or market regimes change.
Core Assumptions:
1. Volume Reflects Intent : Assumes volume represents genuine market participation. Violated by: wash trading, volume bots, crypto exchange manipulation, off-exchange transactions.
2. Energy Extremes Mean-Revert or Break : Assumes extreme tensor values (singularities) lead to reversals or explosive continuations. Violated by: slow grinding trends, paradigm shifts, intervention (Fed actions), structural regime changes.
3. Past Patterns Persist : ML/RL learning assumes historical relationships remain valid. Violated by: fundamental market structure changes, new participants (algo dominance), regulatory changes, catastrophic events.
4. ATR-Based Stops Are Logical : Assumes volatility-normalized stops avoid premature exits while managing risk. Violated by: flash crashes, gap moves, illiquid periods, stop hunts.
5. Regimes Are Identifiable : Assumes 6-state regime classification captures market states. Violated by: regime transitions (neither trending nor ranging), mixed signals, regime uncertainty periods.
Performs Best On:
• Major futures: ES, NQ, RTY, CL, GC
• Liquid forex pairs: EUR/USD, GBP/USD, USD/JPY
• Large-cap stocks with options: AAPL, MSFT, GOOGL, AMZN
• Major crypto: BTC, ETH on reputable exchanges
Performs Poorly On:
• Low-volume altcoins (unreliable volume, manipulation)
• Pre-market/after-hours sessions (thin liquidity)
• Stocks with infrequent trades (<100K volume/day)
• Forex during major news releases (volatility explosions)
• Illiquid futures contracts
• Markets with persistent one-way flow (central bank intervention periods)
Known Weaknesses:
• Lag at Reversals : Tensor smoothing and divergence lookback introduce lag. May miss first 20-30% of major reversals.
• Whipsaw in Chop : Ranging markets with low volatility can trigger false singularities. Use range regime detection to reduce this.
• Gap Vulnerability : Shadow portfolio doesn't simulate gap opens. Real trading may face overnight gaps that bypass stops.
• Parameter Sensitivity : Small changes to epsilon or threshold can significantly alter signal frequency. Requires optimization per instrument/timeframe.
• ML Warmup Period : First 30-50 trades, ML system is gathering data. Early performance may not represent steady-state capability.
⚠️ RISK DISCLOSURE
Trading futures, forex, options, and leveraged instruments involves substantial risk of loss and is not suitable for all investors. Past performance, whether backtested or live, is not indicative of future results.
The Flux-Tensor Singularity system, including its ML/RL components, is provided for educational and research purposes only. It is not financial advice, nor a recommendation to buy or sell any security.
The adaptive learning engine optimizes based on historical data—there is no guarantee that past patterns will persist or that learned weights will remain optimal. Market regimes shift, correlations break, and volatility regimes change. Black swan events occur. No algorithmic system eliminates the risk of substantial loss.
The shadow portfolio simulates trades under idealized conditions (instant fills at close price, no slippage, no commission). Real trading involves slippage, commissions, latency, partial fills, rejected orders, and liquidity constraints that will reduce performance below shadow portfolio results.
Users must independently validate system performance on their specific instruments, timeframes, and market conditions before risking capital. Optimize parameters carefully and conduct extensive paper trading. Never risk more capital than you can afford to lose completely.
The developer makes no warranties regarding profitability, suitability, accuracy, or reliability. Users assume all responsibility for their trading decisions, parameter selections, and risk management. No guarantee of profit is made or implied.
Understand that most retail traders lose money. Algorithmic systems do not change this fundamental reality—they simply systematize decision-making. Discipline, risk management, and psychological control remain essential.
═══════════════════════════════════════════════════════
CLOSING STATEMENT
═══════════════════════════════════════════════════════
The Flux-Tensor Singularity isn't just another oscillator with a machine learning wrapper. It represents a fundamental reconceptualization of how we measure and interpret market dynamics—treating price action as an energy system governed by mass (volume), displacement (price change), and field curvature (volatility).
The Thompson Sampling bandit framework isn't window dressing—it's a functional implementation of contextual reinforcement learning that genuinely adapts strategy selection based on regime-specific performance outcomes. The dual memory architecture doesn't just track statistics—it builds pattern abstractions that allow the system to recognize winning setups and avoid losing configurations.
Most importantly, the shadow portfolio provides genuine ground truth. Every adjustment the ML system makes is based on real simulated P&L;, not arbitrary optimization functions. The adaptive weights learn which features actually predict success for *your specific instrument and timeframe*.
This system will not make you rich overnight. It will not win every trade. It will not eliminate drawdowns. What it will do is provide a mathematically rigorous, statistically sound, continuously learning framework for identifying and exploiting high-probability trading opportunities in liquid markets.
The accretion disk glows brightest near the event horizon. The tensor reaches critical mass. The singularity beckons. Will you answer the call?
"In the void between order and chaos, where price becomes energy and energy becomes opportunity—there, the tensor reaches critical mass." — FTS-PRO
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
RAFA's SMC Killer LITEWhat is the SMC Killer?
The Smart Money Concepts (SMC) Killer is a trading indicator that identifies high-probability entry points using three proven strategies:
Break of Structure (BOS) - Trades when price breaks key support/resistance levels
Fair Value Gap (FVG) - Enters when price fills gaps in the market
Order Blocks (OB) - Entry from institutional order clusters (optional display)
This indicator automatically:
✅ Calculates correct entry, take-profit, and stop-loss levels for your asset
✅ Tracks win/loss statistics in real-time
✅ Works on 30+ different futures contracts
✅ Adapts tick size and point value automatically
Asset Selection
Supported Assets
The indicator supports all major futures contracts:
Equity Futures:
ES (E-mini S&P 500)
NQ (E-mini NASDAQ 100)
YM (Mini Dow Jones)
NKD (Nikkei 225)
EMD (E-mini Midcap 400)
RTY (Russell 2000)
Currency Futures:
6A (Australian Dollar)
6B (British Pound)
6C (Canadian Dollar)
6E (Euro FX)
6J (Japanese Yen)
6S (Swiss Franc)
6N (New Zealand Dollar)
Agricultural Futures:
HE (Lean Hogs)
LE (Live Cattle)
GF (Feeder Cattle)
ZC (Corn)
ZW (Wheat)
ZS (Soybeans)
ZM (Soybean Meal)
ZL (Soybean Oil)
Energy Futures:
CL (Crude Oil)
QM (Mini Crude Oil)
NG (Natural Gas)
QG (E-mini Natural Gas)
HO (Heating Oil)
RB (RBOB Gasoline)
Metal Futures:
GC (Gold)
SI (Silver)
HG (Copper)
PL (Platinum)
PA (Palladium)
QI (E-mini Silver)
QO (E-mini Gold)
Micro Futures:
MES (Micro E-mini S&P 500)
MYM (Micro E-mini Dow Jones)
MNQ (Micro E-mini NASDAQ)
M2K (Micro Russell 2000)
MGC (E-Micro Gold)
M6A (E-Micro AUD/USD)
M6E (E-Micro EUR/USD)
MCL (Micro Crude Oil)
How to Select Your Asset
Open the indicator settings (click ⚙️)
Go to ASSET SELECT section
Select Asset Category (e.g., "Metal Futures")
Enter Select Asset Symbol (e.g., "GC" for Gold)
Click OK
The indicator will automatically load the correct:
✅ Tick size
✅ Point value
✅ Risk/reward calculations
Settings Configuration
ASSET SELECT Group
Asset Category: Choose from 6 categories
Select Asset Symbol: Enter symbol (ES, GC, CL, etc.)
STRUCTURE Group
Show Swing Structure: Display swing highs/lows
Swing Length: Bars used for pivot detection (default: 5)
Build Sweep: Show sweep formations (default: ON)
What it does: Identifies the market trend and key turning points
Teal/Green bars = Uptrend
Orange/Red bars = Downtrend
FVG Group
Enable FVG Entry: Use Fair Value Gap strategy
FVG Threshold: Sensitivity filter (default: 0)
What it does: Detects gaps in price action that indicate imbalance
Lower threshold = More signals
Higher threshold = Fewer, high-quality signals
RISK Group
Show Bracket: Display entry/TP/SL lines
Units/Contracts: Number of contracts to trade (default: 6)
Stop Loss ($): Risk amount per trade (default: $250)
Target ($): Profit target per trade (default: $1,000)
Example: If you select ES with $250 stop loss:
The indicator calculates: 250 ÷ (6 contracts × $50 per point) = 0.83 points
Your stop loss line appears 0.83 points below entry
TABLE Group
Show Statistics: Display results table
Position: Table location (default: top_right)
Year: Start tracking from this year
Month: Start tracking from this month
Day: Start tracking from this day
Trading Signals
BUY Signal 🟢
When you see a green "BUY" label below a candle:
Price is breaking higher (Break of Structure)
OR price is filling a gap (Fair Value Gap)
The indicator plots three lines:
Green line = Entry price
Lime/bright green line = Take Profit level
Red line = Stop Loss level
Action: Consider entering a LONG position at market or entry price
SELL Signal 🔴
When you see a red "SELL" label above a candle:
Price is breaking lower (Break of Structure)
OR price is filling a gap (Fair Value Gap)
The indicator plots three lines:
Red line = Entry price
Magenta/pink line = Take Profit level
Orange line = Stop Loss level
Action: Consider entering a SHORT position at market or entry price
Signal Confirmation
✅ Wait for confirmation - Only trade signals on confirmed (closed) bars
✅ Check the trend - Look at candle colors (green uptrend, orange downtrend)
✅ Risk/reward ratio - TP should be at least 2x your SL risk
Risk Management
Position Sizing Example
Trading Gold (GC) with ES Settings:
Units: 6 contracts
Stop Loss: $250
Target: $1,000
Tick Size: 0.1 (automatic for GC)
Point Value: $100 per point (automatic for GC)
Risk per trade: $250
Reward per trade: $1,000
Risk/Reward Ratio: 1:4 (Excellent!)
Stop Loss Strategy
Always place your stop loss below/above the entry lines
The red/orange line shows exactly where to place SL
Never move your stop loss against the trade (unless scaling)
Use hard stops - set them immediately upon entry
Take Profit Strategy
Take profits at the lime/magenta line (TP level)
Consider taking partial profits at 50% of target
Let remaining 50% run to full target
Use trailing stops if price moves in your favor
Risk Per Trade
Formula: (Stop Loss $) ÷ (Units × Point Value)
Example for ES:
Stop Loss: $250
Units: 6
Point Value: $50
Risk per point: 250 ÷ (6 × 50) = 0.83 points
Reading the Chart
Visual Elements
Candle Colors:
🟩 Green/Teal = Uptrend (higher highs and higher lows)
🟥 Orange/Red = Downtrend (lower highs and lower lows)
Signal Labels:
BUY (Green) = Long entry opportunity
SELL (Red) = Short entry opportunity
Bracket Lines:
Entry Line (Solid) = Your entry price
TP Line (Bright color) = Take profit target
SL Line (Red/Orange) = Stop loss level
Success Markers:
✓ (Green checkmark) = Trade hit TP (WIN)
✗ (Red X) = Trade hit SL (LOSS)
Statistics Table
What Each Column Means
📊 ← Current asset being traded
├── Total: Total signals generated (buys + sells)
├── Buy: Number of buy signals
├── Sell: Number of sell signals
├── Win ✓: Trades that hit take profit
├── Loss ✗: Trades that hit stop loss
├── W%: Win rate percentage (wins ÷ total trades)
└── Asset Info: Tick size and point value
Example Reading
📊 ES
Total: 15
Buy: 8
Sell: 7
Win ✓: 10
Loss ✗: 5
W%: 66.7%
Asset Info: Tick: 0.25 | PV: $50
This means:
15 total signals since tracking started
10 wins, 5 losses
66.7% win rate (Professional level!)
Trading ES with 0.25 tick and $50 point value
Trading Examples
Example 1: Gold (GC) Long Trade
Setup:
Asset: Metal Futures → GC
Stop Loss: $150
Target: $600
Units: 2 contracts
What happens:
You see a BUY label on a green candle
Entry line at 2050.0
TP line at 2050.6 (0.6 points higher = $600 profit)
SL line at 2049.85 (0.15 points lower = $150 loss)
Risk/Reward: 1:4 ✅
Trade Result:
Price moves to 2050.6 → Label shows ✓ = WIN
Table updates: Wins increases by 1, Win% increases
Example 2: Crude Oil (CL) Short Trade
Setup:
Asset: Energy Futures → CL
Stop Loss: $500
Target: $2,000
Units: 1 contract
What happens:
You see a SELL label on a red candle
Entry line at 78.50
TP line at 77.50 (1.00 lower = $1,000 profit)
SL line at 79.00 (0.50 higher = $500 loss)
Risk/Reward: 1:2 ✅
Trade Result:
Price drops to 77.50 → Label shows ✓ = WIN
Table updates: Wins increases by 1, Win% increases
Example 3: E-mini S&P (ES) Day Trading
Setup:
Asset: Equity Futures → ES
Stop Loss: $250
Target: $1,000
Units: 6 contracts
Swap Length: 5 (default)
Enable FVG: ON
Morning Session:
See BUY at 5860.25 (swing break)
Hit TP at 5861.08 = WIN ✓
Table shows: Total 1, Buy 1, Win 1, W% 100%
See SELL at 5861.50 (FVG entry)
Hit SL at 5860.67 = LOSS ✗
Table shows: Total 2, Sell 1, Win 1, L% 50%
By end of day: 4 wins, 1 loss, 80% win rate
Troubleshooting
Issue 1: No signals appearing
Solution:
Check if both Show Bracket is ON
Check if Enable FVG Entry is ON
Try changing Swing Length (lower = more signals)
Ensure you're on a 1-hour or higher timeframe
Check chart has enough data (scroll left to see history)
Issue 2: Signals appear but no entry lines
Solution:
Confirm Show Bracket is toggled ON
Check Stop Loss ()andTarget() and Target (
)andTarget() are reasonable amounts
Ensure your Units value is not 0
Try refreshing the chart
Issue 3: Asset not recognized
Solution:
Check spelling of symbol (ES, not E-S)
Verify asset is in the supported list
Check you're in the correct category
Try closing and reopening the chart
Issue 4: Wrong stop loss/target levels
Solution:
Verify correct asset is selected
Check Units setting matches your position size
Verify Stop Loss ($) and Target ($) amounts
Look at Asset Info in table to confirm tick size
Manually calculate: SL $ ÷ (Units × Point Value) = Points
Issue 5: Statistics table not showing
Solution:
Toggle Show Statistics OFF then back ON
Try changing Table Position
Refresh the chart
Check that Show Table is enabled in settings
Issue 6: Indicator acting "heavy" or laggy
Solution:
Turn off Show Swing Structure if not needed
Turn off Show Bracket if reviewing historical trades
Reduce chart's data window (don't load entire years)
Refresh the chart
Pro Tips 🚀
Tip 1: Start with Micro Futures
Micro contracts (MES, MNQ, MCL) have lower cost
Perfect for learning the strategy
Same quality signals, smaller risk
Tip 2: Trade During Peak Hours
Equity Futures: 9:30-16:00 ET (Regular session)
Energy: 18:00-16:00 CT (After hours active)
Metals: 18:00-17:00 CT (Most liquid)
Currencies: 5:00 PM - 4:00 PM ET (24-5 market)
Tip 3: Combine Timeframes
Look for entry on 1-hour chart
Confirm on 15-minute chart
Execute on 5-minute breakout
More confluence = higher probability
Tip 4: Track Your Trades
Keep notes on WIN/LOSS trades
Identify patterns in your losses
Adjust settings based on performance
Use Win% table to monitor improvement
Tip 5: Risk Management First
Never risk more than 2% of account per trade
Respect your stop loss (don't move it)
Take profits when levels are hit
Be patient for high-probability setups
Tip 6: Adjust for Market Conditions
Trending markets: Increase Swing Length (6-8)
Choppy markets: Decrease Swing Length (2-4)
Low volatility: Reduce Stop Loss $
High volatility: Increase Target $
Quick Reference Card
────────────────────────────────────────────────────
SMC KILLER QUICK START ─────────────────────────────────────────────────────
│ 1. Select Asset Category & Symbol
│ 2. Set Units (contracts)
│ 3. Set Stop Loss ($) - your max risk
│ 4. Set Target ($) - your profit goal
│ 5. Wait for BUY (green) or SELL (red) signal
│ 6. Place entry at the entry line
│ 7. Place stop at the red/orange line
│ 8. Place take-profit at the lime/magenta line
│ 9. Close trade when line closes (✓ or ✗)
│ 10. Review statistics and adjust next trade
└─────────────────────────────────────────────────────
BUY Signal = Break Higher OR Fill Gap = LONG
SELL Signal = Break Lower OR Fill Gap = SHORT
Green candles = Uptrend
Orange candles = Downtrend
✓ = Win (took profit)
✗ = Loss (hit stop)
Support & Updates
Check settings are correct for your asset
Ensure adequate chart data is loaded
Test on demo account first
Start with smallest position size
Track performance over 20+ trades
Volume Pressure and PercentVPP Volume Pressure and Percentage Indicator with a Volume Trendline that indicates which side is driving the flow.
Features:
1. Buy/Sell Pressure Bars (Core Volume Split)
The indicator separates each candle’s volume into buy volume (green) above the zero line and sell volume (red) below it. This gives you a real-time visualization of which side is more aggressive within the current bar. Instead of waiting for prices to move or candles to close, you can instantly see whether buyers or sellers are stepping in.
2. Dynamic Total Volume (Invisible Histogram + Status Line Color)
The total volume of each bar is tracked behind the scenes and displayed in the pinned status line using a dynamic color—green when buyers dominate, red when sellers dominate. The histogram for total volume is invisible to keep the chart clean, but the total volume figure stays visible and changes color based on who is in control. This gives you instant confirmation of whether institutional-sized volume supports the direction shown by the buy/sell pressure, which is especially valuable when evaluating the risk or conviction behind a potential entry.
3. Percentage Mode (% of Bar Volume)
When toggled on, the indicator converts each bar into percent buy vs percent sell, normalizing all flow to a 0–100% scale. This mode is incredibly useful when comparing pressure across different times of day, gaps, or varying volume conditions—such as early morning spikes versus lunchtime chop. By removing absolute volume from the equation, you gain a clean look at the actual imbalance between buyers and sellers.
4. 70% Pressure Band (Imbalance Threshold Zone)
In percentage mode, the indicator displays a subtle 70% band (a light gray zone) above and below the zero line, showing where buy or sell pressure reaches extreme dominance (≥70%). When a bar’s buy or sell percentage enters this zone, it highlights moments of exhaustion, acceleration, or potential reversal. The band acts like a real-time overbought/oversold gauge specifically for volume imbalance, not price.
5. Trend Line (Net Pressure Trend / Reversal Detector)
The trend line smooths out the net volume pressure (buy volume minus sell volume or its percentage equivalent) and shows the overall direction of order flow. When the line slopes upward, buyers are gaining control; when it slopes downward, sellers are taking over. This trend line acts as a real-time momentum indicator based directly on flow rather than price. Because it reacts quickly to intrabar shifts in buy/sell pressure, it often turns before price does—giving you a measurable timing edge.
6. Auto-Selecting Trend Source (Volume Net, Percent Net, or CVD)
The indicator lets you choose how the trend line is calculated: Volume Net (buy minus sell volume), Percent Net (normalized imbalance), or CVD (Cumulative Volume Delta) for long-term flow bias. The default “Auto” mode automatically switches between Volume Net and Percent Net depending on which view you’re using. This flexibility allows the trend line to remain meaningful whether you’re analyzing raw volume or normalized percentage data.
7. Pinned (Status Line) Totals in K/M/B Format
Regardless of whether you’re in volume or percentage mode, the indicator always displays Total Volume, Buy Volume, and Sell Volume in the status line using abbreviated K, M, B formatting. These values update in real time and are color-coded: green for bullish dominance, red for bearish. This gives you a concise snapshot of order flow strength on every bar.
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How To Use:
Support Level Zones
• Watch for Buy bars increasing + Trend line flipping up right at or slightly below support.
• This often signals absorption — market makers filling large buy orders before reversal.
• Confirmation: Price reclaims VWAP ... enter calls / longs.
Resistance Level Zones
• Watch for Sell bars increasing + Trend line flattening/turning down near resistance.
• This signals distribution or stop runs.
• Confirmation: Price rejects VWAP ... enter puts / shorts.
Breakout Traps
• Sometimes you’ll see price break a level, but the flow doesn’t confirm (buy volume doesn’t expand).
• That’s a false breakout — fade it with options opposite the move.
Lynie's V9 SELL🟢🔴 Lynie’s V8 — BUY & SELL (Mirrored, Interlocking System)
Lynie’s V8 is a paired long/short engine built as two mirrored scripts—Lynie’s V8 BUY and Lynie’s V8 SELL—that read price the same way, flip conditions symmetrically, and manage trades with the exact logic on opposite sides. Use either one standalone or run both together for full two-sided automation of entries, re-entries, caution states, and adaptive SL/TP.
✳️ What “mirrored” means here
Supertrend Tri-Stack (10/11/12):
BUY: ST10 primary pierce; ST12 fallback; “PAG Buy” when price pierces any ST while above the other two.
SELL: Exact inverse—ST10 primary pierce down; ST12 fallback; “PAG Sell” when price pierces any ST while below the other two.
Re-Enter Clusters:
BUY: Ratcheted up (Heikin-Ashi green holds/tightens).
SELL: Ratcheted down (Heikin-Ashi red holds/tightens).
Both sides use the same cluster age/decay math, care penalties, session awareness, and fast-candle tightening.
Care Flags (context risk):
Ichimoku, MACD, RSI combine into single and paired flags that tighten or widen offsets on both sides with the same scoring.
VWAP–EMA50 (5m) cluster gate:
Identical distance checks for BUY/SELL. When the mean cluster is present, offsets and labels adapt (tighter/“riskier scalp” messaging).
Golden Pocket A/B/C (prev-day):
Same fib boxes & labeling (gold tone) on both sides to call out TP-friendly zones.
SL/TP Envelope:
Shared dynamic engine: per-bar decay, fast-candle expansion, and care-based compress/relax—all mirrored for up/down.
Caution Labels:
BUY side prints CAUTION SELL if HA flips red inside an active long cluster.
SELL side prints CAUTION BUY if HA flips green inside an active short cluster.
Same latching & auto-release behavior.
🧠 Core workflow (both sides)
Primary trigger via ST10 pierce (structure shift) with an ST12 fallback when ST10 didn’t qualify.
PAG Mode when price is already on the right side of the other two STs—strongest conviction.
Cluster phase begins after a signal: ratcheted re-entry level, session-aware offsets, dynamic tightening on fast bars.
Care system shapes every re-entry & SL/TP label (Ichi/MACD/RSI combos + VWAP/EMA gate + QQE).
Protective layer: SL-wick and SL-body logic, caution flips, and “hold 1 bar” cluster carry after SL to avoid whipsaw spam.
🔎 Labels & messages (shared vocabulary)
Lynie’s / Lynie’s+ / Lynie’s++ — strength tiers (ST12 involvement & clean context).
Re-Enter / Excellent Re-Enter — cluster pullback quality; ratchet shows the “must-hold” zone.
SL&TP (n) — live offset multiplier the engine is using right now.
CAUTION BUY / CAUTION SELL — HA flip against the active side inside the cluster.
Restart Next Candle — visual cue to re-arm after a confirmed signal bar.
⚡ Why run both together
Continuity: When a long cycle ends (SL or caution degradation), the SELL engine is already tracking the inverse without re-tuning.
Symmetry: Same math, same signals, opposite direction—no hidden biases.
Coverage: Trend hand-offs are cleaner; you don’t miss early shorts after a long fade (and vice versa).
🔧 Recommended usage
Intraday futures (ES/NQ) or any liquid market.
Keep the VWAP–EMA cluster ON; it filters FOMO chases.
Honor Caution flips inside cluster—scale down or wait for the next clean re-enter.
Treat Golden Zones as TP magnets, not guaranteed reversals.
📌 Notes
Both scripts are Pine v6 and independent. Load BUY and SELL together for the full experience.
All offsets (re-enter & SL/TP) are visible in labels—so you always know why a zone is where it is.
Alerts are provided for signals, re-enter hits, caution, and SL events on both sides.
Summary: Lynie’s V8 BUY & SELL are vice-versa twins—one framework, two directions—delivering consistent entries, adaptive re-entries, and contextual risk management whether the market is pressing up or breaking down.
Khosro XAUUSD Strategy [TradingFinder] Trading Room Hunter Setup🔵 Introduction
The Trading Room Hunter (TRH) strategy is an analytical model based on the Smart Money Concept, developed by Khosro, an Iranian international trader based in Dubai. This approach is built upon a deep understanding of liquidity engineering, market structure shifts, and institutional order flow. Its core objective is to identify the so-called TRH Zone, the area where market liquidity gets trapped and institutional investors begin accumulating positions. Unlike traditional indicator-based methods, the TRH Zone focuses purely on price behavior and supply & demand dynamics to pinpoint the most precise reversal zones in the market.
Within Smart Money logic, every impulsive move in price results from the displacement or absorption of liquidity in a specific range. In the TRH model, the last pivot preceding the impulsive move (Origin Pivot) is defined as the Distal Line, and the Break Candle, which disrupts the market structure, forms the Proximal Line. The area between these two points defines the Trading Room Hunter Zone, a reaction zone where price, after creating a displacement or Break of Structure (BoS), often returns to fill an imbalance and provide a precision entry opportunity.
In essence, the TRH Zone is the region where smart money seeks re-entry after a liquidity sweep and a confirmed CHoCH or BoS. It frequently lies between supply/demand boundaries and fair value gaps (FVGs), forming one of the strongest decision-making frameworks within modern price-action theory. Due to its structural accuracy, the TRH setup can also function as a Set & Forget Setup, where the trader defines the zone, places a limit order, and lets the market naturally react, eliminating emotional decision-making and allowing for automated execution aligned with institutional logic.
🔵 How to Use
In the TRH strategy, entries are taken based on price returning to the area between the last impulsive pivot and the break candle. This range (the TRH Zone) represents the region where liquidity from the previous move remains concentrated. Before continuing its main direction, price often revisits this zone to fill imbalances or mitigate unfilled orders. The logic is simple: every explosive move originates from a point where large orders were executed, and TRH precisely highlights that institutional footprint.
🟣 Bullish Setup
When the market breaks a structural high after a strong bearish leg, liquidity shifts from sellers to buyers. The last bearish candle before the breakout marks the origin of the bullish move, and the zone between that candle and the break candle becomes the smart-money entry area. As price revisits this zone and signs of exhaustion in selling pressure appear, that’s the optimal point for a long position. Stop-loss is placed slightly below the origin pivot, and targets are set at the next supply zone or upper liquidity pool.
🟣 Bearish Setup
Conversely, when the market breaks a structural low after a sharp bullish leg, liquidity transitions from buyers to sellers. The last bullish candle before the drop is identified as the origin pivot, while the bearish break candle defines the lower boundary of the zone. The range between these two points forms the TRH Supply Zone, where late buyers are trapped and fresh institutional selling begins. As price retraces into this zone, short entries can be placed near the upper boundary, with stops above the pivot and targets toward the next liquidity pool below.
Because of its structural precision and clearly defined reaction behavior, TRH is one of the most effective Set & Forget setups in Smart Money trading. Simply mark the zone, place your order, and let the market do the rest.
🔵Setting
🟣 Spike Filter | Movement
Minimum Spike Bars : Defines the minimum number of consecutive candles required for a valid spike.
Movement Power : Enables or disables the momentum-based spike filter.
Movement Power Level : Sets the strength threshold; higher values filter out weaker moves and only detect strong spikes.
Pivot Period : Defines the lookback range used to detect swing highs and swing lows in market structure. A higher value smooths out smaller fluctuations and focuses on major pivots, while a lower value increases sensitivity and identifies minor turning points more frequently.
🟣 Position Management
Stop-Loss Threshold : Enables or disables the stop-loss threshold feature.
Stop-Loss Threshold Value : Defines the value of the stop-loss threshold for risk management.
Risk-Reward Ratio : Sets the desired risk-to-reward ratio (e.g., 1:1 or 1:2).
Wide Zone Filter : Filters out zones that exceed a defined width threshold, preventing detection of overly broad TRH areas.
🟣 Display Settings
Display Mode : Chooses between Setup (showing setups) or Signal (showing trade signals).
Show Entry Levels : Displays entry levels on the chart (buy/sell zones) when enabled
Only Display the Last Position : Displays only the most recent position on the chart when enabled.
Setup Width Drawing : Adjusts the visual width of the setup drawings on the chart for better visibility.
🔵 Conclusion
The TRH strategy is a precise structural model of liquidity flow that identifies zones where smart money is most likely to enter and where price is most likely to react. By combining the Origin Pivot and Break Candle, TRH isolates the key areas that drive institutional order flow. Without relying on indicators, it focuses purely on price structure, making it highly effective for both reactive entries and Set & Forget setups.
Ultimately, TRH creates a balance between market structure and liquidity flow, enabling traders to identify institutional decision zones on the chart with minimal risk and maximum clarity
cd_VWAP_mtg_CxCd_VWAP_mtg_Cx
Overview
The most important condition for being successful and profitable in the market is to consistently follow the same rules without compromise, while the price constantly moves in countless different ways.
Regardless of the concept or trading school, those who have rules win.
In this indicator, we will define and use three main sections to set and apply our rules.
The indicator uses the VWAP (Volume Weighted Average Price) — price weighted by volume.
Two VWAPs can be displayed either by manually entering date and time, or by selecting from the menu.
From the menu, you can select the following reference levels:
• HTF Open: Opening candle of the higher timeframe
• ATH / ATL: All-Time High / All-Time Low candles
• PMH / PML, PWH / PWL, PDH / PDL, PH4H / PH4L: Previous Month, Week, Day, or H4 Highs/Lows
• MH / ML, WH / WL, DH / DL, H4H / H4L: Current Month, Week, Day, or H4 Highs/Lows
Additionally, it includes:
• Mitigation / Order Block zones (local buyer-seller balance) across two timeframes.
• Buy/Sell Side Liquidity levels (BSL / SSL) from the aligned higher timeframe (target levels).
________________________________________
Components and Usage
1 – VWAP
Calculated using the classical method:
• High + Volume for the upper value
• Close + Volume for the middle value
• Low + Volume for the lower value
The VWAP is displayed as a colored band, where the coloring represents the bias.
Let’s call this band FVB (Fair Value Band) for ease of explanation.
The FVB represents the final line of defense, the buyer/seller boundary, and in technical terms, it can be viewed as premium/discount zones or support/resistance levels.
Within this critical area, the strong side continues its move, while the weaker side is forced to retreat.
But does the side that breaks beyond the band always keep going?
We all know that’s not always the case — in different pairs and timeframes, price often violates both the upper and lower edges multiple times.
To achieve more consistent analysis, we’ll define a new set of rules.
________________________________________
2 – Mitigation / Order Blocks
In trading literature, there are dozens of different definitions and uses of mitigation or order blocks.
Here, we will interpret the candlesticks to create our own definition, and we’ll use the zones defined by candles that fit this pattern.
For simplicity, let’s abbreviate mitigation as “mtg.”
For a candle to be selected as an mtg, it must clearly show strength from one side (buyers or sellers) — which can also be observed visually on the chart.
________________________________________
Bullish mtg criteria:
1. The first candle must be bullish (close > open) → buyers are strong.
2. The next candle makes a new high (buyers push higher) but fails to close above and pulls back to close inside the previous range → sellers react.
It also must not break the previous low → buyers defend.
3. In the following candle(s), as long as the first candle’s low is protected and the second candle’s high is broken, it indicates buyer strength → a bullish mtg is confirmed.
When price returns to this zone later (gets mitigated), the expectation is that the zone holds and price pushes upward again.
If the low is violated, the mtg becomes invalid.
In technical terms:
If the previous candle’s high is broken but no close occurs above it, the expectation is a reversal move that will retest its low.
Question:
What if the low is protected and in the next candle(s) a new high forms?
Answer: → Bullish mtg.
Bearish mtg (opposite)
3 – Buy/Sell Side Liquidity Levels
With the help of the aligned higher timeframe (swing points), we will define our market structure framework and set our liquidity targets accordingly.
Let’s put the pieces together.
If we continue explaining from a trade-focused perspective, our first priority should be our bias — our projection or expectation of the market’s potential movement.
We will determine this bias using the FVB.
Since we know the band often gets violated on both sides, we want the price action to convince us of its strength.
To do that, we’ll use the first candle that closes beyond the band.
The distance from that candle’s high to low will be our threshold range
Bullish level = high + (candle length × coefficient)
Bearish level = low - (candle length × coefficient)
When the price closes beyond this threshold, it demonstrates strength, and our bias will now align in that direction.
How long will this bias remain valid?
→ Until a closing candle appears on the opposite side of the band.
If a close occurs on the opposite side, then a new bias will only be confirmed once the new threshold level is broken.
During the period in between, we have no bias.
Let’s continue on the chart:
Now that our bias has been established, where and how do we look for trade opportunities?
There are two possible entry approaches:
• Aggressive entry: Enter immediately with the breakout.
• Conservative entry: Wait for a pullback and enter once a suitable structure forms.
(The choice depends on the user’s preference.)
At this stage, the user can apply their own entry model. Let’s give an example:
Let’s assume we’re looking for setups using HTF sweep + LTF CISD confirmation.
Once our bias turns bearish, we look for an HTF sweep forming on or near an FVB or mtg block, and then confirm the entry with a CISD signal.
In summary:
• FVB defines the bias, the entry zone, and the target zone.
• Mtg blocks represent entry zones.
• BSL / SSL levels suggest target zones.
Overlapping FVB and mtg blocks are expected to be more effective.
The indicator also provides an option for a second FVB.
A band attached to a lower timeframe can be used as confirmation.
• Main band: Bias + FVB
• Extra band: Entry trigger confirmed by a close beyond it.
Mtg blocks can provide trade entry opportunities, especially when the price is moving strongly in one direction (flow).
Consecutive or complementary mtg blocks indicate that the price is decisive in one direction, while sometimes also showing areas where we should wait before entering.
Mtg blocks that contain an FVG (Fair Value Gap) within their body are expected to be more effective.
Settings:
The default values are set to 1-3-5m, optimized for scalping trades.
VWAP settings:
Main VWAP (FVB):
• Can be set by selecting a start time, manually entering date and time, or choosing a predefined level.
Extra VWAP (FVB):
• Set from the menu. If not needed, select “none.”
• Visibility, color, and fill settings for VWAP are located here.
• Threshold levels visibility and color options are also in this section.
• The multiplier is used for calculating the threshold level.
Important:
• If the Extra VWAP is selected but not displayed, you need to increase the chart timeframe.
o Example: If the chart is on 3m and you select WH from the extra options, it will not display correctly.
• Upper limits for VWAP:
o 1m and 3m charts: daily High/Low
o 5m chart: weekly High/Low
________________________________________
Mtg Settings:
• Visibility and color settings for blocks are configured here.
• To display on a second timeframe, the box must be checked and the timeframe specified.
• Optional display modes: “only active blocks,” “only last violated mtg,” or “all.”
• For confirmation and removal criteria, choosing high/low or close determines the source used for mtg block formation and deletion conditions.
BSL/SSL Settings:
• Visibility, color, font size, and line style can be configured in this section.
When “Auto” is selected, the aligned timeframe is determined automatically by the indicator, while in manual mode, the user defines the timeframe.
Final Words:
Simply opening trades every time the price touches the VWAP or mtg blocks will not make you a profitable trader. Searching for setups with similar structures while maintaining proper risk management will yield better results in the long run.
I would be happy to hear your feedback and suggestions.
Happy trading!
MULTI-CONDITION RSI SIGNAL GENERATOR═══════════════════════════════════════════════
MULTI-CONDITION RSI SIGNAL GENERATOR
═══════════════════════════════════════════════
OVERVIEW:
This indicator generates trading signals based on Relative Strength Index (RSI) movements with multiple confirmation layers designed to filter false signals and identify high-probability reversal opportunities.
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WHAT MAKES THIS ORIGINAL:
═══════════════════════════════════════════════
Unlike basic RSI indicators that simply plot overbought/oversold crossovers, this system combines FOUR distinct confirmation mechanisms:
1. PERSISTENCE FILTERING - Requires RSI to remain in extreme zones for a minimum duration
2. LOOKBACK VALIDATION - Verifies recent extreme zone visits before signaling
3. DIVERGENCE DETECTION - Identifies price/RSI divergence for stronger signals
4. MOMENTUM CONFIRMATION - Provides trend-continuation entries via midline crosses
This multi-layered approach significantly reduces whipsaw trades that plague simple RSI crossover systems.
═══════════════════════════════════════════════
HOW IT WORKS (TECHNICAL METHODOLOGY):
═══════════════════════════════════════════════
STEP 1: RSI CALCULATION
- Standard RSI calculation using user-defined period (default: 14)
- Monitors two extreme zones: Overbought (default: 70) and Oversold (default: 30)
STEP 2: PERSISTENCE FILTERING
The script counts how many bars RSI has spent in extreme zones within the lookback period:
- For overbought signals: Counts bars where RSI > 70
- For oversold signals: Counts bars where RSI < 30
- Signal only triggers if count >= Minimum Duration (default: 4 bars)
This filters out brief spikes that immediately reverse, focusing on sustained extreme conditions that are more likely to lead to genuine reversals.
STEP 3: LOOKBACK VALIDATION
- Checks if RSI reached extreme zones within the Lookback Bars period (default: 20)
- Uses ta.highest() and ta.lowest() functions to verify recent extremes
- Ensures we're trading reversals from meaningful extremes, not random crossovers
STEP 4: BASIC SIGNAL GENERATION
- BUY SIGNAL: RSI crosses above the oversold level (30) after meeting persistence and lookback conditions
- SELL SIGNAL: RSI crosses below the overbought level (70) after meeting persistence and lookback conditions
STEP 5: DIVERGENCE DETECTION
The script identifies two types of divergence over the Divergence Lookback period (default: 5 bars):
A) BULLISH DIVERGENCE (indicates potential upward reversal):
- Price makes a lower low (current low < previous low)
- RSI makes a higher low (current RSI low > previous RSI low)
- Suggests weakening downward momentum
B) BEARISH DIVERGENCE (indicates potential downward reversal):
- Price makes a higher high (current high > previous high)
- RSI makes a lower high (current RSI high < previous RSI high)
- Suggests weakening upward momentum
STEP 6: STRONG SIGNAL CONFIRMATION
- STRONG BUY: Basic buy signal + bullish divergence present
- STRONG SELL: Basic sell signal + bearish divergence present
- These represent the highest-probability setups
STEP 7: MOMENTUM SIGNALS (OPTIONAL)
- MOMENTUM BUY: RSI crosses above 50 after being oversold (trend continuation)
- MOMENTUM SELL: RSI crosses below 50 after being overbought (trend continuation)
- Smaller signals for traders who want trend-following entries
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SIGNAL TYPES AND VISUAL INDICATORS:
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📈 GREEN TRIANGLE (below bar) - Standard Buy Signal
RSI crossed above oversold level with confirmation filters
📉 RED TRIANGLE (above bar) - Standard Sell Signal
RSI crossed below overbought level with confirmation filters
🔵 BLUE TRIANGLE (below bar) - Strong Buy Signal
Buy signal + bullish divergence (HIGHEST PRIORITY)
🟣 PURPLE TRIANGLE (above bar) - Strong Sell Signal
Sell signal + bearish divergence (HIGHEST PRIORITY)
🟢 GREEN CIRCLE (small) - Momentum Buy
RSI crosses above 50 after oversold conditions
🔴 RED CIRCLE (small) - Momentum Sell
RSI crosses below 50 after overbought conditions
BACKGROUND SHADING:
- Light red background: RSI currently overbought
- Light green background: RSI currently oversold
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PARAMETER SETTINGS:
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1. OVERBOUGHT LEVEL (default: 70, range: 50-90)
- Higher values = fewer but stronger overbought signals
- Lower values = more sensitive to overbought conditions
- Recommended: 70 for standard markets, 80 for crypto/volatile assets
2. OVERSOLD LEVEL (default: 30, range: 10-50)
- Lower values = fewer but stronger oversold signals
- Higher values = more sensitive to oversold conditions
- Recommended: 30 for standard markets, 20 for crypto/volatile assets
3. RSI PERIOD (default: 14, range: 2-50)
- Standard RSI calculation period
- Lower = more sensitive/faster signals
- Higher = smoother/slower signals
- Recommended: 14 (industry standard)
4. MINIMUM DURATION (default: 4, range: 1-20)
- Required bars in extreme zone before signal
- Higher values = fewer signals but better quality
- Lower values = more signals but more false positives
- Recommended: 3-5 for day trading, 5-10 for swing trading
5. LOOKBACK BARS (default: 20, range: 5-100)
- How far back to check for extreme zone visits
- Should match your typical trading timeframe
- Recommended: 20 for intraday, 50 for daily charts
6. DIVERGENCE LOOKBACK (default: 5, range: 2-20)
- Period for comparing price/RSI highs and lows
- Lower values = more frequent divergence signals
- Higher values = more significant divergences
- Recommended: 5-10 depending on timeframe
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HOW TO USE THIS INDICATOR:
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RECOMMENDED TRADING APPROACH:
1. PRIMARY ENTRIES: Focus on Strong Buy/Sell signals (blue/purple triangles)
- These have the highest win rate due to divergence confirmation
- Wait for price action confirmation (support/resistance, candlestick patterns)
2. SECONDARY ENTRIES: Regular Buy/Sell signals (green/red triangles)
- Use these when Strong signals are infrequent
- Require additional confirmation from other indicators or chart patterns
3. TREND CONTINUATION: Momentum signals (small circles)
- Best used when overall trend is clear
- Not recommended for reversal trading
4. FILTER TRADES: Use background shading as context
- Be cautious entering longs when background is red (overbought)
- Be cautious entering shorts when background is green (oversold)
RISK MANAGEMENT GUIDELINES:
- Never risk more than 2-5% of capital per trade
- Use stop losses below recent swing lows (buys) or above swing highs (sells)
- Target at least 1.5:1 reward-to-risk ratio
- Consider position sizing based on signal strength
TIMEFRAME RECOMMENDATIONS:
- 15min - 1hour: Day trading with adjusted parameters (lower minimum duration)
- 4hour - Daily: Swing trading with default parameters
- Weekly: Position trading with increased lookback periods
COMPLEMENTARY TOOLS:
This indicator works best when combined with:
- Support and resistance levels
- Trend indicators (moving averages, trend lines)
- Volume analysis
- Price action patterns (engulfing candles, pin bars)
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LIMITATIONS AND CONSIDERATIONS:
═══════════════════════════════════════════════
- This is NOT a standalone trading system - requires additional analysis
- RSI-based strategies perform best in ranging/choppy markets
- May generate fewer signals in strong trending markets
- Divergence signals can be early - wait for price confirmation
- Not recommended for highly illiquid assets
- Backtest on your specific market before live trading
- No indicator is 100% accurate - always use proper risk management
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TECHNICAL NOTES:
═══════════════════════════════════════════════
- Code is original and does not reuse external libraries
- Uses Pine Script v5 native functions only
- Alert conditions included for all signal types
- No repainting - signals appear and remain fixed
- Efficient calculation methods minimize processing load
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ALERT SETUP:
═══════════════════════════════════════════════
Four alert conditions are available:
1. "Buy Alert" - Triggers on standard buy signals
2. "Sell Alert" - Triggers on standard sell signals
3. "Strong Buy Alert" - Triggers on divergence-confirmed buy signals
4. "Strong Sell Alert" - Triggers on divergence-confirmed sell signals
To set up alerts: Right-click chart → Add Alert → Select desired condition
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This indicator is provided for educational and informational purposes. Always practice proper risk management and never trade with money you cannot afford to lose.
Adaptive Volume Delta Map---
📊 Adaptive Volume Delta Map (AVDM)
What is Adaptive Volume Delta Map (AVDM)?
The Adaptive Volume Delta Map (AVDM) is a smart, multi-timeframe indicator that visualizes buy and sell volume imbalances directly on the chart.
It adapts automatically to the best available data resolution (tick, second, minute, or daily), allowing traders to analyze market activity with micro-level precision .
In addition to calculating volume delta (the difference between buying and selling pressure), AVDM can display a Volume Distribution Map — a per-price-level visualization showing how volume is split between buyers and sellers.
Key Features
✅ Adaptive Resolution Selection — Automatically chooses the highest possible data granularity — from tick to daily timeframe.
✅ Volume Delta Visualization — Displays delta candles reflecting the dominance of buyers (green), sellers (red), and delta (orange).
✅ Per-Level Volume Map (optional) — Shows detailed buy/sell volume distribution per price level, grouped by `Ticks Per Row`.
✅ Bid/Ask Classification — When enabled, AVDM uses bid/ask logic to classify trade direction with greater accuracy.
✅ Smart Auto-Disable Protection — Automatically disables volume map if too many price levels (>50) are detected — preventing performance degradation.
Inputs Overview
Use Seconds Resolution — Enables use of second-level data (if your TradingView subscription allows it).
Use Tick Resolution — Enables tick-based analysis for the most detailed view. If available, enable both tick and seconds resolution.
Use Bid/Ask Calculated — Uses bid/ask midpoint logic to classify trades.
Show Volume Distribution — Toggles per-price-level buy/sell volume visualization.
Ticks Per Row — Controls how many ticks are grouped per volume level. Reduce this value for finer detail, or increase it to reduce visual load.
Calculated Bars — Sets how many historical bars the indicator should process. Higher value increases accuracy but may impact performance.
How to Use
1. Add the indicator to your chart.
2. Ensure that your symbol provides volume data (and preferably tick or second-level data).
3. The indicator will automatically select the optimal timeframe for detailed calculation.
4. If your TradingView subscription allows second-level data , enable “Use Seconds Resolution.”
5. If your subscription allows tick-level data , enable both “Use Tick Resolution” and “Use Seconds Resolution.”
6. Adjust the “Calculated Bars” input to set how many historical bars the indicator should process.
7. Observe the Volume Delta Candles :
* Green = Buy pressure dominates
* Red = Sell pressure dominates
8. To see buy/sell clustering by price, enable “Show Volume Distribution.”
9. If the indicator disables the map and shows:
" Volume Distribution disabled: Too many price levels detected (>50). Try decreasing 'Ticks Per Row' or using a lower chart resolution. If you don’t care about the map, just turn off 'Show Volume Distribution'. "
— follow the instructions to reduce chart load.
Notes
* Automatically adapts to your chart’s resolution and data availability.
* If your symbol doesn’t provide volume data, a runtime warning will appear.
* Works best on futures , FX , and crypto instruments with high-frequency volume streams.
Why Traders Love It
AVDM combines adaptive resolution , volume delta analysis , and visual distribution mapping into one clean, efficient tool.
Perfect for traders studying:
* Market microstructure
* Aggressive vs. passive participation
* Volume absorption
* Order flow imbalance zones
* Delta-based divergence signals
Technical Highlights
* Built with Pine Script v6
* Adaptive resolution logic (`security_lower_tf`)
* Smart memory-safe map rendering
* Dynamic bid/ask classification
* Automatic overload protection
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RSI ADX Bollinger Analysis High-level purpose and design philosophy
This indicator — RSI-ADX-Bollinger Analysis — is a compact, educational market-analysis toolkit that blends momentum (RSI), trend strength (ADX), volatility structure (Bollinger Bands) and simple volumetrics to provide traders a snapshot of market condition and trade idea quality. The design philosophy is explicit and layered: use each component to answer a different question about price action (momentum, conviction, volatility, participation), then combine answers to form a more robust, explainable signal. The mashup is intended for analysis and learning, not automatic execution: it surfaces the why behind signals so traders can test, learn and apply rules with risk management.
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What each indicator contributes (component-by-component)
RSI (Relative Strength Index) — role and behavior: RSI measures short-term momentum by comparing recent gains to recent losses. A high RSI (near or above the overbought threshold) indicates strong recent buying pressure and potential exhaustion if price is extended. A low RSI (near or below the oversold threshold) indicates strong recent selling pressure and potential exhaustion or a value area for mean-reversion. In this dashboard RSI is used as the primary momentum trigger: it helps identify whether price is locally over-extended on the buy or sell side.
ADX (Average Directional Index) — role and behavior: ADX measures trend strength independently of direction. When ADX rises above a chosen threshold (e.g., 25), it signals that the market is trending with conviction; ADX below the threshold suggests range or weak trend. Because patterns and momentum signals perform differently in trending vs. ranging markets, ADX is used here as a filter: only when ADX indicates sufficient directional strength does the system treat RSI+BB breakouts as meaningful trade candidates.
Bollinger Bands — role and behavior: Bollinger Bands (20-period basis ± N standard deviations) show volatility envelope and relative price position vs. a volatility-adjusted mean. Price outside the upper band suggests pronounced extension relative to recent volatility; price outside the lower band suggests extended weakness. A band expansion (increasing width) signals volatility breakout potential; contraction signals range-bound conditions and potential squeeze. In this dashboard, Bollinger Bands provide the volatility/structural context: RSI extremes plus price beyond the band imply a stronger, volatility-backed move.
Volume split & basic MA trend — role and behavior: Buy-like and sell-like volume (simple heuristic using close>open or closeopen) or sell-like (close1.2 for validation and compare win rate and expectancy.
4. TF alignment: Accept signals only when higher timeframe (e.g., 4h) trend agrees — compare results.
5. Parameter sensitivity: Vary RSI threshold (70/30 vs 80/20), Bollinger stddev (2 vs 2.5), and ADX threshold (25 vs 30) and measure stability of results.
These exercises teach both statistical thinking and the specific failure modes of the mashup.
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Limitations, failure modes and caveats (explicit & teachable)
• ADX and Bollinger measures lag during fast-moving news events — signals can be late or wrong during earnings, macro shocks, or illiquid sessions.
• Volume classification by open/close is a heuristic; it does not equal TAPEDATA, footprint or signed volume. Use it as supportive evidence, not definitive proof.
• RSI can remain overbought or oversold for extended stretches in persistent trends — relying solely on RSI extremes without ADX or BB context invites large drawdowns.
• Small-cap or low-liquidity instruments yield noisy band behavior and unreliable volume ratios.
Being explicit about these limitations is a strong point in a TradingView description — it demonstrates transparency and educational intent.
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Originality & mashup justification (text you can paste)
This script intentionally combines classical momentum (RSI), volatility envelope (Bollinger Bands) and trend-strength (ADX) because each indicator answers a different and complementary question: RSI answers is price locally extreme?, Bollinger answers is price outside normal volatility?, and ADX answers is the market moving with conviction?. Volume participation then acts as a practical check for real market involvement. This combination is not a simple “indicator mashup”; it is a designed ensemble where each element reduces the others’ failure modes and together produce a teachable, testable signal framework. The script’s purpose is educational and analytical — to show traders how to interpret the interplay of momentum, volatility, and trend strength.
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TradingView publication guidance & compliance checklist
To satisfy TradingView rules about mashups and descriptions, include the following items in your script description (without exposing source code):
1. Purpose statement: One or two lines describing the script’s objective (educational multi-indicator market overview and idea filter).
2. Component list: Name the major modules (RSI, Bollinger Bands, ADX, volume heuristic, SMA trend checks, signal tracking) and one-sentence reason for each.
3. How they interact: A succinct non-code explanation: “RSI finds momentum extremes; Bollinger confirms volatility expansion; ADX confirms trend strength; all three must align for a BUY/SELL.”
4. Inputs: List adjustable inputs (RSI length and thresholds, BB length & stddev, ADX threshold & smoothing, volume MA, table position/size).
5. Usage instructions: Short workflow (check TF alignment → confirm participation → define stop & R:R → backtest).
6. Limitations & assumptions: Explicitly state volume is approximated, ADX has lag, and avoid promising guaranteed profits.
7. Non-promotional language: No external contact info, ads, claims of exclusivity or guaranteed outcomes.
8. Trademark clause: If you used trademark symbols, remove or provide registration proof.
9. Risk disclaimer: Add the copy-ready disclaimer below.
This matches TradingView’s request for meaningful descriptions that explain originality and inter-component reasoning.
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Copy-ready short publication description (paste into TradingView)
Advanced RSI-ADX-Bollinger Market Overview — educational multi-indicator dashboard. This script combines RSI (momentum extremes), Bollinger Bands (volatility envelope and band expansion), ADX (trend strength), simple SMA trend bias and a basic buy/sell volume heuristic to surface high-quality idea candidates. Signals require alignment of momentum, volatility expansion and rising ADX; volume participation is displayed to support signal confidence. Inputs are configurable (RSI length/levels, BB length/stddev, ADX length/threshold, volume MA, display options). This tool is intended for analysis and learning — not for automated execution. Users should back test and apply robust risk management. Limitations: volume classification here is a heuristic (close>open), ADX and BB measures lag in fast news events, and results vary by instrument liquidity.
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Copy-ready risk & misuse disclaimer (paste into description or help file)
This script is provided for educational and analytical purposes only and does not constitute financial or investment advice. It does not guarantee profits. Indicators are heuristics and may give false or late signals; always back test and paper-trade before using real capital. The author is not responsible for trading losses resulting from the use or misuse of this indicator. Use proper position sizing and risk controls.
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Risk Disclaimer: This tool is provided for education and analysis only. It is not financial advice and does not guarantee returns. Users assume all risk for trades made based on this script. Back test thoroughly and use proper risk management.
MRL Slim — SuperBuy/Sell + Bands (v6.4)MRL — Mean Reversion Bands + Super Buy/Sell (RSI-10)
What it does
This overlay plots a mean-reversion line (linear regression of price) with k·σ bands and adds clean RSI-10 signals on the chart.
Signals (tags on price):
SB = Super Buy: fires when RSI(10) (on close) crosses down through your oversold threshold (default 29).
– Capped to 2 touches per cycle; the cycle resets when RSI crosses above 50 (configurable).
SS = Super Sell (71): fires when RSI(10) crosses up through your overbought threshold (default 71).
SS80 = Super Sell (Hard):
– Fires on cross above 80, and (optionally) again while RSI ≥ 80 using a cooldown to prevent spam.
– Per-cycle cap = 2 by default; you can let hard sells bypass the cap.
Bands & Source
Bands are built around a linreg mean of your chosen Source (default hlc3).
Toggle Log Space to make bands act percent-like on long histories/trending assets.
Filters (optional)
Price ≥ Upper Band required for sells.
Mean slope down required for sells.
(Disable if you want every RSI event, even in strong trends.)
Debug (optional)
Turn on Debug to see raw RSI crosses/touches and why a signal was blocked (e.g., cap, band, slope, cooldown).
Separate toggle to show/hide CAP dots.
Tips
For fast charts or very strong momentum, consider loosening the sell filters or shortening the HARD cooldown.
If your panel RSI shows signals you don’t see on price: ensure you’re comparing RSI(10, close) on the same timeframe.
Disclaimer
For research/education only. Not financial advice; always manage risk.
Volume Footprint Anomaly Scanner [PhenLabs]📊 PhenLabs - Volume Footprint Anomaly Scanner (VFAS)
Version: PineScript™ v6
📌 Description
The PhenLabs Volume Footprint Anomaly Scanner (VFAS) is an advanced Pine Script indicator designed to detect and highlight significant imbalances in buying and selling pressure within individual price bars. By analyzing a calculated "Delta" – the net difference between estimated buy and sell volume – and employing statistical Z-score analysis, VFAS pinpoints moments when buying or selling activity becomes unusually dominant. This script was created not in hopes of creating a "Buy and Sell" indicator but rather providing the user with a more in-depth insight into the intrabar volume delta and how it can fluctuate in unusual ways, leading to anomalies that can be capitalized on.
This indicator helps traders identify high-conviction points where strong market participants are active, signaling potential shifts in momentum or continuation of a trend. It aims to provide a clearer understanding of underlying market dynamics, allowing for more informed decision-making in various trading strategies, from identifying entry points to confirming trend strength.
🚀 Points of Innovation
● Z-Score for Delta Analysis : Utilizes statistical Z-scores to objectively identify statistically significant anomalies in buying/selling pressure, moving beyond simple, arbitrary thresholds.
● Dynamic Confidence Scoring : Assigns a multi-star confidence rating (1-4 stars) to each signal, factoring in high volume, trend alignment, and specific confirmation criteria, providing a nuanced view of signal strength.
● Integrated Trend Filtering : Offers an optional Exponential Moving Average (EMA)-based trend filter to ensure signals align with the broader market direction, reducing false positives in ranging markets.
● Strict Confirmation Logic : Implements specific confirmation criteria for higher-confidence signals, including price action and a time-based gap from previous signals, enhancing reliability.
● Intuitive Info Dashboard : Provides a real-time summary of market trend and the latest signal's direction and confidence directly on the chart, streamlining information access.
🔧 Core Components
● Core Delta Engine : Estimates the net buying/selling pressure (bar Delta) by analyzing price movement within each bar relative to volume. It also calculates average volume to identify bars with unusually high activity.
● Anomaly Detection (Z-Score) : Computes the Z-score for the current bar's Delta, indicating how many standard deviations it is from its recent average. This statistical measure is central to identifying significant anomalies.
● Trend Filter : Utilizes a dual Exponential Moving Average (EMA) cross-over system to define the prevailing market trend (uptrend, downtrend, or range), providing contextual awareness.
● Signal Processing & Confidence Algorithm : Evaluates anomaly conditions against trend filters and confirmation rules, then calculates a dynamic confidence score to produce actionable, contextualized signal information.
🔥 Key Features
● Advanced Delta Anomaly Detection : Pinpoints bars with exceptionally high buying or selling pressure, indicating potential institutional activity or strong market conviction.
● Multi-Factor Confidence Scoring : Each signal comes with a 1-4 star rating, clearly communicating its reliability based on high volume, trend alignment, and specific confirmation criteria.
● Optional Trend Alignment : Users can choose to filter signals, so only those aligned with the prevailing EMA-defined trend are displayed, enhancing signal quality.
● Interactive Signal Labels : Displays compact labels on the chart at anomaly points, offering detailed tooltips upon hover, including signal type, direction, confidence, and contextual information.
● Customizable Bar Colors : Visually highlights bars with Delta anomalies, providing an immediate visual cue for strong buying or selling activity.
● Real-time Info Dashboard : A clean, customizable dashboard shows the current market trend and details of the latest detected signal, keeping key information accessible at a glance.
● Configurable Alerts : Set up alerts for bullish or bearish Delta anomalies to receive real-time notifications when significant market pressure shifts occur.
🎨 Visualization
Signal Labels :
* Placed at the top/bottom of anomaly bars, showing a "📈" (bullish) or "📉" (bearish) icon.
* Tooltip: Hovering over a label reveals detailed information: Signal Type (e.g., "Delta Anomaly"), Direction, Confidence (e.g., "★★★☆"), and a descriptive explanation of the anomaly.
* Interpretation: Clearly marks actionable signals and provides deep insights without cluttering the chart, enabling quick assessment of signal strength and context.
● Info Dashboard :
* Located at the top-right of the chart, providing a clean summary.
* Displays: "PhenLabs - VFAS" header, "Market Trend" (Uptrend/Downtrend/Range with color-coded status), and "Direction | Conf." (showing the last signal's direction and star confidence).
* Optional "💡 Hover over signals for details" reminder.
* Interpretation: A concise, real-time summary of the market's pulse and the most recent high-conviction event, helping traders stay informed at a glance.
📖 Usage Guidelines
Setting Categories
⚙️ Core Delta & Volume Engine
● Minimum Volume Lookback (Bars)
○ Default: 9
○ Range: Integer (e.g., 5-50)
○ Description: Defines the number of preceding bars used to calculate the average volume and delta. Bars with volume below this average won't be considered for high-volume signals. A shorter lookback is more reactive to recent changes, while a longer one provides a smoother average.
📈 Anomaly Detection Settings
Delta Z-Score Anomaly Threshold
○ Default: 2.5
○ Range: Float (e.g., 1.0-5.0+)
○ Description: The number of standard deviations from the mean that a bar's delta must exceed to be considered a significant anomaly. A higher threshold means fewer, but potentially stronger, signals. A lower threshold will generate more signals, which might include less significant events. Experiment to find the optimal balance for your trading style.
🔬 Context Filters
Enable Trend Filter
○ Default: False
○ Range: Boolean (True/False)
○ Description: When enabled, signals will only be generated if they align with the current market trend as determined by the EMAs (e.g., only bullish signals in an uptrend, bearish in a downtrend). This helps to filter out counter-trend noise.
● Trend EMA Fast
○ Default: 50
○ Range: Integer (e.g., 10-100)
○ Description: The period for the faster Exponential Moving Average used in the trend filter. In combination with the slow EMA, it defines the trend direction.
● Trend EMA Slow
○ Default: 200
○ Range: Integer (e.g., 100-400)
○ Description: The period for the slower Exponential Moving Average used in the trend filter. The relationship between the fast and slow EMA determines if the market is in an uptrend (fast > slow) or downtrend (fast < slow).
🎨 Visual & UI Settings
● Show Info Dashboard
○ Default: True
○ Range: Boolean (True/False)
○ Description: Toggles the visibility of the dashboard on the chart, which provides a summary of market trend and the last detected signal.
● Show Dashboard Tooltip
○ Default: True
○ Range: Boolean (True/False)
○ Description: Toggles a reminder message in the dashboard to hover over signal labels for more detailed information.
● Show Delta Anomaly Bar Colors
○ Default: True
○ Range: Boolean (True/False)
○ Description: Enables or disables the coloring of bars based on their delta direction and whether they represent a significant anomaly.
● Show Signal Labels
○ Default: True
○ Range: Boolean (True/False)
○ Description: Controls the visibility of the “📈” or “📉” labels that appear on the chart when a delta anomaly signal is generated.
🔔 Alert Settings
Alert on Delta Anomaly
○ Default: True
○ Range: Boolean (True/False)
○ Description: When enabled, this setting allows you to set up alerts in TradingView that will trigger whenever a new bullish or bearish delta anomaly is detected.
✅ Best Use Cases
Early Trend Reversal / Continuation Detection: Identify strong surges of buying/selling pressure at key support/resistance levels that could indicate a reversal or the continuation of a strong move.
● Confirmation of Breakouts: Use high-confidence delta anomalies to confirm the validity of price breakouts, indicating strong conviction behind the move.
● Entry and Exit Points: Pinpoint precise entry opportunities when anomalies align with your trading strategy, or identify potential exhaustion signals for exiting trades.
● Scalping and Day Trading: The indicator’s sensitivity to intraday buying/selling imbalances makes it highly effective for short-term trading strategies.
● Market Sentiment Analysis: Gain a real-time understanding of underlying market sentiment by observing the prevalence and strength of bullish vs. bearish anomalies.
⚠️ Limitations
Estimated Delta: The script uses a simplified method to estimate delta based on bar close relative to its range, not actual order book or footprint data. While effective, it’s an approximation.
● Sensitivity to Z-Score Threshold: The effectiveness heavily relies on the `Delta Z-Score Anomaly Threshold`. Too low, and you’ll get many false positives; too high, and you might miss valid signals.
● Confirmation Criteria: The 4-star confidence level’s “confirmation” relies on specific subsequent bar conditions and previous confirmed signals, which might be too strict or specific for all contexts.
● Requires Context: While powerful, VFAS is best used in conjunction with other technical analysis tools and price action to form a comprehensive trading strategy. It is not a standalone “buy/sell” signal.
💡 What Makes This Unique
Statistical Rigor: The application of Z-score analysis to bar delta provides an objective, statistically-driven way to identify true anomalies, moving beyond arbitrary thresholds.
● Multi-Factor Confidence Scoring: The unique 1-4 star confidence system integrates multiple market dynamics (volume, trend alignment, specific follow-through) into a single, easy-to-interpret rating.
● User-Friendly Design: From the intuitive dashboard to the detailed signal tooltips, the indicator prioritizes clear and accessible information for traders of all experience levels.
🔬 How It Works
1. Bar Delta Calculation:
● The script first estimates the “buy volume” and “sell volume” for each bar. This is done by assuming that volume proportional to the distance from the low to the close represents buying, and volume proportional to the distance from the high to the close represents selling.
● How this contributes: This provides a proxy for the net buying or selling pressure (delta) within that specific price bar, even without access to actual footprint data.
2. Volume & Delta Z-Score Analysis:
● The average volume over a user-defined lookback period is calculated. Bars with volume less than twice this average are generally considered of lower interest.
● The Z-score for the calculated bar delta is computed. The Z-score measures how many standard deviations the current bar’s delta is from its average delta over the `Minimum Volume Lookback` period.
● How this contributes: A high positive Z-score indicates a bullish delta anomaly (significantly more buying than usual), while a high negative Z-score indicates a bearish delta anomaly (significantly more selling than usual). This identifies statistically unusual levels of pressure.
3. Trend Filtering (Optional):
● Two Exponential Moving Averages (Fast and Slow EMA) are used to determine the prevailing market trend. An uptrend is identified when the Fast EMA is above the Slow EMA, and a downtrend when the Fast EMA is below the Slow EMA.
● How this contributes: If enabled, the indicator will only display bullish delta anomalies during an uptrend and bearish delta anomalies during a downtrend, helping to confirm signals within the broader market context and avoid counter-trend signals.
4. Signal Generation & Confidence Scoring:
● When a delta Z-score exceeds the user-defined anomaly threshold, a signal is generated.
● This signal is then passed through a multi-factor confidence algorithm (`f_calculateConfidence`). It awards stars based on: high volume presence, alignment with the overall trend (if enabled), and a fourth star for very strong Z-scores (above 3.0) combined with specific follow-through candle patterns after a cooling-off period from a previous confirmed signal.
● How this contributes: Provides a qualitative rating (1-4 stars) for each anomaly, allowing traders to quickly assess the potential significance and reliability of the signal.
💡 Note:
The PhenLabs Volume Footprint Anomaly Scanner is a powerful analytical tool, but it’s crucial to understand that no indicator guarantees profit. Always backtest and forward-test the indicator settings on your chosen assets and timeframes. Consider integrating VFAS with your existing trading strategy, using its signals as confirmation for entries, exits, or trend bias. The Z-score threshold is highly customizable; lower values will yield more signals (including potential noise), while higher values will provide fewer but potentially higher-conviction signals. Adjust this parameter based on market volatility and your risk tolerance. Remember to combine statistical insights from VFAS with price action, support/resistance levels, and your overall market outlook for optimal results.
