BOS TRADER [v 1.0] [Influxum]The name of the tool, BOS Trader, comes from the abbreviation BOS, which stands for Break Of Structure. In simple terms, this tool identifies situations where a change in market structure occurs after liquidity has been grabbed. Following the structural change, it looks for a point where the balance between buyers and sellers will be tested, potentially continuing the price movement in the direction of the structural break.
The goal of this tool is to identify areas where a trader can look for potential entry opportunities based on their entry rules and filters. In our own research, we found that while this tool is not a standalone strategy, it provides a statistical advantage that stems from the nature of the market itself. If you expect the market to reverse at a certain price level against a short-term, medium-term, or long-term trend, that reversal must logically begin with a change in structure – i.e., its break. BOS Trader then highlights the zone where you can expect a strong reaction from traders speculating on the continuation of price in the direction of the break.
Another important piece of the puzzle is the concept of liquidity. Liquidity grabs are generally considered by traders to be events that can trigger market direction changes. That's why BOS Trader is complemented with multiple ways to identify liquidity in the market from a Price Action perspective. We have explored the liquidity concept in depth in our other tools – the Liquidity Tool and Liquidity Strategy Tester – so we won’t go into too much detail on liquidity settings here.
🟪 Pivots
Liquidity can be found beyond pivot extremes – the highest candles in a series of candles. The pivot liquidity setting specifies how many candles must be before and after the pivot candle with a lower high for a pivot high or a higher low for a pivot low. A pivot high is the local highest point of the last 31 candles (15 before the pivot candle, the pivot candle itself, and 15 after). Another option is to set the time period in which the pivot extreme must occur. For example, you can differentiate between pivot highs of the Asian or London session.
🟪 % Percent Change
This setting is based on the well-known Zig Zag indicator and confirms swing highs or swing lows when there is a certain percentage change in price. This helps filter out noise that can occur when the market consolidates and randomly creates pivot highs or lows that aren’t significant.
🟪 Session High/Low
Many popular strategies are based on liquidity defined as the price range of a specific trading session. This doesn't have to be London, Asia, or New York sessions, but could be, for instance, the first hour of the New York session, and so on.
🟪 Day High/Low, Week High/Low, Month High/Low
As the name suggests, liquidity is often defined by the high/low of the previous day, week, or month. These price levels are watched by many market participants, and it's reasonable to expect reactions at these levels. That’s why we included this option in the BOS tool.
Tip for Traders
To avoid common issues with setting the correct session time, we have added the BG option to the tool – the ability to display a background for the configured trading session. This makes it easy to verify that your trading session is set correctly in relation to your time zone.
Delete grabbed liquidity
If a liquidity level is breached by price, it becomes invalid. For those who prefer to keep their charts clean and uncluttered, there is an option to delete grabbed liquidity. This way, only untraded, valid liquidity lines will be visible on the chart.
Bars after liquidity grab
A liquidity grab should be a significant event that triggers a reaction from market participants. To ensure this is a real response to liquidity rather than random market behavior, we added a time test to the BOS tool. A structural break must occur within a specified time after the liquidity grab. You can define this time in the tool as the number of bars after which the structural break is still considered valid following the liquidity grab.
🟪 AOI (Area of Interest) Settings
Initially, it's important to note that there are two main options for setting the behavior of the AOI. The first option is to fix its duration by the number of bars – Duration, and the second is to keep the AOI valid until it is traded through – Extended.
Duration
Since we expect a quick reaction to the liquidity grab, we also expect a fast pullback to the AOI and a swift response of traders. Our research has shown that the strongest reactions typically occur within a maximum of 15 bars from the formation of the AOI (fractally across timeframes). Therefore, this value is set as the default. However, we recommend considering not just the speed of the reaction but also its intensity. After the set number of bars, the AOI stops extending further.
Extended
We have noticed that price has a tendency to return to the AOI even after a longer period and react again. For this reason, we included the option in the BOS tool to extend the AOI into the future, with the ability to freely adjust the Max AOI Length.
🟪 AOI Size Mode
There are two options for setting the size of the AOI. Either it can be calculated as a percentage of the swing size (% of swing) in which the structural break occurred (the default setting is 30%), or you can set a different concept for the AOI size. For example, the well-known Optimal Trade Entry model. Custom values can be set in the FIBO Levels option, where you can define either preferred Fibonacci values or values based on your own criteria.
🟪 Trading Session (signals + alerts + visibility)
The main goal of our tools is to make it easier for traders to identify patterns and opportunities in the market and allow them to be alerted to their occurrence. The time for AOI plotting after a liquidity grab is combined into a single Trading Session function. This controls both the AOI plotting and when the tool will send alerts. All of this is aimed at helping traders avoid spending the entire day in front of their monitors, waiting for trading opportunities. Here, too, you can use the BG feature to plot a background on the chart showing the current session.
🟪 Trading within session range
We found that some traders have difficulty navigating the many AOIs plotted during times when the market consolidates and creates numerous false breakouts. Therefore, we included an option in the BOS tool to track only structural changes at the price extremes of the current day and trading session. The tool will not plot structural changes for internal liquidity grabs (within the session range), but only for external liquidity grabs (highest highs and lowest lows of the session or liquidity from previous days).
Visuals
The BOS tool is, of course, supplemented with the option to customize the appearance of all its components according to your preferences.
在腳本中搜尋"liquidity"
AR-Session-Orb-HTF High/LowThis indicator is built for intraday model execution around liquidity grabs, session timing, and higher-timeframe draw-on-liquidity. It maps out sessions, ICT killzones, Session opening ranges (including the US 09:30 cash open), a daily NY “TD Open” line (00:00 → NY close), and key highs/lows from higher timeframes directly onto any lower timeframe chart (down to 1 minute).
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1. Sessions (Asia / London / New York)
• Highlights the 3 main sessions with colored boxes:
• Asia
• London
• New York
• Default session times are set in New York local time:
• Asia: 18:00–02:00
• London: 03:00–12:00
• New York: 08:00–17:00
• You can change these times in the settings.
• Each box automatically expands as the session progresses.
Why it matters: these windows show you where liquidity usually builds, where the day “hands off” from Asia → London → NY, and when expansion/displacement typically happens.
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2. ICT Killzones
The script includes 4 configurable killzones (NY local by default):
• Asia late session: 20:00–00:00
• London killzone: 02:00–05:00
• New York AM: 07:00–10:00
• New York Midday: 10:00–12:00
For each killzone you can:
• toggle on/off
• adjust the time window
• pick colors
This makes it easy to see when price is trading inside a high-probability delivery period, so you can line it up with liquidity above/below the session or OR.
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3. Opening Range Levels
The indicator captures the high and low of the first X minutes (default 15) of each important window and projects those levels as horizontal lines.
It does this for:
• Asia Open Range
• London Open Range
• New York Open Range (08:00)
• NY 09:30 Cash-Open Range
• (in the original idea: NY mid / second NY window)
Behavior:
• Asia OR → after the first X minutes of Asia, the high/low are projected across the rest of the trading day.
• London OR → taken from the London start, but extended only while London is active.
• NY OR (08:00) → taken from the start of the NY session and extended only during NY.
• NY 09:30 OR → this one is special. At exactly 09:30 (cash open) the script starts a second, independent OR for that day, using your chosen length (e.g. 15 minutes). When the window finishes, it freezes the 09:30 high and low and projects them horizontally all the way to the NY session end. You can style it separately (color, labels). This gives you a clean “cash-open dealing range” to watch for sweeps, fake-outs and continuations.
You can:
• choose the range length (1–60 minutes for 09:30, 1–30 for the others)
• show/hide each OR
• color each OR
• show labels such as “Asia OR High”, “Lon OR Low”, “NY 09:30 High”, etc.
• control line padding so labels don’t print on top of the candle
These ORs often become obvious liquidity pools, fail-break zones, or continuation triggers.
________________________________________
4. NY TD Open Line (Daily 00:00)
On every trading day the script also plots a “TD” structure for New York:
• at 00:00 NY time it draws a vertical dashed line to mark the day’s start
• it records that day’s open price
• it then projects a horizontal line from 00:00 → all the way to NY session close (default 17:00)
• the horizontal line is labeled e.g. “NY TD Open”
How to use it:
• see instantly where current price is vs the daily open
• combine with 09:30 OR to know if cash open is opening above/below the day’s open
• good for intraday bias (above = bullish day structure, below = bearish day structure)
• nice anchor when you go down to 1m/3m
You can toggle the TD feature on/off and change its colors.
________________________________________
5. Previous Week High / Low
• Plots last week’s high and low on any timeframe
• Drawn as dashed lines with padding (so they don’t run to infinity)
• Each level is labeled (default “PW High” / “PW Low”)
These are classic weekly liquidity magnets and very useful when London/NY is expanding into an old weekly extreme.
________________________________________
6. Monthly High / Low
The script plots both:
• Previous month high/low
• Current month high/low (live)
Defaults:
• previous month → dashed + purple
• current month → solid + blue
You can change:
• line colors
• label text & colors
• how far the line should extend (bars span)
This gives you higher-TF liquidity targets on your intraday chart without switching to M or W.
________________________________________
7. 4H High / Low (Intra-session Liquidity Map)
On timeframes up to 4H, the script also plots:
• previous 4H high/low
• current 4H high/low
Important design choice: they only live inside their own 4H window.
• the previous 4H range is shown only over the previous 4H time span
• the current 4H range is shown only over the current 4H candle
That means you don’t get messy, stretched 4H lines across the whole day — only where they actually apply. This is super useful for London/NY raids on 4H highs/lows.
________________________________________
8. Customization / Inputs
Almost everything is editable:
• session windows + colors
• killzone windows + colors
• opening-range length
• ON/OFF per OR (Asia, London, NY 08:00, NY 09:30)
• label text, size, bg color, text color
• HTF line length (weekly / monthly)
• TD 00:00 ON/OFF + colors
• line end padding so labels don’t sit on the right edge
The idea is to give you structure, not signals.
________________________________________
How to Use
1. Start from the monthly / weekly / previous week levels to see where price “wants” to go.
2. Drop into the active session box / killzone to know when to pay attention.
3. Trade around opening-range highs/lows — especially the NY 09:30 OR — and look for liquidity sweeps.
4. Check where price is relative to the NY TD Open (00:00) to confirm intraday bias.
5. Refine entries using the 4H highs/lows that fall inside that session.
Result: you get a top-down liquidity map + intraday timing tool, all on one chart.
________________________________________
Notes
• All times are interpreted in the chart/session timezone — keep your chart on NY session if you want the defaults to match the description.
• TradingView has drawing limits; on very low timeframes far back in history, old drawings may recycle.
• Because 09:30 and TD are drawn every day, it’s normal to see more labels the further right you scroll.
________________________________________
Disclaimer
This script is for educational and charting purposes only.
It does not generate trade signals, manage risk, or guarantee profitability.
Trading involves risk — always do your own analysis.
Special Thanks to Sabo & Hive Community
Nov 17
Release Notes
This indicator is built for intraday model execution around liquidity grabs, session timing, and higher-timeframe draw-on-liquidity. It maps out sessions, killzones, opening ranges (including the US 09:30 cash open), a daily NY “TD Open” line (00:00 → NY close), and key highs/lows from higher timeframes directly onto any lower timeframe chart (down to 1 minute).
________________________________________
1. Sessions (Asia / London / New York)
• Highlights the 3 main sessions with colored boxes:
• Asia
• London
• New York
• Default session times are set in New York local time:
• Asia: 18:00–02:00
• London: 03:00–12:00
• New York: 08:00–17:00
• You can change these times in the settings.
• Each box automatically expands as the session progresses.
Why it matters: these windows show you where liquidity usually builds, where the day “hands off” from Asia → London → NY, and when expansion/displacement typically happens.
________________________________________
2. ICT Killzones
The script includes 4 configurable killzones (NY local by default):
• Asia late session: 20:00–00:00
• London killzone: 02:00–05:00
• New York AM: 07:00–10:00
• New York Midday: 10:00–12:00
For each killzone you can:
• toggle on/off
• adjust the time window
• pick colors
This makes it easy to see when price is trading inside a high-probability delivery period, so you can line it up with liquidity above/below the session or OR.
________________________________________
3. Opening Range Levels
The indicator captures the high and low of the first X minutes (default 15) of each important window and projects those levels as horizontal lines.
It does this for:
• Asia Open Range
• London Open Range
• New York Open Range (08:00)
• NY 09:30 Cash-Open Range
• (in the original idea: NY mid / second NY window)
Behavior:
• Asia OR → after the first X minutes of Asia, the high/low are projected across the rest of the trading day.
• London OR → taken from the London start, but extended only while London is active.
• NY OR (08:00) → taken from the start of the NY session and extended only during NY.
• NY 09:30 OR → this one is special. At exactly 09:30 (cash open) the script starts a second, independent OR for that day, using your chosen length (e.g. 15 minutes). When the window finishes, it freezes the 09:30 high and low and projects them horizontally all the way to the NY session end. You can style it separately (color, labels). This gives you a clean “cash-open dealing range” to watch for sweeps, fake-outs and continuations.
You can:
• choose the range length (1–60 minutes for 09:30, 1–30 for the others)
• show/hide each OR
• color each OR
• show labels such as “Asia OR High”, “Lon OR Low”, “NY 09:30 High”, etc.
• control line padding so labels don’t print on top of the candle
These ORs often become obvious liquidity pools, fail-break zones, or continuation triggers.
________________________________________
4. NY TD Open Line (Daily 00:00)
On every trading day the script also plots a “TD” structure for New York:
• at 00:00 NY time it draws a vertical dashed line to mark the day’s start
• it records that day’s open price
• it then projects a horizontal line from 00:00 → all the way to NY session close (default 17:00)
• the horizontal line is labeled e.g. “NY TD Open”
How to use it:
• see instantly where current price is vs the daily open
• combine with 09:30 OR to know if cash open is opening above/below the day’s open
• good for intraday bias (above = bullish day structure, below = bearish day structure)
• nice anchor when you go down to 1m/3m
You can toggle the TD feature on/off and change its colors.
________________________________________
5. Previous Week High / Low
• Plots last week’s high and low on any timeframe
• Drawn as dashed lines with padding (so they don’t run to infinity)
• Each level is labeled (default “PW High” / “PW Low”)
These are classic weekly liquidity magnets and very useful when London/NY is expanding into an old weekly extreme.
________________________________________
6. Monthly High / Low
The script plots both:
• Previous month high/low
• Current month high/low (live)
Defaults:
• previous month → dashed + purple
• current month → solid + blue
You can change:
• line colors
• label text & colors
• how far the line should extend (bars span)
This gives you higher-TF liquidity targets on your intraday chart without switching to M or W.
________________________________________
7. 4H High / Low (Intra-session Liquidity Map)
On timeframes up to 4H, the script also plots:
• previous 4H high/low
• current 4H high/low
Important design choice: they only live inside their own 4H window.
• the previous 4H range is shown only over the previous 4H time span
• the current 4H range is shown only over the current 4H candle
That means you don’t get messy, stretched 4H lines across the whole day — only where they actually apply. This is super useful for London/NY raids on 4H highs/lows.
________________________________________
8. Customization / Inputs
Almost everything is editable:
• session windows + colors
• killzone windows + colors
• opening-range length
• ON/OFF per OR (Asia, London, NY 08:00, NY 09:30)
• label text, size, bg color, text color
• HTF line length (weekly / monthly)
• TD 00:00 ON/OFF + colors
• line end padding so labels don’t sit on the right edge
The idea is to give you structure, not signals.
________________________________________
How to Use
1. Start from the monthly / weekly / previous week levels to see where price “wants” to go.
2. Drop into the active session box / killzone to know when to pay attention.
3. Trade around opening-range highs/lows — especially the NY 09:30 OR — and look for liquidity sweeps.
4. Check where price is relative to the NY TD Open (00:00) to confirm intraday bias.
5. Refine entries using the 4H highs/lows that fall inside that session.
Result: you get a top-down liquidity map + intraday timing tool, all on one chart.
________________________________________
Notes
• All times are interpreted in the chart/session timezone — keep your chart on NY session if you want the defaults to match the description.
• TradingView has drawing limits; on very low timeframes far back in history, old drawings may recycle.
• Because 09:30 and TD are drawn every day, it’s normal to see more labels the further right you scroll.
________________________________________
Disclaimer
This script is for educational and charting purposes only.
It does not generate trade signals, manage risk, or guarantee profitability.
Trading involves risk — always do your own analysis.
Special Thanks to Sabo & Hive Community
Algorithm Predator - ProAlgorithm Predator - Pro: Advanced Multi-Agent Reinforcement Learning Trading System
Algorithm Predator - Pro combines four specialized market microstructure agents with a state-of-the-art reinforcement learning framework . Unlike traditional indicator mashups, this system implements genuine machine learning to automatically discover which detection strategies work best in current market conditions and adapts continuously without manual intervention.
Core Innovation: Rather than forcing traders to interpret conflicting signals, this system uses 15 different multi-armed bandit algorithms and a full reinforcement learning stack (Q-Learning, TD(λ) with eligibility traces, and Policy Gradient with REINFORCE) to learn optimal agent selection policies. The result is a self-improving system that gets smarter with every trade.
Target Users: Swing traders, day traders, and algorithmic traders seeking systematic signal generation with mathematical rigor. Suitable for stocks, forex, crypto, and futures on liquid instruments (>100k daily volume).
Why These Components Are Combined
The Fundamental Problem
No single indicator works consistently across all market regimes. What works in trending markets fails in ranging conditions. Traditional solutions force traders to manually switch indicators (slow, error-prone) or interpret all signals simultaneously (cognitive overload).
This system solves the problem through automated meta-learning: Deploy multiple specialized agents designed for specific market microstructure conditions, then use reinforcement learning to discover which agent (or combination) performs best in real-time.
Why These Specific Four Agents?
The four agents provide orthogonal failure mode coverage —each agent's weakness is another's strength:
Spoofing Detector - Optimal in consolidation/manipulation; fails in trending markets (hedged by Exhaustion Detector)
Exhaustion Detector - Optimal at trend climax; fails in range-bound markets (hedged by Liquidity Void)
Liquidity Void - Optimal pre-breakout compression; fails in established trends (hedged by Mean Reversion)
Mean Reversion - Optimal in low volatility; fails in strong trends (hedged by Spoofing Detector)
This creates complete market state coverage where at least one agent should perform well in any condition. The bandit system identifies which one without human intervention.
Why Reinforcement Learning vs. Simple Voting?
Traditional consensus systems have fatal flaws: equal weighting assumes all agents are equally reliable (false), static thresholds don't adapt, and no learning means past mistakes repeat indefinitely.
Reinforcement learning solves this through the exploration-exploitation tradeoff: Continuously test underused agents (exploration) while primarily relying on proven winners (exploitation). Over time, the system builds a probability distribution over agent quality reflecting actual market performance.
Mathematical Foundation: Multi-armed bandit problem from probability theory, where each agent is an "arm" with unknown reward distribution. The goal is to maximize cumulative reward while efficiently learning each arm's true quality.
The Four Trading Agents: Technical Explanation
Agent 1: 🎭 Spoofing Detector (Institutional Manipulation Detection)
Theoretical Basis: Market microstructure theory on order flow toxicity and information asymmetry. Based on research by Easley, López de Prado, and O'Hara on high-frequency trading manipulation.
What It Detects:
1. Iceberg Orders (Hidden Liquidity Absorption)
Method: Monitors volume spikes (>2.5× 20-period average) with minimal price movement (<0.3× ATR)
Formula: score += (close > open ? -2.5 : 2.5) when volume > vol_avg × 2.5 AND abs(close - open) / ATR < 0.3
Interpretation: Large volume without price movement indicates institutional absorption (buying) or distribution (selling) using hidden orders
Signal Logic: Contrarian—fade false breakouts caused by institutional manipulation
2. Spoofing Patterns (Fake Liquidity via Layering)
Method: Analyzes candlestick wick-to-body ratios during volume spikes
Formula: if upper_wick > body × 2 AND volume_spike: score += 2.0
Mechanism: Spoofing creates large wicks (orders pulled before execution) with volume evidence
Signal Logic: Wick direction indicates trapped participants; trade against the failed move
3. Post-Manipulation Reversals
Method: Tracks volume decay after manipulation events
Formula: if volume > vol_avg × 3 AND volume / volume < 0.3: score += (close > open ? -1.5 : 1.5)
Interpretation: Sharp volume drop after manipulation indicates exhaustion of manipulative orders
Why It Works: Institutional manipulation creates detectable microstructure anomalies. While retail traders see "mysterious reversals," this agent quantifies the order flow patterns causing them.
Parameter: i_spoof (sensitivity 0.5-2.0) - Controls detection threshold
Best Markets: Consolidations before breakouts, London/NY overlap windows, stocks with institutional ownership >70%
Agent 2: ⚡ Exhaustion Detector (Momentum Failure Analysis)
Theoretical Basis: Technical analysis divergence theory combined with VPIN reversals from market microstructure literature.
What It Detects:
1. Price-RSI Divergence (Momentum Deceleration)
Method: Compares 5-bar price ROC against RSI change
Formula: if price_roc > 5% AND rsi_current < rsi : score += 1.8
Mathematics: Second derivative detecting inflection points
Signal Logic: When price makes higher highs but momentum makes lower highs, expect mean reversion
2. Volume Exhaustion (Buying/Selling Climax)
Method: Identifies strong price moves (>5% ROC) with declining volume (<-20% volume ROC)
Formula: if price_roc > 5 AND vol_roc < -20: score += 2.5
Interpretation: Price extension without volume support indicates retail chasing while institutions exit
3. Momentum Deceleration (Acceleration Analysis)
Method: Compares recent 3-bar momentum to prior 3-bar momentum
Formula: deceleration = abs(mom1) < abs(mom2) × 0.5 where momentum significant (> ATR)
Signal Logic: When rate of price change decelerates significantly, anticipate directional shift
Why It Works: Momentum is lagging, but momentum divergence is leading. By comparing momentum's rate of change to price, this agent detects "weakening conviction" before reversals become obvious.
Parameter: i_momentum (sensitivity 0.5-2.0)
Best Markets: Strong trends reaching climax, parabolic moves, instruments with high retail participation
Agent 3: 💧 Liquidity Void Detector (Breakout Anticipation)
Theoretical Basis: Market liquidity theory and order book dynamics. Based on research into "liquidity holes" and volatility compression preceding expansion.
What It Detects:
1. Bollinger Band Squeeze (Volatility Compression)
Method: Monitors Bollinger Band width relative to 50-period average
Formula: bb_width = (upper_band - lower_band) / middle_band; triggers when < 0.6× average
Mathematical Foundation: Regression to the mean—low volatility precedes high volatility
Signal Logic: When volatility compresses AND cumulative delta shows directional bias, anticipate breakout
2. Volume Profile Gaps (Thin Liquidity Zones)
Method: Identifies sharp volume transitions indicating few limit orders
Formula: if volume < vol_avg × 0.5 AND volume < vol_avg × 0.5 AND volume > vol_avg × 1.5
Interpretation: Sudden volume drop after spike indicates price moved through order book to low-opposition area
Signal Logic: Price accelerates through low-liquidity zones
3. Stop Hunts (Liquidity Grabs Before Reversals)
Method: Detects new 20-bar highs/lows with immediate reversal and rejection wick
Formula: if new_high AND close < high - (high - low) × 0.6: score += 3.0
Mechanism: Market makers push price to trigger stop-loss clusters, then reverse
Signal Logic: Enter reversal after stop-hunt completes
Why It Works: Order book theory shows price moves fastest through zones with minimal liquidity. By identifying these zones before major moves, this agent provides early entry for high-reward breakouts.
Parameter: i_liquidity (sensitivity 0.5-2.0)
Best Markets: Range-bound pre-breakout setups, volatility compression zones, instruments prone to gap moves
Agent 4: 📊 Mean Reversion (Statistical Arbitrage Engine)
Theoretical Basis: Statistical arbitrage theory, Ornstein-Uhlenbeck mean-reverting processes, and pairs trading methodology applied to single instruments.
What It Detects:
1. Z-Score Extremes (Standard Deviation Analysis)
Method: Calculates price distance from 20-period and 50-period SMAs in standard deviation units
Formula: zscore_20 = (close - SMA20) / StdDev(50)
Statistical Interpretation: Z-score >2.0 means price is 2 standard deviations above mean (97.5th percentile)
Trigger Logic: if abs(zscore_20) > 2.0: score += zscore_20 > 0 ? -1.5 : 1.5 (fade extremes)
2. Ornstein-Uhlenbeck Process (Mean-Reverting Stochastic Model)
Method: Models price as mean-reverting stochastic process: dx = θ(μ - x)dt + σdW
Implementation: Calculates spread = close - SMA20, then z-score of spread vs. spread distribution
Formula: ou_signal = (spread - spread_mean) / spread_std
Interpretation: Measures "tension" pulling price back to equilibrium
3. Correlation Breakdown (Regime Change Detection)
Method: Compares 50-period price-volume correlation to 10-period correlation
Formula: corr_breakdown = abs(typical_corr - recent_corr) > 0.5
Enhancement: if corr_breakdown AND abs(zscore_20) > 1.0: score += zscore_20 > 0 ? -1.2 : 1.2
Why It Works: Mean reversion is the oldest quantitative strategy (1970s pairs trading at Morgan Stanley). While simple, it remains effective because markets exhibit periodic equilibrium-seeking behavior. This agent applies rigorous statistical testing to identify when mean reversion probability is highest.
Parameter: i_statarb (sensitivity 0.5-2.0)
Best Markets: Range-bound instruments, low-volatility periods (VIX <15), algo-dominated markets (forex majors, index futures)
Multi-Armed Bandit System: 15 Algorithms Explained
What Is a Multi-Armed Bandit Problem?
Origin: Named after slot machines ("one-armed bandits"). Imagine facing multiple slot machines, each with unknown payout rates. How do you maximize winnings?
Formal Definition: K arms (agents), each with unknown reward distribution with mean μᵢ. Goal: Maximize cumulative reward over T trials. Challenge: Balance exploration (trying uncertain arms to learn quality) vs. exploitation (using known-best arm for immediate reward).
Trading Application: Each agent is an "arm." After each trade, receive reward (P&L). Must decide which agent to trust for next signal.
Algorithm Categories
Bayesian Approaches (probabilistic, optimal for stationary environments):
Thompson Sampling
Bootstrapped Thompson Sampling
Discounted Thompson Sampling
Frequentist Approaches (confidence intervals, deterministic):
UCB1
UCB1-Tuned
KL-UCB
SW-UCB (Sliding Window)
D-UCB (Discounted)
Adversarial Approaches (robust to non-stationary environments):
EXP3-IX
Hedge
FPL-Gumbel
Reinforcement Learning Approaches (leverage learned state-action values):
Q-Values (from Q-Learning)
Policy Network (from Policy Gradient)
Simple Baseline:
Epsilon-Greedy
Softmax
Key Algorithm Details
Thompson Sampling (DEFAULT - RECOMMENDED)
Theoretical Foundation: Bayesian decision theory with conjugate priors. Published by Thompson (1933), rediscovered for bandits by Chapelle & Li (2011).
How It Works:
Model each agent's reward distribution as Beta(α, β) where α = wins, β = losses
Each step, sample from each agent's beta distribution: θᵢ ~ Beta(αᵢ, βᵢ)
Select agent with highest sample: argmaxᵢ θᵢ
Update winner's distribution after observing outcome
Mathematical Properties:
Optimality: Achieves logarithmic regret O(K log T) (proven optimal)
Bayesian: Maintains probability distribution over true arm means
Automatic Balance: High uncertainty → more exploration; high certainty → exploitation
⚠️ CRITICAL APPROXIMATION: This is a pseudo-random approximation of true Thompson Sampling. True implementation requires random number generation from beta distributions, which Pine Script doesn't provide. This version uses Box-Muller transform with market data (price/volume decimal digits) as entropy source. While not mathematically pure, it maintains core exploration-exploitation balance and learns agent preferences effectively.
When To Use: Best all-around choice. Handles non-stationary markets reasonably well, balances exploration naturally, highly sample-efficient.
UCB1 (Upper Confidence Bound)
Formula: UCB_i = reward_mean_i + sqrt(2 × ln(total_pulls) / pulls_i)
Interpretation: First term (exploitation) + second term (exploration bonus for less-tested arms)
Mathematical Properties:
Deterministic : Always selects same arm given same state
Regret Bound: O(K log T) — same optimality as Thompson Sampling
Interpretable: Can visualize confidence intervals
When To Use: Prefer deterministic behavior, want to visualize uncertainty, stable markets
EXP3-IX (Exponential Weights - Adversarial)
Theoretical Foundation: Adversarial bandit algorithm. Assumes environment may be actively hostile (worst-case analysis).
How It Works:
Maintain exponential weights: w_i = exp(η × cumulative_reward_i)
Select agent with probability proportional to weights: p_i = (1-γ)w_i/Σw_j + γ/K
After outcome, update with importance weighting: estimated_reward = observed_reward / p_i
Mathematical Properties:
Adversarial Regret: O(sqrt(TK log K)) even if environment is adversarial
No Assumptions: Doesn't assume stationary or stochastic reward distributions
Robust: Works even when optimal arm changes continuously
When To Use: Extreme non-stationarity, don't trust reward distribution assumptions, want robustness over efficiency
KL-UCB (Kullback-Leibler Upper Confidence Bound)
Theoretical Foundation: Uses KL-divergence instead of Hoeffding bounds. Tighter confidence intervals.
Formula (conceptual): Find largest q such that: n × KL(p||q) ≤ ln(t) + 3×ln(ln(t))
Mathematical Properties:
Tighter Bounds: KL-divergence adapts to reward distribution shape
Asymptotically Optimal: Better constant factors than UCB1
Computationally Intensive: Requires iterative binary search (15 iterations)
When To Use: Maximum sample efficiency needed, willing to pay computational cost, long-term trading (>500 bars)
Q-Values & Policy Network (RL-Based Selection)
Unique Feature: Instead of treating agents as black boxes with scalar rewards, these algorithms leverage the full RL state representation .
Q-Values Selection:
Uses learned Q-values: Q(state, agent_i) from Q-Learning
Selects agent via softmax over Q-values for current market state
Advantage: Selects based on state-conditional quality (which agent works best in THIS market state)
Policy Network Selection:
Uses neural network policy: π(agent | state, θ) from Policy Gradient
Direct policy over agents given market features
Advantage: Can learn non-linear relationships between market features and agent quality
When To Use: After 200+ RL updates (Q-Values) or 500+ updates (Policy Network) when models converged
Machine Learning & Reinforcement Learning Stack
Why Both Bandits AND Reinforcement Learning?
Critical Distinction:
Bandits treat agents as contextless black boxes: "Agent 2 has 60% win rate"
Reinforcement Learning adds state context: "Agent 2 has 60% win rate WHEN trend_score > 2 and RSI < 40"
Power of Combination: Bandits provide fast initial learning with minimal assumptions. RL provides state-dependent policies for superior long-term performance.
Component 1: Q-Learning (Value-Based RL)
Algorithm: Temporal Difference Learning with Bellman equation.
State Space: 54 discrete states formed from:
trend_state = {0: bearish, 1: neutral, 2: bullish} (3 values)
volatility_state = {0: low, 1: normal, 2: high} (3 values)
RSI_state = {0: oversold, 1: neutral, 2: overbought} (3 values)
volume_state = {0: low, 1: high} (2 values)
Total states: 3 × 3 × 3 × 2 = 54 states
Action Space: 5 actions (No trade, Agent 1, Agent 2, Agent 3, Agent 4)
Total state-action pairs: 54 × 5 = 270 Q-values
Bellman Equation:
Q(s,a) ← Q(s,a) + α ×
Parameters:
α (learning rate): 0.01-0.50, default 0.10 - Controls step size for updates
γ (discount factor): 0.80-0.99, default 0.95 - Values future rewards
ε (exploration): 0.01-0.30, default 0.10 - Probability of random action
Update Mechanism:
Position opens with state s, action a (selected agent)
Every bar position is open: Calculate floating P&L → scale to reward
Perform online TD update
When position closes: Perform terminal update with final reward
Gradient Clipping: TD errors clipped to ; Q-values clipped to for stability.
Why It Works: Q-Learning learns "quality" of each agent in each market state through trial and error. Over time, builds complete state-action value function enabling optimal state-dependent agent selection.
Component 2: TD(λ) Learning (Temporal Difference with Eligibility Traces)
Enhancement Over Basic Q-Learning: Credit assignment across multiple time steps.
The Problem TD(λ) Solves:
Position opens at t=0
Market moves favorably at t=3
Position closes at t=8
Question: Which earlier decisions contributed to success?
Basic Q-Learning: Only updates Q(s₈, a₈) ← reward
TD(λ): Updates ALL visited state-action pairs with decayed credit
Eligibility Trace Formula:
e(s,a) ← γ × λ × e(s,a) for all s,a (decay all traces)
e(s_current, a_current) ← 1 (reset current trace)
Q(s,a) ← Q(s,a) + α × TD_error × e(s,a) (update all with trace weight)
Lambda Parameter (λ): 0.5-0.99, default 0.90
λ=0: Pure 1-step TD (only immediate next state)
λ=1: Full Monte Carlo (entire episode)
λ=0.9: Balance (recommended)
Why Superior: Dramatically faster learning for multi-step tasks. Q-Learning requires many episodes to propagate rewards backwards; TD(λ) does it in one.
Component 3: Policy Gradient (REINFORCE with Baseline)
Paradigm Shift: Instead of learning value function Q(s,a), directly learn policy π(a|s).
Policy Network Architecture:
Input: 12 market features
Hidden: None (linear policy)
Output: 5 actions (softmax distribution)
Total parameters: 12 features × 5 actions + 5 biases = 65 parameters
Feature Set (12 Features):
Price Z-score (close - SMA20) / ATR
Volume ratio (volume / vol_avg - 1)
RSI deviation (RSI - 50) / 50
Bollinger width ratio
Trend score / 4 (normalized)
VWAP deviation
5-bar price ROC
5-bar volume ROC
Range/ATR ratio - 1
Price-volume correlation (20-period)
Volatility ratio (ATR / ATR_avg - 1)
EMA50 deviation
REINFORCE Update Rule:
θ ← θ + α × ∇log π(a|s) × advantage
where advantage = reward - baseline (variance reduction)
Why Baseline? Raw rewards have high variance. Subtracting baseline (running average) centers rewards around zero, reducing gradient variance by 50-70%.
Learning Rate: 0.001-0.100, default 0.010 (much lower than Q-Learning because policy gradients have high variance)
Why Policy Gradient?
Handles 12 continuous features directly (Q-Learning requires discretization)
Naturally maintains exploration through probability distribution
Can converge to stochastic optimal policy
Component 4: Ensemble Meta-Learner (Stacking)
Architecture: Level-1 meta-learner combines Level-0 base learners (Q-Learning, TD(λ), Policy Gradient).
Three Meta-Learning Algorithms:
1. Simple Average (Baseline)
Final_prediction = (Q_prediction + TD_prediction + Policy_prediction) / 3
2. Weighted Vote (Reward-Based)
weight_i ← 0.95 × weight_i + 0.05 × (reward_i + 1)
3. Adaptive Weighting (Gradient-Based) — RECOMMENDED
Loss Function: L = (y_true - ŷ_ensemble)²
Gradient: ∂L/∂weight_i = -2 × (y_true - ŷ_ensemble) × agent_contribution_i
Updates weights via gradient descent with clipping and normalization
Why It Works: Unlike simple averaging, meta-learner discovers which base learner is most reliable in current regime. If Policy Gradient excels in trending markets while Q-Learning excels in ranging, meta-learner learns these patterns and weights accordingly.
Feature Importance Tracking
Purpose: Identify which of 12 features contribute most to successful predictions.
Update Rule: importance_i ← 0.95 × importance_i + 0.05 × |feature_i × reward|
Use Cases:
Feature selection: Drop low-importance features
Market regime detection: Importance shifts reveal regime changes
Agent tuning: If VWAP deviation has high importance, consider boosting agents using VWAP
RL Position Tracking System
Critical Innovation: Proper reinforcement learning requires tracking which decisions led to outcomes.
State Tracking (When Signal Validates):
active_rl_state ← current_market_state (0-53)
active_rl_action ← selected_agent (1-4)
active_rl_entry ← entry_price
active_rl_direction ← 1 (long) or -1 (short)
active_rl_bar ← current_bar_index
Online Updates (Every Bar Position Open):
floating_pnl = (close - entry) / entry × direction
reward = floating_pnl × 10 (scale to meaningful range)
reward = clip(reward, -5.0, 5.0)
Update Q-Learning, TD(λ), and Policy Gradient
Terminal Update (Position Close):
Final Q-Learning update (no next Q-value, terminal state)
Update meta-learner with final result
Update agent memory
Clear position tracking
Exit Conditions:
Time-based: ≥3 bars held (minimum hold period)
Stop-loss: 1.5% adverse move
Take-profit: 2.0% favorable move
Market Microstructure Filters
Why Microstructure Matters
Traditional technical analysis assumes fair, efficient markets. Reality: Markets have friction, manipulation, and information asymmetry. Microstructure filters detect when market structure indicates adverse conditions.
Filter 1: VPIN (Volume-Synchronized Probability of Informed Trading)
Theoretical Foundation: Easley, López de Prado, & O'Hara (2012). "Flow Toxicity and Liquidity in a High-Frequency World."
What It Measures: Probability that current order flow is "toxic" (informed traders with private information).
Calculation:
Classify volume as buy or sell (close > close = buy volume)
Calculate imbalance over 20 bars: VPIN = |Σ buy_volume - Σ sell_volume| / Σ total_volume
Compare to moving average: toxic = VPIN > VPIN_MA(20) × sensitivity
Interpretation:
VPIN < 0.3: Normal flow (uninformed retail)
VPIN 0.3-0.4: Elevated (smart money active)
VPIN > 0.4: Toxic flow (informed institutions dominant)
Filter Logic:
Block LONG when: VPIN toxic AND price rising (don't buy into institutional distribution)
Block SHORT when: VPIN toxic AND price falling (don't sell into institutional accumulation)
Adaptive Threshold: If VPIN toxic frequently, relax threshold; if rarely toxic, tighten threshold. Bounded .
Filter 2: Toxicity (Kyle's Lambda Approximation)
Theoretical Foundation: Kyle (1985). "Continuous Auctions and Insider Trading."
What It Measures: Price impact per unit volume — market depth and informed trading.
Calculation:
price_impact = (close - close ) / sqrt(Σ volume over 10 bars)
impact_zscore = (price_impact - impact_mean) / impact_std
toxicity = abs(impact_zscore)
Interpretation:
Low toxicity (<1.0): Deep liquid market, large orders absorbed easily
High toxicity (>2.0): Thin market or informed trading
Filter Logic: Block ALL SIGNALS when toxicity > threshold. Most dangerous when price breaks from VWAP with high toxicity.
Filter 3: Regime Filter (Counter-Trend Protection)
Purpose: Prevent counter-trend trades during strong trends.
Trend Scoring:
trend_score = 0
trend_score += close > EMA8 ? +1 : -1
trend_score += EMA8 > EMA21 ? +1 : -1
trend_score += EMA21 > EMA50 ? +1 : -1
trend_score += close > EMA200 ? +1 : -1
Range:
Regime Classification:
Strong Bull: trend_score ≥ +3 → Block all SHORT signals
Strong Bear: trend_score ≤ -3 → Block all LONG signals
Neutral: -2 ≤ trend_score ≤ +2 → Allow both directions
Filter 4: Liquidity Boost (Signal Enhancer)
Unique: Unlike other filters (which block), this amplifies signals during low liquidity.
Logic: if volume < vol_avg × 0.7: agent_scores × 1.2
Why It Works: Low liquidity often precedes explosive moves (breakouts). By increasing agent sensitivity during compression, system catches pre-breakout signals earlier.
Technical Implementation & Approximations
⚠️ Critical Approximations Required by Pine Script
1. Thompson Sampling: Pseudo-Random Beta Distribution
Academic Standard: True random sampling from beta distributions using cryptographic RNG
This Implementation: Box-Muller transform for normal distribution using market data (price/volume decimal digits) as entropy source, then scale to beta distribution mean/variance
Impact: Not cryptographically random, may have subtle biases in specific price ranges, but maintains correct mean and approximate variance. Sufficient for bandit agent selection.
2. VPIN: Simplified Volume Classification
Academic Standard: Lee-Ready algorithm or exchange-provided aggressor flags with tick-by-tick data
This Implementation: Bar-based classification: if close > close : buy_volume += volume
Impact: 10-15% precision loss. Works well in directional markets, misclassifies in choppy conditions. Still captures order flow imbalance signal.
3. Policy Gradient: Simplified Per-Action Updates
Academic Standard: Full softmax gradient updating all actions (selected action UP, others DOWN proportionally)
This Implementation: Only updates selected action's weights
Impact: Valid approximation for small action spaces (5 actions). Slower convergence than full softmax but still learns optimal policy.
4. Kyle's Lambda: Simplified Price Impact
Academic Standard: Regression over multiple time scales with signed order flow
This Implementation: price_impact = Δprice_10 / sqrt(Σvolume_10); z_score calculation
Impact: 15-20% precision loss. No proper signed order flow. Still detects informed trading signals at extremes (>2σ).
5. Other Simplifications:
Hawkes Process: Fixed exponential decay (0.9) not MLE-optimized
Entropy: Ratio approximation not true Shannon entropy H(X) = -Σ p(x)·log₂(p(x))
Feature Engineering: 12 features vs. potential 100+ with polynomial interactions
RL Hybrid Updates: Both online and terminal (non-standard but empirically effective)
Overall Precision Loss Estimate: 10-15% compared to academic implementations with institutional data feeds.
Practical Trade-off: For retail trading with OHLCV data, these approximations provide 90%+ of the edge while maintaining full transparency, zero latency, no external dependencies, and runs on any TradingView plan.
How to Use: Practical Guide
Initial Setup (5 Minutes)
Select Trading Mode: Start with "Balanced" for most users
Enable ML/RL System: Toggle to TRUE, select "Full Stack" ML Mode
Bandit Configuration: Algorithm: "Thompson Sampling", Mode: "Switch" or "Blend"
Microstructure Filters: Enable all four filters, enable "Adaptive Microstructure Thresholds"
Visual Settings: Enable dashboard (Top Right), enable all chart visuals
Learning Phase (First 50-100 Signals)
What To Monitor:
Agent Performance Table: Watch win rates develop (target >55%)
Bandit Weights: Should diverge from uniform (0.25 each) after 20-30 signals
RL Core Metrics: "RL Updates" should increase when position open
Filter Status: "Blocked" count indicates filter activity
Optimization Tips:
Too few signals: Lower min_confidence to 0.25, increase agent sensitivities to 1.1-1.2
Too many signals: Raise min_confidence to 0.35-0.40, decrease agent sensitivities to 0.8-0.9
One agent dominates (>70%): Consider "Lock Agent" feature
Signal Interpretation
Dashboard Signal Status:
⚪ WAITING FOR SIGNAL: No agent signaling
⏳ ANALYZING...: Agent signaling but not confirmed
🟡 CONFIRMING 2/3: Building confirmation (2 of 3 bars)
🟢 LONG ACTIVE : Validated long entry
🔴 SHORT ACTIVE : Validated short entry
Kill Zone Boxes: Entry price (triangle marker), Take Profit (Entry + 2.5× ATR), Stop Loss (Entry - 1.5× ATR). Risk:Reward = 1:1.67
Risk Management
Position Sizing:
Risk per trade = 1-2% of capital
Position size = (Capital × Risk%) / (Entry - StopLoss)
Stop-Loss Placement:
Initial: Entry ± 1.5× ATR (shown in kill zone)
Trailing: After 1:1 R:R achieved, move stop to breakeven
Take-Profit Strategy:
TP1 (2.5× ATR): Take 50% off
TP2 (Runner): Trail stop at 1× ATR or use opposite signal as exit
Memory Persistence
Why Save Memory: Every chart reload resets the system. Saving learned parameters preserves weeks of learning.
When To Save: After 200+ signals when agent weights stabilize
What To Save: From Memory Export panel, copy all alpha/beta/weight values and adaptive thresholds
How To Restore: Enable "Restore From Saved State", input all values into corresponding fields
What Makes This Original
Innovation 1: Genuine Multi-Armed Bandit Framework
This implements 15 mathematically rigorous bandit algorithms from academic literature (Thompson Sampling from Chapelle & Li 2011, UCB family from Auer et al. 2002, EXP3 from Auer et al. 2002, KL-UCB from Garivier & Cappé 2011). Each algorithm maintains proper state, updates according to proven theory, and converges to optimal behavior. This is real learning, not superficial parameter changes.
Innovation 2: Full Reinforcement Learning Stack
Beyond bandits learning which agent works best globally, RL learns which agent works best in each market state. After 500+ positions, system builds 54-state × 5-action value function (270 learned parameters) capturing context-dependent agent quality.
Innovation 3: Market Microstructure Integration
Combines retail technical analysis with institutional-grade microstructure metrics: VPIN from Easley, López de Prado, O'Hara (2012), Kyle's Lambda from Kyle (1985), Hawkes Processes from Hawkes (1971). These detect informed trading, manipulation, and liquidity dynamics invisible to technical analysis.
Innovation 4: Adaptive Threshold System
Dynamic quantile-based thresholds: Maintains histogram of each agent's score distribution (24 bins, exponentially decayed), calculates 80th percentile threshold from histogram. Agent triggers only when score exceeds its own learned quantile. Proper non-parametric density estimation automatically adapts to instrument volatility, agent behavior shifts, and market regime changes.
Innovation 5: Episodic Memory with Transfer Learning
Dual-layer architecture: Short-term memory (last 20 trades, fast adaptation) + Long-term memory (condensed episodes, historical patterns). Transfer mechanism consolidates knowledge when STM reaches threshold. Mimics hippocampus → neocortex consolidation in human memory.
Limitations & Disclaimers
General Limitations
No Predictive Guarantee: Pattern recognition ≠ prediction. Past performance ≠ future results.
Learning Period Required: Minimum 50-100 bars for reliable statistics. Initial performance may be suboptimal.
Overfitting Risk: System learns patterns in historical data. May not generalize to unprecedented conditions.
Approximation Limitations: See technical implementation section (10-15% precision loss vs. academic standards)
Single-Instrument Limitation: No multi-asset correlation, sector context, or VIX integration.
Forward-Looking Bias Disclaimer
CRITICAL TRANSPARENCY: The RL system uses an 8-bar forward-looking window for reward calculation.
What This Means: System learns from rewards incorporating future price information (bars 101-108 relative to entry at bar 100).
Why Acceptable:
✅ Signals do NOT look ahead: Entry decisions use only data ≤ entry bar
✅ Learning only: Forward data used for optimization, not signal generation
✅ Real-time mirrors backtest: In live trading, system learns identically
⚠️ Implication: Dashboard "Agent Win%" reflects this 8-bar evaluation. Real-time performance may differ slightly if positions held longer, slippage/fees not captured, or market microstructure changes.
Risk Warnings
No Guarantee of Profit: All trading involves risk of loss
System Failures: Bugs possible despite extensive testing
Market Conditions: Optimized for liquid markets (>100k daily volume). Performance degrades in illiquid instruments, major news events, flash crashes
Broker-Specific Issues: Execution slippage, commission/fees, overnight financing costs
Appropriate Use
This Indicator Is:
✅ Entry trigger system
✅ Risk management framework (stop/target)
✅ Adaptive agent selection engine
✅ Learning system that improves over time
This Indicator Is NOT:
❌ Complete trading strategy (requires position sizing, portfolio management)
❌ Replacement for fundamental analysis
❌ Guaranteed profit generator
❌ Suitable for complete beginners without training
Recommended Complementary Analysis: Market context (support/resistance), volume profile, fundamental catalysts, correlation with related instruments, broader market regime
Recommended Settings by Instrument
Stocks (Large Cap, >$1B):
Mode: Balanced | ML/RL: Enabled, Full Stack | Bandit: Thompson Sampling, Switch
Agent Sensitivity: Spoofing 1.0-1.2, Exhaustion 0.9-1.1, Liquidity 0.8-1.0, StatArb 1.1-1.3
Microstructure: All enabled, VPIN 1.2, Toxicity 1.5 | Timeframe: 15min-1H
Forex Majors (EURUSD, GBPUSD):
Mode: Balanced to Conservative | ML/RL: Enabled, Full Stack | Bandit: Thompson Sampling, Blend
Agent Sensitivity: Spoofing 0.8-1.0, Exhaustion 0.9-1.1, Liquidity 0.7-0.9, StatArb 1.2-1.5
Microstructure: All enabled, VPIN 1.0-1.1, Toxicity 1.3-1.5 | Timeframe: 5min-30min
Crypto (BTC, ETH):
Mode: Aggressive to Balanced | ML/RL: Enabled, Full Stack | Bandit: Thompson Sampling OR EXP3-IX
Agent Sensitivity: Spoofing 1.2-1.5, Exhaustion 1.1-1.3, Liquidity 1.2-1.5, StatArb 0.7-0.9
Microstructure: All enabled, VPIN 1.4-1.6, Toxicity 1.8-2.2 | Timeframe: 15min-4H
Futures (ES, NQ, CL):
Mode: Balanced | ML/RL: Enabled, Full Stack | Bandit: UCB1 or Thompson Sampling
Agent Sensitivity: All 1.0-1.2 (balanced)
Microstructure: All enabled, VPIN 1.1-1.3, Toxicity 1.4-1.6 | Timeframe: 5min-30min
Conclusion
Algorithm Predator - Pro synthesizes academic research from market microstructure theory, reinforcement learning, and multi-armed bandit algorithms. Unlike typical indicator mashups, this system implements 15 mathematically rigorous bandit algorithms, deploys a complete RL stack (Q-Learning, TD(λ), Policy Gradient), integrates institutional microstructure metrics (VPIN, Kyle's Lambda), adapts continuously through dual-layer memory and meta-learning, and provides full transparency on approximations and limitations.
The system is designed for serious algorithmic traders who understand that no indicator is perfect, but through proper machine learning, we can build systems that improve over time and adapt to changing markets without manual intervention.
Use responsibly. Risk disclosure applies. Past performance ≠ future results.
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Dinkan Price Action Pro | Pure Price Action Toolkit🔸 Overview
Dinkan Price Action Pro is a pure price-action research toolkit that automatically detects and visualizes Order Blocks (OB), Fair Value Gaps (FVG), merged-candle hidden structures, liquidity zones (including HTF bias liquidity), and trendline & chart-pattern liquidity.
This indicator helps traders align with the Higher Time Frame (HTF) bias — the direction of the dominant institutional wave — and uncover hidden candlestick structures that normal timeframe charts never show.
⚙️ Core Features
✅ Automatic Order Block detection (bullish & bearish)
✅ Fair Value Gaps with real-time fill tracking
✅ Merged-Candle Engine — reveals hidden structures between standard timeframes
✅ Liquidity Zones — equal highs/lows, trendline liquidity & HTF liquidity pools
✅ HTF Bias Engine — detect directional bias across multiple timeframes
✅ Auto Trendlines & Chart Pattern Liquidity
🔍 How It Works (Step by Step)
🕯️ A. Merged Candle Engine (Hidden Structure)
1️⃣ Choose how many candles to merge (e.g., 3–5).
2️⃣ The script groups candles backward from the current bar in continuous sets.
3️⃣ Each merged candle forms using:
• Open = first candle’s open • Close = last candle’s close
• High = highest high • Low = lowest low
4️⃣ These new candles expose “hidden” structures between fixed timeframes — revealing true base-impulse patterns missed by normal charts.
🟩 B. Order Block Detection
Detects consolidation (base) followed by strong impulse.
Marks demand (green) and supply (red) zones automatically.
Strength calculated using impulse range (and volume, if available).
Older, mitigated OBs can be hidden for clarity.
🟦 C. Fair Value Gaps (FVG)
Automatically detects imbalances between consecutive candles.
Unfilled FVGs are highlighted; once filled, zones fade or gray out.
Works dynamically across merged and standard candles.
🟧 D. Liquidity Zones
Finds equal highs/lows, wick clusters, and structural liquidity.
Trendline liquidity and chart-pattern liquidity detected in real time.
Projects HTF liquidity zones from higher charts down to current timeframe.
🔺 E. HTF Bias Engine
Analyzes higher and medium timeframes (HTF/MTF) using CISD-style confirmation.
Bias auto-adjusts or can be manually selected.
🧭 Purpose: Identify the dominant institutional flow and trade in its direction.
⏰ Timeframe Alignment
Recommended structure:
HTF: 4H or 1D
MTF: 1H or 30M
LTF: 15M or 5M
Users may let the script auto-adjust or manually configure each timeframe combination.
📘 Inputs & Settings
🔹 OB sensitivity (Low / Medium / High)
🔹 Volume weighting toggle
🔹 HTF & MTF selection (Auto / Manual)
🔹 Multi-symbol mode
🔹 Visual toggles (OB, FVG, trendlines, merged candles, bias labels)
🔹 Alert toggles (zone touch, bias flip, hidden structure detection)
📊 How to Use — Workflow Example
1️⃣ Load the indicator on your chart.
2️⃣ Check the HTF Bias direction — trade only in that direction.
3️⃣ Identify nearby Order Blocks or FVGs inside HTF liquidity areas.
4️⃣ Watch the Merged Candle View to confirm hidden structures (base + impulse).
5️⃣ Wait for LTF confirmation (e.g., small structure break, wick rejection).
6️⃣ Place stop beyond the opposite OB edge; target next liquidity cluster.
🎯 This workflow aligns your lower-timeframe trades with the dominant higher-timeframe flow.
🧱 Repainting & Stability
Completed OBs and FVGs remain static — they do not repaint.
Real-time zones during candle formation can update until candle closes (standard behavior).
Merged candles are recalculated each bar; once a group closes, it remains fixed historically.
⚠️ Limitations
This is not a buy/sell signal generator.
Volume-weighted features require volume data.
Use responsible risk management and independent confirmation methods.
🔒 Invite-Only / Locked Code
The script is published as invite-only to protect proprietary implementations of:
The merged-candle engine
Liquidity and bias-detection heuristics
Invite-only publishing complies with TradingView rules.
All logic, purpose, and usage are fully described here for transparency.
🧩 Originality & Usefulness
This script is an original integrated system, not a simple mashup.
Each module is interconnected to provide a unified analytical process:
The Merged Candle Engine creates hybrid bars that expose hidden base–impulse patterns.
These merged bars feed into the Order Block and Fair Value Gap logic, refining zone accuracy.
The Liquidity Detector references those zones and merged bars to locate valid structural pools.
Finally, the HTF Bias Engine confirms directional context across multiple pairs and timeframes.
Together, these elements form a dynamic framework that interprets institutional footprints and structure flow — something no single indicator can achieve individually.
The combination produces new analytical value: a precise, adaptive HTF bias alignment and structure-based liquidity map in one visual system.
📜 Disclaimer
This tool is for educational and analytical use only.
It does not constitute financial advice.
Trading involves risk — always perform independent analysis and practice sound risk management.
Past performance does not guarantee future results.
Smart Volume S/R Pro [The_lurker]مؤشر "Smart Volume S/R Pro " هو أداة تحليل فني متقدمة مصممة لمساعدة المتداولين في تحديد مستويات الدعم والمقاومة القوية بناءً على حجم التداول، مع إضافة ميزات تحليلية متطورة مثل تصفية الاتجاه ، مناطق الثقة ، تقييم القوة ، حساب احتمالية الاختراق ، قياس السيولة ، تحديد الأهداف السعرية ، ومستويات فيبوناتشي . وايضا تقديم تسميات (Labels) بجانب كل مستوى دعم ومقاومة، تحتوي على أرقام ومعلومات دقيقة تعكس حالة السوق. هذه التسميات ليست مجرد زينة، بل أدوات تحليلية تساعد المتداولين على اتخاذ قرارات مستنيرة بناءً على بيانات السوقيهدف هذا المؤشر إلى توفير رؤية شاملة للسوق .
الوظائف الرئيسية للمؤشر
1- تحديد مستويات الدعم والمقاومة بناءً على حجم التداول العالي
يقوم المؤشر بتحليل الأشرطة (Bars) السابقة (حتى 300 شريط افتراضيًا) لتحديد النقاط التي شهدت أعلى مستويات حجم التداول.
يرسم خطوط أفقية تمثل مستويات المقاومة (عند أعلى سعر في تلك الأشرطة) والدعم (عند أدنى سعر)، ويمكن للمستخدم اختيار عدد الخطوط المعروضة (من 1 إلى 6).
2- تصفية الاتجاه باستخدام مؤشر ADX
يستخدم المؤشر مؤشر الاتجاه المتوسط (ADX) لتقييم قوة الاتجاه في السوق.
عندما تكون قوة الاتجاه عالية (تتجاوز عتبة محددة، 25 افتراضيًا)، يقلل المؤشر عدد مستويات الدعم والمقاومة المعروضة للتركيز فقط على المستويات الأكثر أهمية.
3- مناطق الثقة الديناميكية
يضيف المؤشر مناطق حول مستويات الدعم والمقاومة بناءً على متوسط المدى الحقيقي (ATR)، مما يساعد المتداولين على تصور النطاقات التي قد يتفاعل فيها السعر مع هذه المستويات.
يمكن تعديل عرض هذه المناطق باستخدام مضاعف ATR.
4- تقييم قوة المستويات
يحسب المؤشر قوة كل مستوى بناءً على حجم التداول، عدد المرات التي تم اختبار المستوى فيها (Touch Count)، وقرب السعر الحالي من المستوى.
يتم عرض درجة القوة (من 0 إلى 100) بجانب كل مستوى إذا تم تفعيل هذه الخاصية.
5- احتمالية الاختراق
يقدّر المؤشر احتمالية اختراق كل مستوى بناءً على الزخم (ROC)، قوة المستوى، والمسافة بين السعر الحالي والمستوى.
يظهر الاحتمال كنسبة مئوية إذا تم تفعيل الخيار، مما يساعد المتداولين على توقع الحركات المحتملة.
6- تحليل السيولة التاريخية
يقيس المؤشر السيولة حول كل مستوى بناءً على حجم التداول في النطاقات القريبة منه.
يمكن عرض قيم السيولة في التسميات أو استخدامها لتعديل عرض الخطوط (الخطوط الأكثر سيولة تظهر أعرض).
7- الأهداف السعرية
عند تفعيل هذه الخاصية، يحسب المؤشر أهداف سعرية للاختراق (Breakout) والارتداد (Reversal) بناءً على الزخم وقوة المستوى وATR.
يمكن عرض هذه الأهداف كنصوص في التسميات أو كخطوط أفقية على الرسم البياني.
8- مستويات فيبوناتشي
يرسم المؤشر مستويات فيبوناتشي (0.0، 0.236، 0.382، 0.5، 0.618، 0.786، 1.0) بناءً على أعلى وأدنى سعر في فترة النظرة الخلفية.
يمكن للمستخدم اختيار أي من هذه المستويات لعرضها أو إخفائها.
9- تنبيه شامل للاختراق
يوفر المؤشر تنبيهًا واحدًا يشمل جميع المستويات، حيث يُطلق التنبيه عندما يخترق السعر أي مستوى دعم أو مقاومة مع رسالة توضح نوع الاختراق والمستوى المخترق.
كيفية عمل المؤشر
الخطوة الأولى: يحدد المؤشر الأشرطة ذات الحجم العالي خلال فترة النظرة الخلفية المحددة (Lookback Period).
الخطوة الثانية: يرسم مستويات الدعم والمقاومة بناءً على أعلى وأدنى الأسعار في تلك الأشرطة، مع مراعاة عدد الخطوط المختارة من المستخدم.
الخطوة الثالثة: يطبق مرشح الاتجاه (إذا كان مفعلاً) لتقليل عدد المستويات في حالة الاتجاه القوي.
الخطوة الرابعة: يضيف التحليلات الإضافية مثل القوة، السيولة، احتمالية الاختراق، والأهداف السعرية، ويرسم مناطق الثقة ومستويات فيبوناتشي حسب الإعدادات.
الخطوة الخامسة: يراقب السعر ويطلق تنبيهًا عند الاختراق.
الإعدادات القابلة للتخصيص
1- فترة النظرة الخلفية (Lookback Period): عدد الأشرطة التي يتم تحليلها (افتراضيًا 300).
2- عدد الخطوط (Number of Lines): من 1 إلى 6 مستويات دعم ومقاومة.
3- الألوان والأنماط: يمكن تغيير ألوان الخطوط وأنماطها (ممتلئة، متقطعة، منقطة).
4- التسميات: تفعيل/تعطيل التسميات، وحجمها، وموقعها، ولون النص.
5- مرشح الاتجاه: تفعيل/تعطيل ADX، وتعديل طوله وعتبته.
6- مناطق الثقة: تفعيل/تعطيل، وتعديل طول ATR ومضاعفه.
7- القوة واحتمالية الاختراق: تفعيل/تعطيل العرض، وتعديل طول ROC.
8- السيولة: تفعيل/تعطيل تأثير السيولة على عرض الخطوط وقيمها في التسميات.
9- الأهداف السعرية: تفعيل/تعطيل الأهداف وعرضها كخطوط.
10- فيبوناتشي: اختيار المستويات المعروضة ولون الخطوط.
فوائد المؤشر
دقة عالية: يعتمد على حجم التداول لتحديد المستويات، مما يجعله أكثر موثوقية من المستويات العشوائية.
مرونة: يوفر خيارات تخصيص واسعة تتيح للمتداولين تكييفه حسب استراتيجياتهم.
تحليل شامل: يجمع بين الدعم والمقاومة، الاتجاه، السيولة، والأهداف في أداة واحدة.
سهولة الاستخدام: التسميات والتنبيهات تجعل من السهل متابعة السوق دون تعقيد.
==================================================================================تسميات (Labels) بجانب كل مستوى دعم ومقاومة، تحتوي على أرقام ومعلومات دقيقة تعكس حالة السوق. هذه التسميات ليست مجرد زينة، بل أدوات تحليلية تساعد المتداولين على اتخاذ قرارات مستنيرة بناءً على بيانات السوق. في هذا الشرح، سنستعرض كل رقم أو قيمة تظهر في التسميات ومعناها العملي.
مكونات التسميات
التسميات تظهر بجانب كل مستوى دعم (Support) ومقاومة (Resistance) وتبدأ بحرف "S" للدعم أو "R" للمقاومة، تليها مجموعة من الأرقام والقيم التي يمكن تفعيلها أو تعطيلها حسب إعدادات المستخدم. إليك تفصيل كل عنصر:
1- عدد اللمسات (Touch Count)
الرمز: يظهر مباشرة بعد "S" أو "R" (مثال: "R: 5" أو "S: 3").
المعنى: يشير إلى عدد المرات التي اختبر فيها السعر هذا المستوى دون اختراقه.
الفائدة: كلما زاد عدد اللمسات، كلما كان المستوى أقوى وأكثر أهمية. على سبيل المثال، إذا كان "R: 5"، فهذا يعني أن السعر ارتد من هذا المستوى 5 مرات، مما يجعله مقاومة قوية محتملة.
2- قوة المستوى (Strength Rating)
الرمز: يظهر بين قوسين مربعين (مثال: " ").
المعنى: قيمة من 0 إلى 100 تعكس قوة المستوى بناءً على عوامل مثل حجم التداول، عدد اللمسات، وقرب السعر الحالي من المستوى.
الفائدة: القيم العالية (مثل 75 أو أكثر) تشير إلى مستوى قوي يصعب اختراقه، بينما القيم المنخفضة (مثل 30 أو أقل) تدل على ضعف المستوى وسهولة اختراقه. يمكن للمتداول استخدام هذا لتحديد المستويات الأكثر موثوقية.
3- احتمالية الاختراق (Breakout Probability)
الرمز: يبدأ بحرف "B" متبوعًا بنسبة مئوية (مثال: "B: 60%").
المعنى: نسبة من 0% إلى 100% تُظهر احتمالية اختراق السعر للمستوى بناءً على الزخم الحالي، قوة المستوى، والمسافة بين السعر والمستوى.
الفائدة: نسبة مرتفعة (مثل 60% أو أكثر) تعني أن السعر قد يخترق المستوى قريبًا، بينما النسب المنخفضة (مثل 20%) تشير إلى احتمال ارتداد السعر. هذا مفيد لتوقع الحركة التالية.
4- قيمة السيولة (Liquidity Value)
الرمز: يبدأ بحرف "L" متبوعًا برقم (مثال: "L: 1200").
المعنى: يمثل متوسط حجم التداول في النطاق القريب من المستوى، مما يعكس السيولة التاريخية حوله.
الفائدة: القيم العالية تدل على وجود سيولة كبيرة، مما يعني أن السعر قد يتفاعل بقوة مع هذا المستوى (إما بالارتداد أو الاختراق). القيم المنخفضة تشير إلى سيولة ضعيفة، مما قد يجعل المستوى أقل تأثيرًا.
5- الأهداف السعرية (Price Targets)
الرمز: يبدأ بـ "BT" (هدف الاختراق) و"RT" (هدف الارتداد) متبوعين بأرقام (مثال: "BT: 150.50 RT: 148.20").
المعنى:
BT (Breakout Target): السعر المحتمل الذي قد يصل إليه السعر بعد اختراق المستوى.
RT (Reversal Target): السعر المحتمل الذي قد يصل إليه السعر إذا ارتد من المستوى.
الفائدة: تساعد المتداولين في تحديد نقاط الخروج المحتملة بعد الاختراق أو الارتداد، مما يسهل وضع خطة تداول دقيقة.
أمثلة عملية
تسمية مقاومة: "R: 4 B: 25% L: 1500 BT: 155.00 RT: 152.00"
المستوى اختُبر 4 مرات، قوته 80 (قوي جدًا)، احتمالية الاختراق 25% (منخفضة، أي احتمال ارتداد أعلى)، السيولة 1500 (مرتفعة)، هدف الاختراق 155.00، هدف الارتداد 152.00.
الاستنتاج: المستوى قوي ومن المرجح أن يرتد السعر منه، لكن إذا اخترق، فقد يصل إلى 155.00.
تسمية دعم: "S: 2 B: 70% L: 800 BT: 145.00 RT: 147.50"
المستوى اختُبر مرتين، قوته 40 (متوسطة إلى ضعيفة)، احتمالية الاختراق 70% (مرتفعة)، السيولة 800 (متوسطة)، هدف الاختراق 145.00، هدف الارتداد 147.50.
الاستنتاج: المستوى ضعيف ومن المحتمل أن يخترقه السعر ليهبط إلى 145.00.
كيفية الاستفادة من التسميات
تحديد القوة والضعف: استخدم قوة المستوى (Strength) لمعرفة ما إذا كان المستوى موثوقًا للارتداد أو عرضة للاختراق.
توقع الحركة: انظر إلى احتمالية الاختراق (Breakout Probability) لتحديد ما إذا كنت ستنتظر اختراقًا أو ترتدًا.
إدارة المخاطر: استخدم الأهداف السعرية (BT وRT) لتحديد نقاط جني الأرباح أو وقف الخسارة.
تقييم السيولة: ركز على المستويات ذات السيولة العالية لأنها غالبًا تكون نقاط تحول رئيسية في السوق.
تأكيد التحليل: ادمج عدد اللمسات مع القوة والسيولة للحصول على صورة كاملة عن أهمية المستوى.
تخصيص التسميات
يمكن للمستخدم تفعيل أو تعطيل أي من هذه القيم (القوة، الاحتمالية، السيولة، الأهداف) من إعدادات المؤشر.
يمكن أيضًا تغيير حجم التسميات (صغير، عادي، كبير)، موقعها (يمين، يسار، أعلى، أسفل)، ولون النص لتناسب احتياجاتك.
التسميات في هذا المؤشر هي بمثابة لوحة تحكم صغيرة بجانب كل مستوى دعم ومقاومة، تقدم لك معلومات فورية عن قوته، احتمالية اختراقه، سيولته، وأهدافه السعرية. بفهم هذه الأرقام، يمكنك تحسين قراراتك في التداول، سواء كنت تبحث عن نقاط دخول، خروج، أو إدارة مخاطر. إذا كنت تريد أداة تجمع بين البساطة والعمق التحليلي .
تنويه:
المؤشر هو أداة مساعدة فقط ويجب استخدامه مع التحليل الفني والأساسي لتحقيق أفضل النتائج.
إخلاء المسؤولية
لا يُقصد بالمعلومات والمنشورات أن تكون، أو تشكل، أي نصيحة مالية أو استثمارية أو تجارية أو أنواع أخرى من النصائح أو التوصيات المقدمة أو المعتمدة من TradingView.
The Smart Volume S/R Pro indicator is an advanced technical analysis tool designed to help traders identify strong support and resistance levels based on trading volume, with the addition of advanced analytical features such as trend filtering, confidence zones, strength assessment, breakout probability calculation, liquidity measurement, price target identification, and Fibonacci levels. It also provides labels next to each support and resistance level, containing accurate numbers and information that reflect the market condition. These labels are not just decorations, but analytical tools that help traders make informed decisions based on market data. This indicator aims to provide a comprehensive view of the market.
Main functions of the indicator
1- Identifying support and resistance levels based on high trading volume
The indicator analyzes previous bars (up to 300 bars by default) to identify the points that witnessed the highest levels of trading volume.
It draws horizontal lines representing resistance levels (at the highest price in those bars) and support (at the lowest price), and the user can choose the number of lines displayed (from 1 to 6).
2- Filtering the trend using the ADX indicator
The indicator uses the Average Directional Index (ADX) to assess the strength of a trend in the market.
When the strength of the trend is high (exceeding a specified threshold, 25 by default), the indicator reduces the number of support and resistance levels displayed to focus only on the most important levels.
3- Dynamic Confidence Zones
The indicator adds zones around support and resistance levels based on the Average True Range (ATR), helping traders visualize the ranges in which the price may interact with these levels.
The width of these zones can be adjusted using the ATR multiplier.
4- Assessing the Strength of Levels
The indicator calculates the strength of each level based on trading volume, the number of times the level has been tested (Touch Count), and the proximity of the current price to the level.
A strength score (from 0 to 100) is displayed next to each level if this feature is enabled.
5- Breakout Probability
The indicator estimates the probability of breaking each level based on momentum (ROC), the strength of the level, and the distance between the current price and the level.
The probability is displayed as a percentage if the option is enabled, helping traders anticipate potential moves.
6- Historical Liquidity Analysis
The indicator measures liquidity around each level based on the trading volume in the ranges near it.
The liquidity values can be displayed in the labels or used to adjust the width of the lines (the most liquid lines appear wider).
7- Price Targets
When this feature is enabled, the indicator calculates price targets for breakout and reversal based on momentum, level strength and ATR.
These targets can be displayed as text in the labels or as horizontal lines on the chart.
8- Fibonacci Levels
The indicator plots Fibonacci levels (0.0, 0.236, 0.382, 0.5, 0.618, 0.786, 1.0) based on the highest and lowest price in the lookback period.
The user can choose which of these levels to display or hide.
9- Comprehensive Breakout Alert
The indicator provides a single alert that includes all levels, where the alert is triggered when the price breaks any support or resistance level with a message explaining the type of breakout and the level broken.
How the indicator works
Step 1: The indicator identifies the bars with high volume during the specified Lookback Period.
Step 2: Draws support and resistance levels based on the highest and lowest prices in those bars, taking into account the number of lines selected by the user.
Step 3: Apply the trend filter (if enabled) to reduce the number of levels in case of a strong trend.
Step 4: Adds additional analyses such as strength, liquidity, breakout probability, and price targets, and draws confidence zones and Fibonacci levels according to the settings.
Step 5: Monitors the price and triggers an alert when the breakout occurs.
Customizable Settings
1- Lookback Period: Number of bars to analyze (default 300).
2- Number of Lines: From 1 to 6 support and resistance levels.
3- Colors and Styles: Line colors and styles can be changed (filled, dashed, dotted).
4- Labels: Enable/disable labels, their size, location, and text color.
5- Trend Filter: Enable/disable ADX, and modify its length and threshold.
6- Confidence Zones: Enable/disable, and modify the ATR length and multiplier.
7- Strength and Breakout Probability: Enable/disable the display, and modify the ROC length.
8- Liquidity: Enable/disable the effect of liquidity on the display of the lines and their values in the labels.
9- Price Targets: Enable/disable the targets and display them as lines.
10- Fibonacci: Choose the displayed levels and the color of the lines.
Indicator Benefits
High Accuracy: It relies on trading volume to determine the levels, which makes it more reliable than random levels.
Flexibility: It provides extensive customization options that allow traders to adapt it to their strategies.
Comprehensive Analysis: Combines support and resistance, trend, liquidity, and targets in one tool. Ease of Use: Labels and alerts make it easy to follow the market without complexity.
Labels next to each support and resistance level contain accurate numbers and information that reflect the market situation. These labels are not just decorations, but analytical tools that help traders make informed decisions based on market data. In this explanation, we will review each number or value that appears in the labels and their practical meaning.
Label Components
Labels appear next to each support and resistance level and begin with the letter "S" for support or "R" for resistance, followed by a set of numbers and values that can be enabled or disabled according to the user's settings. Here is a breakdown of each element:
1- Touch Count
Symbol: Appears immediately after "S" or "R" (example: "R: 5" or "S: 3").
Meaning: Indicates the number of times the price has tested this level without breaking it.
Benefit: The more touches, the stronger and more important the level. For example, if it is "R: 5", it means that the price has bounced off this level 5 times, making it a potentially strong resistance.
2- Strength Rating
Symbol: Appears between square brackets (example: " ").
Meaning: A value from 0 to 100 that reflects the strength of the level based on factors such as trading volume, number of touches, and proximity of the current price to the level.
Benefit: High values (such as 75 or more) indicate a strong level that is difficult to break, while low values (such as 30 or less) indicate a weak level that is easy to break. A trader can use this to determine the most reliable levels.
3- Breakout Probability
Symbol: Starts with the letter "B" followed by a percentage (example: "B: 60%").
Meaning: A percentage from 0% to 100% that shows the probability of the price breaking the level based on the current momentum, the strength of the level, and the distance between the price and the level.
Interest: A high percentage (such as 60% or more) means that the price may soon break through the level, while low percentages (such as 20%) indicate that the price may bounce. This is useful for anticipating the next move.
4- Liquidity Value
Symbol: Starts with the letter "L" followed by a number (example: "L: 1200").
Meaning: Represents the average trading volume in the range near the level, reflecting historical liquidity around it.
Interest: High values indicate high liquidity, meaning that the price may react strongly to this level (either by bouncing or breaking through). Low values indicate low liquidity, which may make the level less influential.
5- Price Targets
Symbol: Starts with "BT" (breakout target) and "RT" (rebound target) followed by numbers (example: "BT: 150.50 RT: 148.20").
Meaning:
BT (Breakout Target): The potential price that the price may reach after breaking the level.
RT (Reversal Target): The potential price that the price may reach if it rebounds from the level.
Utility: Helps traders identify potential exit points after a breakout or rebound, making it easier to develop an accurate trading plan.
Working examples
Resistance label: "R: 4 B: 25% L: 1500 BT: 155.00 RT: 152.00"
Level tested 4 times, strength 80 (very strong), probability of breakout 25% (low, i.e. higher probability of rebound), liquidity 1500 (high), breakout target 155.00, rebound target 152.00.
Conclusion: The level is strong and the price is likely to rebound from it, but if it breaks, it may reach 155.00.
Support Label: "S: 2 B: 70% L: 800 BT: 145.00 RT: 147.50"
Level tested twice, Strength 40 (medium to weak), Breakout Probability 70% (high), Liquidity 800 (medium), Breakout Target 145.00, Rebound Target 147.50.
Conclusion: The level is weak and the price is likely to break it to drop to 145.00.
How to use labels
Determine strength and weakness: Use the level's strength to see if the level is reliable for a bounce or vulnerable to a breakout.
Predict the move: Look at the Breakout Probability to determine whether to wait for a breakout or a bounce.
Risk Management: Use price targets (BT and RT) to set take profit or stop loss points.
Liquidity Evaluation: Focus on levels with high liquidity as they are often key turning points in the market.
Analysis Confirmation: Combine the number of touches with strength and liquidity to get a complete picture of the level’s importance.
Customize Labels
The user can enable or disable any of these values (strength, probability, liquidity, targets) from the indicator settings.
The size of the labels (small, normal, large), their position (right, left, top, bottom), and the color of the text can also be changed to suit your needs.
The labels in this indicator act as a small dashboard next to each support and resistance level, providing you with instant information about its strength, probability of breakout, liquidity, and price targets. By understanding these numbers, you can improve your trading decisions, whether you are looking for entry points, exit points, or risk management. If you want a tool that combines simplicity with analytical depth.
Disclaimer:
The indicator is an auxiliary tool only and should be used in conjunction with technical and fundamental analysis for best results.
Disclaimer
The information and posts are not intended to be, or constitute, any financial, investment, trading or other types of advice or recommendations provided or endorsed by TradingView.
OrderFlow [Adjustable] | FractalystWhat's the indicator's purpose and functionality?
This indicator is designed to assist traders in identifying real-time probabilities of buyside and sellside liquidity .
It allows for an adjustable pivot level , enabling traders to customize the level they want to use for their entries.
By doing so, traders can evaluate whether their chosen entry point would yield a positive expected value over a large sample size, optimizing their strategy for long-term profitability.
For advanced traders looking to enhance their analysis, the indicator supports the incorporation of up to 7 higher timeframe biases .
Additionally, the higher timeframe pivot level can be adjusted according to the trader's preferences,
Offering maximum adaptability to different strategies and needs, further helping to maximize positive EV.
EV=(P(Win)×R(Win))−(P(Loss)×R(Loss))
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What's the purpose of these levels? What are the underlying calculations?
1. Understanding Swing highs and Swing Lows
Swing High: A Swing High is formed when there is a high with 2 lower highs to the left and right.
Swing Low: A Swing Low is formed when there is a low with 2 higher lows to the left and right.
2. Understanding the purpose and the underlying calculations behind Buyside, Sellside and Pivot levels.
3. Identifying Discount and Premium Zones.
4. Importance of Risk-Reward in Premium and Discount Ranges
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How does the script calculate probabilities?
The script calculates the probability of each liquidity level individually. Here's the breakdown:
1. Upon the formation of a new range, the script waits for the price to reach and tap into pivot level level. Status: "⏸" - Inactive
2. Once pivot level is tapped into, the pivot status becomes activated and it waits for either liquidity side to be hit. Status: "▶" - Active
3. If the buyside liquidity is hit, the script adds to the count of successful buyside liquidity occurrences. Similarly, if the sellside is tapped, it records successful sellside liquidity occurrences.
4. Finally, the number of successful occurrences for each side is divided by the overall count individually to calculate the range probabilities.
Note: The calculations are performed independently for each directional range. A range is considered bearish if the previous breakout was through a sellside liquidity. Conversely, a range is considered bullish if the most recent breakout was through a buyside liquidity.
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What does the multi-timeframe functionality offer?
In the adjustable version of the orderflow indicator, you can incorporate up to 7 higher timeframe probabilities directly into the table.
This feature allows you to analyze the probabilities of buyside and sellside liquidity across multiple timeframes, without the need to manually switch between them.
By viewing these higher timeframe probabilities in one place, traders can spot larger market trends and refine their entries and exits with a better understanding of the overall market context.
This multi-timeframe functionality helps traders:
1. Simplify decision-making by offering a comprehensive view of multiple timeframes at once.
2. Identify confluence between timeframes, enhancing the confidence in trade setups.
3. Adapt strategies more effectively, as the higher timeframe pivot levels can be customized to meet individual preferences and goals.
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What are the multi-timeframe underlying calculations?
The script uses the same calculations (mentioned above) and uses security function to request the data such as price levels, bar time, probabilities and booleans from the user-input timeframe.
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How does the Indicator Identifies Positive Expected Values?
OrderFlow indicator instantly calculates whether a trade setup has the potential for positive expected value (EV) in the long run.
To determine a positive EV setup, the indicator uses the formula:
EV=(P(Win)×R(Win))−(P(Loss)×R(Loss))
where:
P(Win) is the probability of a winning trade.
R(Win) is the reward or return for a winning trade, determined by the current risk-to-reward ratio (RR).
P(Loss) is the probability of a losing trade.
R(Loss) is the loss incurred per losing trade, typically assumed to be -1.
By calculating these values based on historical data and the current trading setup, the indicator helps you understand whether your trade has a positive expected value over a large sample size.
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How can I know that the setup I'm going to trade with has a postive EV?
If the indicator detects that the adjusted pivot and buy/sell side probabilities have generated positive expected value (EV) in historical data, the risk-to-reward (RR) label within the range box will be colored blue and red .
If the setup does not produce positive EV, the RR label will appear gray.
This indicates that even the risk-to-reward ratio is greater than 1:1, the setup is not likely to yield a positive EV because, according to historical data, the number of losses outweighs the number of wins relative to the RR gain per winning trade.
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What is the confidence level in the indicator, and how is it determined?
The confidence level in the indicator reflects the reliability of the probabilities calculated based on historical data. It is determined by the sample size of the probabilities used in the calculations. A larger sample size generally increases the confidence level, indicating that the probabilities are more reliable and consistent with past performance.
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How does the confidence level affect the risk-to-reward (RR) label?
The confidence level (★) is visually represented alongside the probability label. A higher confidence level indicates that the probabilities used to determine the RR label are based on a larger and more reliable sample size.
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How can traders use the confidence level to make better trading decisions?
Traders can use the confidence level to gauge the reliability of the probabilities and expected value (EV) calculations provided by the indicator. A confidence level above 95% is considered statistically significant and indicates that the historical data supporting the probabilities is robust. This high confidence level suggests that the probabilities are reliable and that the indicator’s recommendations are more likely to be accurate.
In data science and statistics, a confidence level above 95% generally means that there is less than a 5% chance that the observed results are due to random variation. This threshold is widely accepted in research and industry as a marker of statistical significance. Studies such as those published in the Journal of Statistical Software and the American Statistical Association support this threshold, emphasizing that a confidence level above 95% provides a strong assurance of data reliability and validity.
Conversely, a confidence level below 95% indicates that the sample size may be insufficient and that the data might be less reliable . In such cases, traders should approach the indicator’s recommendations with caution and consider additional factors or further analysis before making trading decisions.
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How does the sample size affect the confidence level, and how does it relate to my TradingView plan?
The sample size for calculating the confidence level is directly influenced by the amount of historical data available on your charts. A larger sample size typically leads to more reliable probabilities and higher confidence levels.
Here’s how the TradingView plans affect your data access:
Essential Plan
The Essential Plan provides basic data access with a limited amount of historical data. This can lead to smaller sample sizes and lower confidence levels, which may weaken the robustness of your probability calculations. Suitable for casual traders who do not require extensive historical analysis.
Plus Plan
The Plus Plan offers more historical data than the Essential Plan, allowing for larger sample sizes and more accurate confidence levels. This enhancement improves the reliability of indicator calculations. This plan is ideal for more active traders looking to refine their strategies with better data.
Premium Plan
The Premium Plan grants access to extensive historical data, enabling the largest sample sizes and the highest confidence levels. This plan provides the most reliable data for accurate calculations, with up to 20,000 historical bars available for analysis. It is designed for serious traders who need comprehensive data for in-depth market analysis.
PRO+ Plans
The PRO+ Plans offer the most extensive historical data, allowing for the largest sample sizes and the highest confidence levels. These plans are tailored for professional traders who require advanced features and significant historical data to support their trading strategies effectively.
For many traders, the Premium Plan offers a good balance of affordability and sufficient sample size for accurate confidence levels.
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What is the HTF probability table and how does it work?
The HTF (Higher Time Frame) probability table is a feature that allows you to view buy and sellside probabilities and their status from timeframes higher than your current chart timeframe.
Here’s how it works:
Data Request : The table requests and retrieves data from user-defined higher timeframes (HTFs) that you select.
Probability Display: It displays the buy and sellside probabilities for each of these HTFs, providing insights into the likelihood of price movements based on higher timeframe data.
Detailed Tooltips: The table includes detailed tooltips for each timeframe, offering additional context and explanations to help you understand the data better.
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What do the different colors in the HTF probability table indicate?
The colors in the HTF probability table provide visual cues about the expected value (EV) of trading setups based on higher timeframe probabilities:
Blue: Suggests that entering a long position from the HTF user-defined pivot point, targeting buyside liquidity, is likely to result in a positive expected value (EV) based on historical data and sample size.
Red: Indicates that entering a short position from the HTF user-defined pivot point, targeting sellside liquidity, is likely to result in a positive expected value (EV) based on historical data and sample size.
Gray: Shows that neither long nor short trades from the HTF user-defined pivot point are expected to generate positive EV, suggesting that trading these setups may not be favorable.
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How to use the indicator effectively?
For Amateur Traders:
Start Simple: Begin by focusing on one timeframe at a time with the pivot level set to the default (50%). This helps you understand the basic functionality of the indicator.
Entry and Exit Strategy: Focus on entering trades at the pivot level while targeting the higher probability side for take profit and the lower probability side for stop loss.
Use simulation or paper trading to practice this strategy.
Adjustments: Once you have a solid understanding of how the indicator works, you can start adjusting the pivot level to other values that suit your strategy.
Ensure that the RR labels are colored (blue or red) to indicate positive EV setups before executing trades.
For Advanced Traders:
1. Select Higher Timeframe Bias: Choose a higher timeframe (HTF) as your main bias. Start with the default pivot level and ensure the confidence level is above 95% to validate the probabilities.
2. Align Lower Timeframes: Switch between lower timeframes to identify which ones align with your predefined HTF bias. This helps in synchronizing your trading decisions across different timeframes.
3. Set Entries with Current Pivot Level: Use the current pivot level for trade entries. Ensure the HTF status label is active, indicating that the probabilities are valid and in play.
4. Target HTF Liquidity Level: Aim for liquidity levels that correspond to the higher timeframe, as these levels are likely to offer better trading opportunities.
5. Adjust Pivot Levels: As you gain experience, adjust the pivot levels to further optimize your strategy for high EV. Fine-tune these levels based on the aggregated data from multiple timeframes.
6. Practice on Paper Trading: Test your strategies through paper trading to eliminate discretion and refine your approach without financial risk.
7. Focus on Trade Management: Ultimately, effective trade management is crucial. Concentrate on managing your trades well to ensure long-term success. By aiming for setups that produce positive EV, you can position yourself similarly to how a casino operates.
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🎲 Becoming the House (Gaining Edge Over the Market):
In American roulette, the house has a 5.26% edge due to the 0 and 00. This means that while players have a 47.37% chance of winning on even-money bets, the true odds are 50%. The discrepancy between the true odds and the payout ensures that, statistically, the casino will win over time.
From the Trader's Perspective: In trading, you gain an edge by focusing on setups with positive expected value (EV). If you have a 55.48% chance of winning with a 1:1 risk-to-reward ratio, your setup has a higher probability of profitability than the losing side. By consistently targeting such setups and managing your trades effectively, you create a statistical advantage, similar to the casino’s edge.
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🎰 Applying the Concept to Trading:
Just as casinos rely on their mathematical edge, you can achieve long-term success in trading by focusing on setups with positive EV. By ensuring that your probabilities and risk-to-reward (RR) ratios are in your favor, you create an edge similar to that of the house.
And by systematically targeting trades with favorable probabilities and managing your trades effectively, you improve your chances of profitability over the long run. Which is going to help you “become the house” in your trading, leveraging statistical advantages to enhance your overall performance.
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What makes this indicator original?
Real-Time Probability Calculations: The indicator provides real-time calculations of buy and sell probabilities based on historical data, allowing traders to assess the likelihood of positive expected value (EV) setups instantly.
Adjustable Pivot Levels: It features an adjustable pivot level that traders can modify according to their preferences, enhancing the flexibility to align with different trading strategies.
Multi-Timeframe Integration: The indicator supports up to 7 higher timeframes, displaying their probabilities and biases in a single view, which helps traders make informed decisions without switching timeframes.
Confidence Levels: It includes confidence levels based on sample sizes, offering insights into the reliability of the probabilities. Traders can gauge the strength of the data before making trades.
Dynamic EV Labels: The indicator provides color-coded EV labels that change based on the validity of the setup. Blue indicates positive EV in a long bias, red indicates positive EV in a short bias and gray signals caution, making it easier for traders to identify high-quality setups.
HTF Probability Table: The HTF probability table displays buy and sell probabilities from user-defined higher timeframes, helping traders integrate broader market context into their decision-making process.
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Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst use, reproduction, or distribution of these proprietary elements is prohibited.
By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
LuxAlgo® - Price Action Concepts™Price Action Concepts™ is a first of it's kind all-in-one indicator toolkit which includes various features specifically based on pure price action.
Order Blocks w/ volume data, real-time market structure (BOS, CHoCH, EQH/L) w/ 'CHoCH+' being a more confirmed reversal signal, a MTF dashboard, Trend Line Liquidity Zones (real-time), Chart Pattern Liquidity Zones, Liquidity Grabs, and much more detailed customization to get an edge trading price action automatically.
Many traders argue that trading price action is better than using technical indicators due to lag, complexity, and noisy charts. Popular ideas within the trading space that cater towards price action trading include "trading like the banks" or "Smart Money Concepts trading" (SMC), most prominently known within the forex community.
What differentiates price action trading from others forms of technical analysis is that it's main focus is on raw price data opposed to creating values or plots derived from price history.
Mostly all of the features within this script are generated purely from price action, more specifically; swing highs, swing lows, and market structure... which allows users to automate their analysis of price action for any market / timeframe.
🔶 FEATURES
This script includes many features based on Price Action; these are highlighted below:
Market structure (BOS, CHoCH, CHoCH+, EQH/L) (Internal & Swing) multi-timeframe
Volumetric Order Blocks & mitigation methods (bullish & bearish)
Liquidity Concepts
Trend Line Liquidity Zones
Chart Pattern Liquidity
Liquidity Grabs Feature
Imbalance Concepts MTF w/ multiple mitigation methods
Fair Value Gaps
Balanced Price Range
Activity Asymmetry
Strong/Weak Highs & Lows w/ volume percentages
Premium & Discount Zones included
Candle Coloring based on market structure
Previous Highs/Lows (Daily, Monday's, Weekly, Monthly, Quarterly)
Multi-Timeframe Dashboard (15m, 1h, 4h, 1d)
Built-in alert conditions & Any Alert() Function Call Conditions
Advanced Alerts Creator to create step-by-step alerts with various conditions
+ more (see changelog below for current features)
🔶 BASIC DEMONSTRATION
In the image above we can see a demonstration of the market structure labeling within this indicator. The automatic BOS & CHoCH labels on top of dashed lines give clear indications of breakouts & reversals within the internal market structure (short term price action). The "CHoCH+" label is also demonstrated as it triggers only if price has already made a new higher low, or lower high.
We can also see a solid line with a larger BOS label in the middle of the chart. This label demonstrates a break of structure taking into account the swing market structure (longer term price action). All of these labels are generated in real-time.
🔶 USAGE & EXAMPLES
In the image below we can see how a trade setup could be created using Order Blocks w/ volume metrics to find points of interest in the market, swing / internal market structure to get indications of longer & shorter term reversals, and trend line liquidity zones to find more likely impulses & breakouts within trends.
We can see in the next image below that price came down to the highest volume order block marked out previously as our point of interest for an entry used in confluence with the overall market structure being bullish (swing CHoCH). Due to price closing below the middle Order Block at (24.77%), we saw it was mitigated, and then price revisited liquidity above the Trend Line zone above, leading us to the first Order Block as a target.
You will notice the % values adjust as Order Blocks are touched & mitigated, aligning with the correct volume detected when the Order Block was established.
In the image below we can see more features from within Price Action Concepts™ indicator, including Chart Pattern Liquidity, Fair Value Gaps (one of many Imbalance Concepts), Liquidity Grabs, as well as the primary market structures & OBs.
By using multiple features as such, users can develop a greater interpretation of where liquidity rests in the market, which allows them to develop trading plans a lot easier. Liquidity Grabs are highlighted as blue/red boxes on the wicks during specific price action that indicates the market has made an impulse specifically to take out resting buy or sell side orders.
We can notice in the trade demonstrated below (hindsight example) how price often moves to the areas of the most liquidity, even if unexpected according to classical technical analysis performed by retail traders such as chart patterns. Wicks to take out orders above & potentially trap traders are much more noticeable with features such as these.
The Chart Patterns which can be detected include:
Ascending/Descending Wedges (Asc/Desc Wedge)
Ascending/Descending Broadening Wedges (Asc/Desc BW)
Ascending/Descending/Symmetrical Triangles (Asc/Desc/Sym Triangle)
Double Tops/Bottoms (Double Top/Double BTM)
Head & Shoulders (H&S)
Inverted Head & Shoulders (IH&S)
General support & resistance during undetected patterns
In the image below we can see more features from within the indicator, including Balanced Price Range (another imbalance method similar to FVG), Market Structure Candle Coloring, Accumulation & Distribution zones, Premium & Discount zones w/ a percentage on each zone, the MTF dashboard, as well as the Previous Daily Highs & Lows (one of many highs/lows) displayed on the chart automatically.
The colored candles use more specific market structure analysis, specifically allowing users to visualize when trends are considered "normal" or "strong". By utilizing other features alongside this market structure analysis, such as noticing price retesting the PDL level + the Equilibrium as resistance, a Balanced Price Range below price, the discount with a high 72% metric, and the MTF dashboard displaying an overall bearish structure...
...users can instantly gain a deeper interpretation of price action, make highly confluent trading plans while avoiding classical technical indicators, and use traditional retail trading concepts such as chart patterns / trend lines to their advantage in finding logical areas of liquidity & points of interest in the market.
The image below shows the previous chart zoomed in with 2 liquidity concepts re-enabled & used alongside a new range targeting the same Discount zone.
🔶 SETTINGS
Market Structure Internal: Allows the user to select which internal structures to display (BOS, CHoCH, or None).
Market Structure Swing: Allows the user to select which swing structures to display (BOS, CHoCH, or None).
MTF Scanner: See market structure on various timeframes & how many labels are active consecutively.
Equal Highs & Lows: Displays EQH / EQL labels on chart for detecting equal highs & lows.
Color Candles: Plots candles based on the internal & swing structures from within the indicator on the chart.
Order Blocks Internal: Enables Internal Order Blocks & allows the user to select how many most recent Internal Order Blocks appear on the chart as well as select a color.
Order Blocks Swing: Enables Swing Order Blocks & allows the user to select how many most recent Swing Order Blocks appear on the chart as well as select a color.
Mitigation Method: Allows the user to select how the script mitigates an Order Block (close, wick, or average).
Internal Buy/Sell Activity: Allows the user to display buy/sell activity within Order Blocks & decide their color.
Show Metrics: Allows the user to display volume % metrics within the Order Blocks.
Trend Line Liquidity Zones: Allows the user to display Trend Line Zones on the chart, select the number of Trend Lines visible, & their colors.
Chart Pattern Liquidity: Allows the user to display Chart Patterns on the chart, select the significance of the pattern detection, & their colors.
Liquidity Grabs: Allows the user to display Liquidity Grabs on the chart.
Imbalance Concepts: Allows the user to select the type of imbalances to display on the chart as well as the styling, mitigation method, & timeframe.
Auto FVG Threshold: Filter out non-significant fair value gaps.
Premium/ Discount Zones: Allows the user to display Premium, Discount , and Equilibrium zones on the chart
Accumulation / Distribution: Allows the user to display accumulation & distribution consolidation zones with an optional Consolidation Zig-Zag setting included.
Highs/Lows MTF: Displays previous highs & lows as levels on the chart for the previous Day, Monday, Week, Month, or quarter (3M).
General Styling: Provides styling options for market structure labels, market structure theme, and dashboard customization.
Any Alert() Function Call Conditions: Allows the user to select multiple conditions to use within 1 alert.
🔶 CONCLUSION
Price action trading is a widely respected method for its simplicity & realistic approach to understanding the market itself. Price Action Concepts™ is an extremely comprehensive product that opens the possibilities for any trader to automatically display useful metrics for trading price action with enhanced details in each. While this script is useful, it's critical to understand that past performance is not necessarily indicative of future results and there are many more factors that go into being a profitable trader.
🔶 HOW TO GET ACCESS
You can see the Author's instructions below to get instant access to this indicator & our premium suite.
SMC Pro+ ICT v4 Enhanced - FINAL🎯 SMC Pro+ ICT v4 Enhanced - Complete Smart Money Trading System📊 Professional All-in-One Indicator for Smart Money Concepts & ICT MethodologyThe SMC Pro+ ICT v4 Enhanced is a comprehensive trading system that combines Smart Money Concepts (SMC) with Inner Circle Trader (ICT) methodology. This indicator provides institutional-grade market structure analysis, liquidity mapping, and volume profiling in one powerful package.✨ CORE FEATURES🏗️ Advanced Market Structure Detection
MSS (Market Structure Shift) - Identifies major trend reversals with precision
BOS (Break of Structure) - Confirms trend continuation moves
CHoCH (Change of Character) - Detects internal structure shifts
Modern LuxAlgo-Style Lines - Clean, professional visualization
Dual Sensitivity System - External structure (major swings) + Internal structure (minor swings)
Customizable Labels - Tiny, Small, or Normal sizes
Structure Break Visualization - Clear break point markers
💎 Supply & Demand Zones (POI - Point of Interest)
Institutional Order Blocks - Where smart money enters/exits
ATR-Based Zone Sizing - Dynamically adjusted to market volatility
Smart Overlap Detection - Prevents cluttered charts
Historical Zone Tracking - Maintains up to 50 zones
POI Central Lines - Pinpoint entry/exit levels
Auto-Extension - Zones extend to current price
Auto-Cleanup - Removes broken zones automatically
📦 Fair Value Gap (FVG) Detection
Bullish & Bearish FVGs - Institutional inefficiencies
Consequent Encroachment (CE) - 50% fill levels
Auto-Delete Filled Gaps - Keeps charts clean
Customizable Lookback - 1-30 days of history
Color-Coded Zones - Easy visual identification
CE Line Styles - Dotted, Dashed, or Solid
🚀 Enhanced PVSRA Volume Analysis
This is one of the most powerful features:
200% Volume Candles - Extreme institutional activity (Lime/Red)
150% Volume Candles - High institutional interest (Blue/Fuchsia)
Volume Climax Detection - Major reversal signals with 2.5x+ volume
Exhaustion Signals - Identifies buying/selling exhaustion with high accuracy
Enhanced Volume Divergence - NEW! High-quality reversal detection
Price makes lower low, Volume makes higher low = Bullish Divergence
Price makes higher high, Volume makes lower high = Bearish Divergence
Strict trend context filtering for accuracy
Rising/Falling Volume Patterns - Momentum confirmation (allows 1 exception in 3 bars)
Volume Spread Analysis - Price range × Volume for true strength
Body/Wick Ratio Analysis - Candle structure quality
ATR Normalization - Adjusts for different market volatility
Volume Profile Indicators - 🔥 EXTREME, ⚡ VERY HIGH, 📈 HIGH, ✅ ABOVE AVG
💧 Advanced Liquidity System
Smart money targets these levels:
Weekly High/Low Liquidity - Major institutional targets
Daily High/Low Liquidity - Intraday key levels
4H Session Liquidity - Short-term targets
Distance Indicators - Shows % distance from current price
Strength Indicators - Identifies high-probability sweeps
Swept Level Detection - Tracks executed liquidity grabs
Customizable Line Styles - Width, length, offset controls
Color-Coded Levels - Easy visual hierarchy
🎯 Master Bias System
Data-driven directional bias with 9-factor scoring:
Bull/Bear Bias Calculation - 0-100% scoring system
Multi-Timeframe Analysis - Daily, 4H, 1H trend alignment
Kill Zone Integration - London (2-5 AM) & NY (8-11 AM) sessions
EMA Alignment Factor - Trend confirmation
Volume Confirmation - Adds 5% when volume supports direction
Range Filter Integration - Adds 10% for trending markets
Session Context - Above/below session midpoint scoring
Bias Strength Rating - STRONG (>75%), MODERATE (60-75%), WEAK (<60%)
Real-Time Updates - Dynamic recalculation
📈 Premium & Discount Zones
Fibonacci-based institutional pricing:
Extreme Premium - Above 78.6% (Overvalued)
Premium Zone - 61.8% - 78.6% (Expensive)
Equilibrium - 38.2% - 61.8% (Fair Value)
Discount Zone - 21.4% - 38.2% (Cheap)
Extreme Discount - Below 21.4% (Undervalued)
Visual Zone Boxes - Color-coded for instant recognition
200-500 Bar Lookback - Customizable range calculation
🔄 Range Filter
Advanced trend detection:
Smoothed Range Calculation - Eliminates noise
Dynamic Support/Resistance - Auto-adjusting levels
Upward/Downward Counters - Measures trend strength
Color-Coded Line - Green (uptrend), Red (downtrend), Orange (ranging)
Adjustable Period - 1-200 bars
Multiplier Control - Fine-tune sensitivity (0.1-10.0)
🌊 Liquidity Zones (Vector Zones)
PVSRA-based horizontal liquidity:
Above Price Zones - Resistance clusters
Below Price Zones - Support clusters
Maximum 500 Zones - Professional-grade capacity
Body/Wick Definition - Choose zone boundaries
Auto-Cleanup - Removes cleared zones
Color Override - Custom styling options
Transparency Control - 0-100% opacity
📊 EMA System
Triple EMA trend confirmation:
Fast EMA (9) - Green line - Immediate trend
Medium EMA (21) - Blue line - Short-term trend
Slow EMA (50) - Red line - Major trend
EMA Alignment Detection - Bull/Bear stack confirmation
Dashboard Integration - Status: 📈 BULL ALIGN, 📉 BEAR ALIGN, 🔀 MIXED
Adjustable Lengths - Customize all three EMAs (5-200)
🎯 IDM (Institutional Decision Maker) Levels
Key institutional price levels:
Latest IDM Detection - 20-bar pivot lookback
Extended Lines - Projects 50 bars into future
Customizable Styles - Solid, Dashed, or Dotted
Line Width Control - 1-5 pixels
Color Selection - Match your chart theme
Price Label - Shows exact level with tick precision
📱 Professional Dashboard
Real-time market intelligence panel:
🎯 SIGNAL - 🟢 LONG, 🔴 SHORT, ⏳ WAIT, 🛑 NO TRADE
🎲 BIAS - Bull/Bear with STRONG/MODERATE/WEAK rating
📊 BULL/BEAR Scores - 0-100% percentage display
💎 ZONE - Current premium/discount location
🕐 KZ - Kill Zone status (🇬🇧 LONDON/🇺🇸 NY/⏸️ OFF)
🏗️ STRUCT - Market structure status (BULLISH/BEARISH/NEUTRAL)
⚡ EVENT - Last structure event (MSS/BOS)
⚡ INT - Internal structure trend
🎯 IDM - Latest institutional level
📊 EMA - EMA alignment status
🔄 RF - Range Filter direction
📊 PVSRA - Volume status (🚀 CLIMAX/📈 RISING/📉 FALLING)
📅 MTF - Multi-timeframe alignment (✅ FULL/⚠️ PARTIAL/❌ CONFLICT)
💪 CONF - Confidence score (0-100%)
📊 VOL - Volume ratio (e.g., 1.8x average)
Advanced Metrics (Toggle On/Off):
📏 RSI - Value + Status (OVERBOUGHT/STRONG/NEUTRAL/WEAK/OVERSOLD)
📈 MACD - Value + Direction (BULL/BEAR)
🌪️ VOL - Volatility state (⚠️ EXTREME/🔥 HIGH/📊 NORMAL/😴 LOW)
🔊 VOL PROF - Volume profile ratio
⏱️ TF - Current timeframe
Dashboard Customization:
4 Positions - Top Left, Top Right, Bottom Left, Bottom Right
3 Sizes - Small, Normal, Large
2 Modes - Compact (MTF combined) or Full (separate rows)
Professional Design - Dark theme with color-coded cells
🎮 TRADING SIGNALS & SETUP SCORING🟢 LONG Setup Requirements (9-Factor Confidence Score)
MTF Alignment - Daily/4H/1H/Structure all bullish (+2 points for full, +1 for partial)
Volume Confirmation - Above 1.2x average (+1 point)
Structure Event - MSS or BOS bullish (+2 points)
EMA Alignment - 9 > 21 > 50 (+1 point)
Kill Zone Active - London/NY + Bull bias >75% (+2 points)
Bias Match - Master bias matches structure trend (+1 point)
Confidence Threshold - >60% minimum for signal
🔴 SHORT Setup Requirements
Same 9-factor system but inverted for bearish conditions.💪 Confidence Levels
75-100% - ⭐ HIGH CONFIDENCE (Strong setup, all factors aligned)
50-74% - ⚠️ MODERATE (Good setup, partial alignment)
0-49% - ❌ LOW CONFIDENCE (Wait for better setup)
🎯 Signal Output
🟢 LONG - Bull bias + Bullish structure + >60% confidence
🔴 SHORT - Bear bias + Bearish structure + >60% confidence
⏳ WAIT LONG - Bull bias but low confidence
⏳ WAIT SHORT - Bear bias but low confidence
🛑 NO TRADE - Neutral bias or conflicting signals
🔔 COMPREHENSIVE ALERT SYSTEM (12 Alerts)Structure Alerts
⚡ MSS Bullish - Major bullish reversal
⚡ MSS Bearish - Major bearish reversal
📈 BOS Bullish - Bullish continuation
📉 BOS Bearish - Bearish continuation
⚠️ CHoCH Bullish - Internal bullish shift
⚠️ CHoCH Bearish - Internal bearish shift
Bias & Confidence Alerts
🟢 Bias Shift Bull - Master bias turns bullish
🔴 Bias Shift Bear - Master bias turns bearish
⭐ High Confidence - Setup reaches 75%+ confidence
Volume Alerts (High Probability)
🚀 Volume Climax Buy - Extreme bullish volume spike
💥 Volume Climax Sell - Extreme bearish volume spike
⚠️ Selling Exhaustion - Potential bullish reversal
⚠️ Buying Exhaustion - Potential bearish reversal
📊 Bullish Volume Divergence - High-quality bullish reversal signal
📊 Bearish Volume Divergence - High-quality bearish reversal signal
🎨 EXTENSIVE CUSTOMIZATIONColors & Styling
✅ All colors customizable for every component
✅ Supply/Demand zone colors + outlines
✅ FVG colors (bullish/bearish)
✅ PVSRA candle colors (6 types)
✅ Liquidity level colors (Weekly/Daily/4H/Swept)
✅ Structure line colors
✅ Premium/Equilibrium/Discount zone colorsDisplay Controls
✅ Toggle each feature on/off independently
✅ Adjustable sensitivities (Structure: 5-30, Internal: 3-15)
✅ Label size controls (Tiny/Small/Normal)
✅ Line width adjustments (1-5 pixels)
✅ Transparency controls (0-100%)
✅ Extension lengths (20-100 bars)
✅ Lookback periods (50-500 bars)Volume Settings
✅ PVSRA symbol override (trade one asset, analyze another)
✅ Climax threshold (2.0-5.0x)
✅ Rising volume bar count (2-5 bars)
✅ Divergence filters (Strict/Lenient)
✅ Divergence minimum bars (10-30)
✅ Volume threshold multiplier (1.0-2.0x)Dashboard Settings
✅ Position (4 corners)
✅ Size (Small/Normal/Large)
✅ Compact/Full mode
✅ Show/Hide advanced metrics
✅ Show/Hide EMA status💡 BEST PRACTICES & USAGE TIPS⏰ Optimal Timeframes
Scalping - 1m, 5m (Use Kill Zones, Volume Climax, FVG)
Day Trading - 5m, 15m, 1H (Use Structure, Liquidity, Bias)
Swing Trading - 4H, Daily (Use MTF, Premium/Discount, Structure)
Position Trading - Daily, Weekly (Use major structure, liquidity)
🎯 Asset Classes
✅ Forex - All pairs (especially majors during Kill Zones)
✅ Crypto - BTC, ETH, altcoins (24/7 liquidity)
✅ Stocks - All stocks and indices (use session times)
✅ Commodities - Gold, Silver, Oil (high volume periods)
✅ Indices - S&P 500, NASDAQ, DAX, etc.🔥 High-Probability Setups
The Perfect Storm
MSS in direction of daily trend
Kill Zone active
Volume climax
Confidence >75%
Price in discount (long) or premium (short)
Volume Divergence Play
Enhanced volume divergence signal
CHoCH confirms direction change
Price near liquidity level
FVG forms for entry
Liquidity Sweep
Price sweeps weekly/daily high/low
Immediate rejection (selling/buying exhaustion)
Structure shift (MSS)
Volume confirmation
Structure Retest
BOS breaks structure
Price returns to POI/FVG
Volume confirms (>1.2x)
Kill Zone active
📊 Multi-Timeframe Analysis
Higher Timeframe - Identify trend & structure (Daily/4H)
Trading Timeframe - Find entries (15m/1H)
Lower Timeframe - Precise entries (1m/5m)
Look for MTF alignment - Dashboard shows ✅ FULL or ⚠️ PARTIAL
⚠️ Risk Management
Always use stop-loss (below/above recent structure)
Position size: 1-2% risk per trade
Target liquidity levels for take profit
Use supply/demand zones for SL placement
Watch for exhaustion signals near targets
Smart Money Decoded [GOLD]Title: Smart Money Decoded
Description:
Introduction
Smart Money Decoded is a comprehensive, institutional-grade visualization suite designed to simplify the complex world of Smart Money Concepts (SMC). While many indicators flood the chart with noise, this tool focuses on clarity, precision, and high-probability structure.
This script is built for traders who follow the "Inner Circle Trader" (ICT) methodologies but struggle to identify valid Zones, Displacement, and Liquidity Sweeps in real-time.
💎 Key Features & Logic
1. Refined Market Structure (BOS & CHoCH)
Instead of marking every minor pivot, this script uses a filtered Swing High/Low detection system.
HH/LL/LH/HL Labels: Only significant structure points are mapped.
BOS (Break of Structure): Marks trend continuations in the direction of the bias.
CHoCH (Change of Character): Marks potential trend reversals.
2. Advanced Order Blocks (with "Strict Mode")
Not all down-candles before an up-move are Order Blocks. This script separates the weak from the strong.
Standard OBs: Visualized with standard transparency.
⚡ SWEEP OBs (High Probability): Order Blocks that explicitly swept liquidity (Stop Hunt) before the reversal are highlighted with a thicker border, brighter color, and a ⚡ symbol. These are your high-probability "Turtle Soup" entries.
Strict Mode Toggle: In the settings, you can choose to hide all weak OBs and only see the ones that swept liquidity.
3. Dynamic Breaker Blocks
A true ICT Breaker is a failed Order Block that trapped liquidity.
This script automatically detects when a valid OB is mitigated (broken through) and projects it forward as a Breaker Block.
This ensures you are trading off valid flipped zones (Support becomes Resistance, Resistance becomes Support).
4. Fair Value Gaps (FVG)
Automatically detects Imbalances (Imbalance/Inefficiency).
Includes an ATR Filter to ignore tiny, insignificant gaps, keeping your chart clean.
Option to show the Consequent Encroachment (50% CE) level for precision entries.
5. Liquidity Zones (BSL / SSL)
Automatically plots Buy Side Liquidity (BSL) and Sell Side Liquidity (SSL) at key swing points.
Once price sweeps these levels, the zone is removed or marked as "Swept," helping you identify when the draw on liquidity has been met.
6. Institutional Data Panel
A dashboard in the top right corner displays:
Market Bias: Bullish/Bearish/Neutral based on structure.
Premium/Discount: Tells you if price is in the expensive (Premium) or cheap (Discount) part of the current dealing range.
Active Zones: Counts of current open arrays.
⚙️ How To Use This Indicator
Identify Bias: Look at the Structure Labels (HH/LL) and the Panel. Are we making Higher Highs?
Wait for the Trap: Look for a Liquidity Sweep (BSL/SSL taken) or a ⚡ Sweep OB.
Entry Confirmation: Watch for a return to a Fair Value Gap (FVG) or a retest of a Breaker Block (BRK).
Manage Risk: Use the visuals to place stops above/below invalidation points.
Customization:
Go to the settings to toggle "Strict Mode" for Order Blocks, change colors to match your theme, or adjust the lookback periods to fit your specific asset (Forex, Crypto, or Indices).
📚 Credits & Acknowledgments
This script is an educational tool based on the public teachings of Michael J. Huddleston (The Inner Circle Trader - ICT).
Concepts used: Order Blocks, Breakers, FVGs, Market Structure, Liquidity Pools.
Credit is fully given to ICT for originating these concepts and sharing them with the world.
⚠️ Disclaimer
This script is NOT affiliated with, endorsed by, or connected to Michael J. Huddleston (ICT) in any way. It is an independent coding project intended for educational purposes and visual assistance.
Trading involves substantial risk. This indicator does not guarantee profits. Always use proper risk management. Trust your analysis first, and use indicators as confluence.
#Smart Money Concepts, #SMC, #ICT,#Liquidity, #Market Structure, #Trend, #Price Action.
CandelaCharts - Turtle Soup Model📝 Overview
The ICT Turtle Soup Model indicator is a precision-engineered tool designed to identify high-probability reversal setups based on ICT’s renowned Turtle Soup strategy.
The Turtle Soup Model is a classic reversal setup that exploits false breakouts beyond previous swing highs or lows. It targets areas where retail traders are trapped into breakout trades, only for the price to reverse sharply in the opposite direction.
Price briefly breaks a previous high (for short setups) or low (for long setups), triggering stop orders and pulling in breakout traders. Once that liquidity is taken, smart money reverses price back inside the range, creating a high-probability fade setup.
📦 Features
Liquidity Levels: Projects forward-looking liquidity levels after a Turtle Soup model is formed, highlighting potential price targets. These projected zones act as magnet levels—areas where price is likely to reach based on the liquidity draw narrative. This allows traders to manage exits and partials with more precision.
Market Structure Shift (MSS): Confirms reversal strength by detecting a bullish or bearish MSS after a sweep. Acts as a secondary confirmation to filter out weak setups.
Custom TF Pairing: Choose your own combination of entry timeframe and context timeframe. For example, trade 5m setups inside a 1h HTF bias — perfect for aligning microstructure with macro intent.
HTF & LTF PD Arrays: Displays HTF PD Arrays (e.g., Fair Value Gaps, Inversion Fair Value Gaps) to serve as confluence zones.
History: Review and backtest past Turtle Soup setups directly on the chart. Toggle historical models on/off to study model behavior across different market conditions.
Killzone Filter: Limit signals to specific trading sessions or time blocks (e.g., New York AM, London, Asia, etc). Avoid signals in low-liquidity or choppy environments.
Standard Deviation: Calculates and projects four levels of standard deviation from the point of model confirmation. These zones help identify overextended moves, mean-reversion opportunities, and confluence with liquidity or PD arrays.
Dashboard: The dashboard displays the active model type, remaining time of the HTF candle, current bias, asset name, and date—providing real-time context and signal clarity at a glance.
⚙️ Settings
Core
Status: Filter models based on status
Bias: Controls what model type will be displayed, bullish or bearish
Fractal: Controls the timeframe pairing that will be used
High Probability Models: Detects and plots only the high-probability models
Sweeps
Sweep: Shows the sweep that forms a model
I-sweep: Controls the visibility of invalidated sweeps
D-purge: Plots the double purge sweeps
S-area: Highlights the sweep area
Liquidity
Liquidity: Displays the liquidity levels that belong to the model
MSS
MSS: Displays the Market Structure Shift for a model
History
History: Controls the number of past models displayed on the chart
Filters
Asia: Filter models based on Asia Killzone hours
London: Filter models based on London Killzone hours
NY AM: Filter models based on NY AM Killzone hours
NY Launch: Filter models based on NY Launch Killzone hours
NY PM: Filter models based on NY PM Killzone hours
Custom: Filter models based on user Custom hours
HTF
Candles: Controls the number of HTF candles that will be visible on the chart
Candles T: Displays the model’s third timeframe candle, which serves as a confirmation of directional bias
NY Open: Display True Day Open line
Offset: Controls the distance of HTF from the current chart
Space: Controls the space between HTF candles
Size: Controls the size of HTF candles
PD Array: Displays ICT PD Arrays
CE Line: Style the equilibrium line of PD Array
Border: Style the border of the PD Array
LTF
H/L Line: Displays on the LTF chart the High and Low of each HTF candle
O/C Line: Displays on the LTF chart the Open and Close of each HTF candle
PD Array: Displays ICT PD Arrays
CE Line: Style the equilibrium line of PD Array
Border: Style the border of the PD Array
Standard Deviation
StDev: Controls standard deviation of available levels
Labels: Controls the size of standard deviation levels
Lines: Controls the line widths and color of standard deviation levels
Dashboard
Panel: Display information about the current model
💡 Framework
The Turtle Soup Model is designed to detect and interpret false breakout patterns by analyzing key price action components, each playing a vital role in identifying liquidity traps and generating actionable reversal signals.
The model incorporates the following timeframe pairing:
15s - 5m - 15m
1m - 5m - 1H
2m - 15m - 2H
3m - 30m - 3H
5m - 60m - 4H
15m - 1H - 8H
30m - 3H - 12H
1H - 4H - 1D
4H - 1D - 1W
1D - 1W - 1M
1W - 1M - 6M
1M - 6M - 12M
Below are the key components that make up the model:
Sweep
D-purge
MSS
Liquidity
Standard Deviation
HTF & LTF PD Arrays
The Turtle Soup Model operates through a defined lifecycle that identifies its current state and determines the validity of a trade opportunity.
The model's lifecycle includes the following statuses:
Formation (grey)
Invalidation (red)
Pre-Invalidation (purple)
Success (green)
By incorporating the phases of Formation, Invalidation, and Success, traders can effectively manage risk, optimize position handling, and capitalize on the high-probability opportunities presented by the Turtle Soup Model.
⚡️ Showcase
Introducing the Turtle Soup Model — a powerful trading tool engineered to detect high-probability false breakout reversals. This indicator helps you pinpoint liquidity sweeps, confirm market structure shifts, and identify precise entry and exit points, enabling more confident, informed, and timely trading decisions.
LTF PD Array
LTF PD Arrays are essential for model formation—a valid Turtle Soup setup will only trigger if a qualifying LTF PD Array is present near the sweep zone.
HTF PD Array
HTF PD Arrays provide macro-level context and are used to validate the direction and strength of the potential reversal.
Timeframe Alignment
In the Turtle Soup trading model, timeframe alignment is an essential structural component. The model relies on multi-timeframe context to identify high-probability reversal setups based on failed breakouts.
High-Probability Model
A high-probability setup forms when key elements align: a Sweep, Market Structure Shift (MSS), LTF and HTF PD Arrays.
Killzone Filters
Filter Turtle Soup Models based on key market sessions: Asia, London, New York AM, New York Launch, and New York PM . This allows you to focus on high-liquidity periods where smart money activity is most likely to occur, improving both the quality and timing of your trade setups.
Unlock your trading edge with the Turtle Soup Model — your go-to tool for sharper insights, smarter decisions, and more confident execution in the markets.
🚨 Alerts
This script offers alert options for all model types. The alerts need to be set up manually from TradingView.
Bearish Model
A bearish model alert is triggered when a model forms, signaling a high sweep, MS,S and LTF PD Array.
Bullish Model
A bullish model alert is triggered when a model forms, signaling a low sweep, MSS and LTF PD Array.
⚠️ Disclaimer
These tools are exclusively available on the TradingView platform.
Our charting tools are intended solely for informational and educational purposes and should not be regarded as financial, investment, or trading advice. They are not designed to predict market movements or offer specific recommendations. Users should be aware that past performance is not indicative of future results and should not rely on these tools for financial decisions. By using these charting tools, the purchaser agrees that the seller and creator hold no responsibility for any decisions made based on information provided by the tools. The purchaser assumes full responsibility and liability for any actions taken and their consequences, including potential financial losses or investment outcomes that may result from the use of these products.
By purchasing, the customer acknowledges and accepts that neither the seller nor the creator is liable for any undesired outcomes stemming from the development, sale, or use of these products. Additionally, the purchaser agrees to indemnify the seller from any liability. If invited through the Friends and Family Program, the purchaser understands that any provided discount code applies only to the initial purchase of Candela's subscription. The purchaser is responsible for canceling or requesting cancellation of their subscription if they choose not to continue at the full retail price. In the event the purchaser no longer wishes to use the products, they must unsubscribe from the membership service, if applicable.
We do not offer reimbursements, refunds, or chargebacks. Once these Terms are accepted at the time of purchase, no reimbursements, refunds, or chargebacks will be issued under any circumstances.
By continuing to use these charting tools, the user confirms their understanding and acceptance of these Terms as outlined in this disclaimer.
CandelaCharts - Buyside & Sellside 📝 Overview
The Buyside & Sellside Liquidity Indicator is designed to identify and emphasize one of the foundational concepts within the ICT (Inner Circle Trader) trading methodology: liquidity levels.
This tool focuses on pinpointing key areas in the market where buy-side and sell-side liquidity is concentrated, providing traders with insights into potential price targets, reversal zones, and institutional order flow behavior.
By highlighting these liquidity zones, the indicator serves as a strategic aid in understanding market dynamics and enhancing decision-making in alignment with ICT principles.
📦 Features
Buyside & Sellside Liquidity
Invalidated Liquidity
Threshold
Styling
⚙️ Settings
Liquidity: Controls visibility of Bullish/Bearish Liquidity levels.
Invalidated: Displays the invalidated liquidity levels.
Levels: Controls the number of Liquidity levels that will be displayed.
Line Style: Customize the line style and width.
Threshold: Filter by swing points the Liquidity levels.
Labels: Control the Labels visibility.
⚡️ Showcase
Buyside & Sellside
Invalidated
🚨 Alerts
This script offers alert options for all signal types.
Bearish Signal
A bearish signal is generated when the price reaches a Buyside Liquidity level.
Bullish Signal
A bullish signal is generated when the price reaches a Sellside Liquidity level.
⚠️ Disclaimer
Trading involves significant risk, and many participants may incur losses. The content on this site is not intended as financial advice and should not be interpreted as such. Decisions to buy, sell, hold, or trade securities, commodities, or other financial instruments carry inherent risks and are best made with guidance from qualified financial professionals. Past performance is not indicative of future results.
RSI Analysis with Statistical Summary Scientific Analysis of the Script "RSI Analysis with Statistical Summary"
Introduction
I observed that there are outliers in the price movement liquidity, and I wanted to understand the RSI value at those points and whether there are any notable patterns. I aimed to analyze this statistically, and this script is the result.
Explanation of Key Terms
1. Outliers in Price Movement Liquidity: An outlier is a data point that significantly deviates from other values. In this context, an outlier refers to an unusually high or low liquidity of price movement, which is the ratio of trading volume to the price difference between the open and close prices. These outliers can signal important market changes or unusual trading activities.
2. RSI (Relative Strength Index): The RSI is a technical indicator that measures the speed and change of price movements. It ranges from 0 to 100 and helps identify overbought or oversold conditions of a trading instrument. An RSI value above 70 indicates an overbought condition, while a value below 30 suggests an oversold condition.
3. Mean: The mean is a measure of the average of a dataset. It is calculated by dividing the sum of all values by the number of values. In this script, the mean of the RSI values is calculated to provide a central tendency of the RSI distribution.
4. Standard Deviation (stdev): The standard deviation is a measure of the dispersion or variation of a dataset. It shows how much the values deviate from the mean. A high standard deviation indicates that the values are widely spread, while a low standard deviation indicates that the values are close to the mean.
5. 68% Confidence Interval: A confidence interval indicates the range within which a certain percentage of values of a dataset lies. The 68% confidence interval corresponds to a range of plus/minus one standard deviation around the mean. It indicates that about 68% of the data points lie within this range, providing insight into the distribution of values.
Overview
This Pine Script™, written in Pine version 5, is designed to analyze the Relative Strength Index (RSI) of a stock or other trading instrument and create statistical summaries of the distribution of RSI values. The script identifies outliers in price movement liquidity and uses this information to calculate the frequency of RSI values. At the end, it displays a statistical summary in the form of a table.
Structure and Functionality of the Script
1. Input Parameters
- `rsi_len`: An integer input parameter that defines the length of the RSI (default: 14).
- `outlierThreshold`: An integer input parameter that defines the length of the outlier threshold (default: 10).
2. Calculating Price Movement Liquidity
- `priceMovementLiquidity`: The volume is divided by the absolute difference between the close and open prices to calculate the liquidity of the price movement.
3. Determining the Boundary for Liquidity and Identifying Outliers
- `liquidityBoundary`: The boundary is calculated using the Exponential Moving Average (EMA) of the price movement liquidity and its standard deviation.
- `outlier`: A boolean value that indicates whether the price movement liquidity exceeds the set boundary.
4. Calculating the RSI
- `rsi`: The RSI is calculated with a period length of 14, using various moving averages (e.g., SMA, EMA) depending on the settings.
5. Storing and Limiting RSI Values
- An array `rsiFrequency` stores the frequency of RSI values from 0 to 100.
- The function `f_limit_rsi` limits the RSI values between 0 and 100.
6. Updating RSI Frequency on Outlier Occurrence
- On an outlier occurrence, the limited and rounded RSI value is updated in the `rsiFrequency` array.
7. Statistical Summary
- Various variables (`mostFrequentRsi`, `leastFrequentRsi`, `maxCount`, `minCount`, `sum`, `sumSq`, `count`, `upper_interval`, `lower_interval`) are initialized to perform statistical analysis.
- At the last bar (`bar_index == last_bar_index`), a loop is run to determine the most and least frequent RSI values and their frequencies. Sum and sum of squares of RSI values are also updated for calculating mean and standard deviation.
- The mean (`mean`) and standard deviation (`stddev`) are calculated. Additionally, a 68% confidence interval is determined.
8. Creating a Table for Result Display
- A table `resultsTable` is created and filled with the results of the statistical analysis. The table includes the most and least frequent RSI values, the standard deviation, and the 68% confidence interval.
9. Graphical Representation
- The script draws horizontal lines and fills to indicate overbought and oversold regions of the RSI.
Interpretation of the Results
The script provides a detailed analysis of RSI values based on specific liquidity outliers. By calculating the most and least frequent RSI values, standard deviation, and confidence interval, it offers a comprehensive statistical summary that can help traders identify patterns and anomalies in the RSI. This can be particularly useful for identifying overbought or oversold conditions of a trading instrument and making informed trading decisions.
Critical Evaluation
1. Robustness of Outlier Identification: The method of identifying outliers is solely based on the liquidity of price movement. It would be interesting to examine whether other methods or additional criteria for outlier identification would lead to similar or improved results.
2. Flexibility of RSI Settings: The ability to select various moving averages and period lengths for the RSI enhances the adaptability of the script, allowing users to tailor it to their specific trading strategies.
3. Visualization of Results: While the tabular representation is useful, additional graphical visualizations, such as histograms of RSI distribution, could further facilitate the interpretation of the results.
In conclusion, this script provides a solid foundation for analyzing RSI values by considering liquidity outliers and enables detailed statistical evaluation that can be beneficial for various trading strategies.
Fractal Consolidations [Pro+]Introduction:
Fractal Consolidations Pro+ pushes the boundaries of Algorithmic Price Delivery Analysis. Tailored for traders seeking precision and efficiency to unlock hidden insights, this tool empowers you to dissect market Consolidations on your terms, live, in all asset classes.
What is a Fractal Consolidation?
Consolidations occur when price is trading in a range. Normally, Consolidation scripts use a static number of "lookback candles", checking whether price is continuously trading inside the highest and lowest price points of said Time window.
After years spent studying price action and numerous programming attempts, this tool succeeds in veering away from the lookback candle approach. This Consolidation script harnesses the delivery mechanisms and Time principles of the Interbank Price Delivery Algorithm (IPDA) to define Fractal Consolidations – solely based on a Timeframe Input used for context.
Description:
This concept was engineered around price delivery principles taught by the Inner Circle Trader (ICT). As per ICT, it's integral for an Analyst to understand the four phases of price delivery: Consolidation , Expansion , Retracement , and Reversal .
According to ICT, any market movement originates from a Consolidation, followed by an Expansion .
When Consolidation ranges begin to break and resting liquidity is available, cleaner Expansions will take place. This tool's value is to visually aid Analysts and save Time in finding Consolidations in live market conditions, to take advantage of Expansion moves.
CME_MINI:ES1! 15-Minute Consolidation setting up an Expansion move, on the 10 Minute Chart:
Fractal Consolidations Pro+ doesn't only assist in confirming Higher Timeframe trend continuations and exposing opportunities on Lower Timeframes. It's also designed for both advanced traders and new traders to save Time and energy in navigating choppy or rangebound environments.
CME_MINI:ES1! 30 Minute Consolidation forming Live, on the 5 Minute Chart:
By analyzing past price action, traders will find algorithmic signatures when Consolidations are taking place, therefore providing a clearer view of where and when price is likely to contract, continue consolidating, breakout, retrace, or reverse. A prominent signature to consider when using this script is ICT's Market Maker Buy/Sell Models. These signatures revolve around the engineering of Consolidations to manipulate price in a specific direction, to then reverse at the appropriate Time. Each stage of the Market Maker Model can be identified and taken advantage of using Fractal Consolidations.
CME_MINI:NQ1! shift of the Delivery Curve from a Sell Program to a Buy Program, Market Maker Buy Model
Key Features:
Tailored Timeframes: choose the Timeframe that suits your model. Whether you're a short-term enthusiast eyeing 1 Hour Consolidations or a long-term trend follower analyzing 4 Hour Consolidations, this tool gives you the freedom to choose.
FOREXCOM:EURUSD Fractal Consolidations on a 15 Minute Chart:
Auto-Timeframe Convenience: for those who prefer a more dynamic and adaptive approach, our Auto Timeframe feature effortlessly adjusts to the most relevant Timeframe, ensuring you stay on top of market consolidations without manually adjusting settings.
Consolidation Types: define consolidations as contractions of price based on either its wick range or its body range.
COMEX:GC1! 4 Hour Consolidation differences between Wick-based and Body-based on a 1 Hour Chart:
Filtering Methods: combine previous overlapping Consolidations, merging them into one uniform Consolidation. This feature is subject to repainting only while a larger Consolidation is forming , as smaller Consolidations are confirmed. However once established, the larger Consolidation will not repaint .
FOREXCOM:GBPUSD 15 Minute Consolidation Differences between Filter Consolidations ON and OFF:
IPDA Data Range Filtering: this feature gives the Analyst control for selective visibility of Consolidations in the IPDA Data Range Lookback . The Analyst can choose between 20, 40, and 60 days as per ICT teachings, or manually adjust through Override.
INDEX:BTCUSD IPDA40 Data Range vs. IPDA20 Data Range:
Extreme Float: this feature provides reference points when the price is outside the highest or lowest liquidity levels in the chosen IPDA Data Range Lookback. These Open Float Extremes offer critical insights when the market extends beyond the Lookback Consolidation Liquidity Levels . This feature helps identify liquidity extremes of interest that IPDA will consider, which is crucial for traders in understanding market movements beyond the IPDA Data Ranges.
INDEX:ETHUSD Extreme Float vs. Non-Extreme Float Liquidity:
IPDA Override: the Analyst can manually override the default settings of the IPDA Data Range Lookback, enabling more flexible and customized analysis of market data. This is particularly useful for focusing on recent price actions in Lower Timeframes (like viewing the last 3 days on a 1-minute timeframe) or for incorporating a broader data range in Higher Timeframes (like using 365 days to analyze Weekly Consolidations on a daily timeframe).
Liquidity Insight: gain a deeper understanding of market liquidity through customizable High Resistance Liquidity Run (HRLR) and Low Resistance Liquidity Run (LRLR) Consolidation colors. This feature helps distinguishing between HRLR (high resistance, delayed price movement) and LRLR (low resistance, smooth price movement) Consolidations, aiding in quick assessment of market liquidity types.
TVC:DXY Low Resistance vs. High Resistance Consolidation Liquidity Behaviour and Narrative:
Liquidity Raid Type: decide whether to categorize a Consolidation liquidity raid by a wick or body trading through a level.
CBOT:ZB1! Wick vs. Body Liquidity Raid Type:
Customizable User Interface: tailor the visual representation to align with your preferences. Personalize your trading experience by adjusting the colors of consolidation liquidity (highs and lows) and equilibrium, as well as line styles.
付費腳本
Titan VSA + SMC Prime (Professional Institutional System)Titan VSA + SMC Prime is a comprehensive, hybrid trading system designed to bridge the gap between Volume Spread Analysis (VSA) and Smart Money Concepts (SMC) By Sultan of Multan. This script is built for traders who want to identify institutional activity, spot liquidity traps, and trade in harmony with the "Smart Money."
Unlike standard indicators that repaint or lag, Titan Prime focuses on price action, structural shifts, and volume anomalies to generate high-probability setups.
🔥 Key Features
1. Smart Money Concepts (SMC) Suite
Market Structure: Automatically maps BOS (Break of Structure) and CHoCH (Change of Character) with real-time trend identification (Bullish/Bearish).
Institutional Zones: clearly plots Order Blocks (OB), Breaker Blocks (BB), Fair Value Gaps (FVG), and Supply/Demand Zones.
Mitigation Tracking: Zones are automatically marked as "Mitigated" or removed once price has tested them, keeping your chart clean.
Premium & Discount Zones: Automatically draws the Equilibrium (EQ) to help you sell in Premium and buy in Discount areas.
2. Advanced Liquidity & Traps
Liquidity Sweeps (⚔): Identifies when key Highs or Lows are swept to grab liquidity.
Inducement (IDM 🪤): Highlights short-term highs/lows that act as "traps" for retail traders before the real move occurs. This helps you avoid false breakouts.
3. Volume Spread Analysis (VSA) Engine
Volume Bar Coloring: Candles are color-coded based on volume intensity:
🟨 Yellow: Ultra High Volume (Institutional Activity).
⬜ Gray: Low Volume (Lack of interest).
VSA Signals: Automatically detects powerful VSA patterns including:
No Demand (ND) / No Supply (NS)
Stopping Volume & Climaxes (SC/BC)
UpThrusts (UT) & Springs
Effort to Rise / Fall
Absorption
4. The "Smart Entry" System
This is the core of the indicator. It does not spam signals. It waits for a specific institutional sequence:
Liquidity Sweep: Price grabs liquidity.
Displacement: Price reverses aggressively.
Retest: The system waits for a pullback to the Order Block or FVG.
Confirmation: Only then does it display a "RETEST COMPLETE ✅ - SMART ENTRY" label with suggested TP/SL levels.
5. Professional Dashboards
Trade Status Panel (Top-Right): Monitors active signals, Entry, Stop Loss, Take Profit, and VSA Trend Score.
SMC Status Panel (Bottom-Right): A live scanner showing the status of Supply/Demand, FVGs, Structure, and overall Market Bias at a glance.
How to Use
Identify Trend: Use the dashboard to check if the market structure is Bullish or Bearish.
Wait for Traps: Look for IDM or Liquidity Sweep (⚔) labels. Smart moves usually happen after these traps.
Entry Confirmation: Do not enter blindly. Wait for the "RETEST COMPLETE" label which confirms that price has respected a Smart Money Zone.
Confluence: The best trades occur when an SMC Zone aligns with a VSA Signal (e.g., A Buying Climax inside a Demand Zone).
Customization
Visual Control: Fully adjustable text sizes, colors, and box lengths to fit your charting style.
Zoom Stability: Labels and text are pinned to ensure they remain readable when zooming in or out.
Disclaimer
This tool is for educational and analytical purposes. Always manage your risk and do not rely solely on any single indicator for financial decisions.
Pressure Pivots - MPIPressure Pivots - MPI
A multi-factor reversal detection system built on a proprietary Market Pressure Index (MPI) that combines institutional order flow analysis, liquidity dynamics, and momentum exhaustion to identify high-probability pivot points with automated win rate validation.
What This System Does
This indicator solves the core challenge of reversal trading: distinguishing genuine exhaustion pivots from temporary retracements. It combines six independent detection mechanisms—divergence, liquidity sweeps, order flow imbalance, wick rejection, volume surges, and velocity exhaustion—weighted by reliability and unified through a custom pressure oscillator.
Three-Layer Architecture:
Layer 1 - Market Pressure Index (MPI): Proprietary volume-weighted pressure oscillator that measures buying vs. selling pressure using proportional intrabar allocation and dual-timeframe normalization (-1.0 to +1.0 range).
Layer 2 - Weighted Confluence Engine: Six detection factors scored hierarchically (divergence: 3.0 pts, liquidity: 2.5 pts, order flow: 2.0 pts, velocity: 1.5 pts, wick: 1.5 pts, volume: 1.0 pt). Premium signals (DIV/LIQ/OF) require 6.0+ score, standard signals (STD) require 4.0+ score.
Layer 3 - Automated Win Rate Validation: Every signal tracked forward and validated against actual pivot formation within 10-bar window. Real-time performance statistics displayed by signal type and direction.
The Market Pressure Index - Original Calculation
What MPI Measures: The balance of aggressive buying vs. aggressive selling within each bar, smoothed and normalized to create a continuous oscillator.
Calculation Methodology:
Step 1: Intrabar Pressure Decomposition
Buy Pressure = Volume × (Close - Low) / (High - Low)
Sell Pressure = Volume × (High - Close) / (High - Low)
Net Pressure = Buy Pressure - Sell Pressure
Step 2: Exponential Smoothing
Smooth Pressure = EMA(Net Pressure, 14)
Step 3: Normalization
Avg Absolute Pressure = SMA(|Net Pressure|, 28)
MPI Raw = Smooth Pressure / Avg Absolute Pressure
Step 4: Sensitivity Amplification
MPI = clamp(MPI Raw × 1.5, -1.0, +1.0)
Why This Is Different:
• vs. RSI: RSI measures price momentum without volume context. MPI integrates volume magnitude and distribution within each bar.
• vs. OBV: OBV uses binary classification (up bar = buy volume). MPI uses proportional allocation based on close position within range.
• vs. Money Flow Index: MFI uses typical price × volume. MPI uses intrabar positioning, revealing pressure balance regardless of bar-to-bar movement.
• vs. VWAP: VWAP shows average price. MPI shows directional pressure balance (who controls the bar).
MPI Interpretation:
• +0.7 to +1.0: Extreme buying pressure (strong uptrends, potential exhaustion)
• +0.3 to +0.7: Moderate buying pressure (healthy uptrends)
• -0.3 to +0.3: Neutral/balanced (ranging, consolidation)
• -0.7 to -0.3: Moderate selling pressure (healthy downtrends)
• -1.0 to -0.7: Extreme selling pressure (strong downtrends, potential exhaustion)
Critical Insight: MPI at extremes indicates pressure exhaustion risk , not automatic reversal. Reversals occur when extreme MPI coincides with confluence factors.
Six Confluence Factors - Detection Arsenal
1. Divergence Detection (Weight: 3.0 - Highest Priority)
Detects: Price making higher highs while MPI makes lower highs (bearish), or price making lower lows while MPI makes higher lows (bullish).
Why It Matters: Reveals weakening pressure behind price moves. Declining participation signals potential reversal.
Signal Type: Premium (DIV) - Historically highest win rates.
2. Liquidity Sweep Detection (Weight: 2.5)
Detects: Price penetrates recent swing high/low (triggering stops), then immediately reverses and closes back inside range.
Calculation: High breaks swing high by <0.3× ATR but closes below it (bearish), or low breaks swing low by <0.3× ATR but closes above it (bullish).
Why It Matters: Stop hunts mark institutional accumulation/distribution zones. Often pinpoints exact pivot points.
Signal Type: Premium (LIQ) - Extremely reliable with volume confirmation.
3. Order Flow Imbalance (Weight: 2.0)
Detects: Aggressive directional ordering where price consistently closes in upper/lower third of bars with elevated volume.
Calculation:
Close Position = (Close - Low) / (High - Low)
Aggressive Buy = Volume when Close Position > 0.65
Aggressive Sell = Volume when Close Position < 0.35
Imbalance = EMA(Aggressive Buy, 5) - EMA(Aggressive Sell, 5)
Strong Flow = |Imbalance| > 1.5 × Average
Why It Matters: Reveals institutional accumulation/distribution footprints before directional moves.
Signal Type: Premium (OF)
4. Wick Rejection Patterns (Weight: 1.5)
Detects: Pin bars, hammers, shooting stars where wick exceeds 60% of total bar range.
Why It Matters: Large wicks demonstrate failed attempts to push price, indicating strong opposition.
5. Volume Spike Detection (Weight: 1.0)
Detects: Volume exceeding 2× the 20-bar average.
Why It Matters: Confirms institutional participation vs. retail noise. Most effective when combined with wick rejection or liquidity sweeps.
6. Velocity Exhaustion (Weight: 1.5)
Detects: Parabolic moves (velocity >2.0× ATR over 3 bars) showing deceleration while MPI at extremes.
Calculation:
Velocity = Change(Close, 3) / ATR(14)
Exhaustion = |Velocity| > 2.0 AND MPI > |0.5| AND Velocity Slowing
Why It Matters: Extended moves are unsustainable. Momentum deceleration from extremes precedes reversals.
Signal Classification & Scoring
Weighted Confluence Scoring:
Each factor contributes points when present. Signals fire when total score exceeds thresholds:
Bearish Example:
+ At recent high (1.0)
+ Bearish divergence (3.0)
+ Wick rejection (1.5)
+ Volume spike (1.0)
+ Velocity slowing (1.5)
= 8.0 total score → BEARISH DIV SIGNAL
Bullish Example:
+ At recent low (1.0)
+ Liquidity sweep (2.5)
+ Strong buy flow (2.0)
+ Wick rejection (1.5)
= 7.0 total score → BULLISH LIQ SIGNAL
Dual Threshold System:
• Premium Signals (DIV/LIQ/OF): Require 6.0+ points. Must include divergence, liquidity sweep, or order flow. Higher win rates.
• Standard Signals (STD): Require 4.0+ points. No premium factors. More frequent, moderate win rates.
Visual Signal Color-Coding:
• Purple Triangle: DIV (Divergence signal)
• Orange Triangle: LIQ (Liquidity sweep signal)
• Aqua Triangle: OF (Order flow signal)
• Red/Green Triangle: STD (Standard signal)
• Yellow Diamond: Warning (setup forming, not confirmed)
Warning System - Early Alerts
Yellow diamond warnings fire when 2+ factors present but full confluence not met:
• At recent 10-bar high/low
• Wick rejection present
• Volume spike present
• MPI extreme or accelerating/decelerating
Critical: Warnings are NOT trade signals. They indicate potential setups forming. Wait for colored triangle confirmation.
Win Rate Validation - Transparent Performance Tracking
How It Works:
Signal Storage: Every signal recorded (bar index, price, type, direction)
Pivot Confirmation: System monitors next 10 bars for confirmed pivot formation at signal price (±2%)
Validation: If pivot forms within window → Win. If not → Loss.
Statistics: Win Rate = Validated Signals / Total Mature Signals × 100
Dashboard Displays:
• Overall win rate with visual bar
• Bearish signal win rate
• Bullish signal win rate
• Win rate by signal type (DIV/LIQ/OF/STD)
• Wins/Total for each category
Why This Matters:
After 30-50 signals, you'll know exactly which patterns work on your instrument:
Example Performance Analysis:
Overall: 58% (35/60)
Bearish: 52% | Bullish: 65%
DIV: 72% | LIQ: 68% | OF: 50% | STD: 38%
Insight: Focus on bullish DIV/LIQ signals (72%/68% win rate), avoid STD signals (38%), investigate bearish underperformance.
This transforms the indicator from signal generator to learning system.
Dynamic Microstructure Visualization
Fibonacci Retracement Levels
• Auto-detects last swing high + swing low
• Draws 11 levels: 0%, 23.6%, 38.2%, 50%, 61.8%, 78.6%, 100%, 127.2%, 161.8%, 200%, 261.8%
• Removes crossed levels automatically
• Clears on new signal (fresh structure analysis)
• Color gradient (bullish to bearish across range)
• Key levels (0.618, 0.5, 1.0) highlighted with solid lines
Support/Resistance Lines
• Resistance: 50-bar highest high (red, only shown when above price)
• Support: 50-bar lowest low (green, only shown when below price)
• Auto-removes when price crosses
Usage: Signals firing at key Fibonacci levels (38.2%, 50%, 61.8%) or major S/R zones have enhanced structural significance.
Dashboard - Real-Time Intelligence
MPI Status:
• Current pressure reading with interpretation
• Color-coded background (green/red/gray zones)
Signal Status:
• Active signal type and direction
• Confidence score with visual bar (20 blocks, color-coded)
• Scanning status when no signal active
Divergence Indicator:
• Highlights active divergence separately (highest priority factor)
Performance Stats:
• Overall win rate with 10-block visual bar
• Directional breakdown (bearish vs. bullish)
• Signal type breakdown (DIV/LIQ/OF/STD individual win rates)
• Sample size for each category
Customization:
• Position: 9 locations (Top/Middle/Bottom × Left/Center/Right)
• Size: Tiny/Small/Normal/Large
• Toggle sections independently
How to Use This System
Initial Setup (10 Minutes)
1. MPI Configuration:
• Period: 14 (balanced) | 5-10 for scalping | 21-30 for swing
• Sensitivity: 1.5 (moderate) | Increase if MPI rarely hits ±0.7 | Decrease if constantly maxed
2. Detection Thresholds:
• Wick Threshold: 0.6 (60% of bar must be wick)
• Volume Spike: 2.0× average (lower to 1.5-1.8 for stocks, raise to 2.5-3.0 for crypto)
• Velocity: 2.0 ATR (raise to 2.5-3.0 for crypto)
3. Confluence Settings:
• Enable Divergence (highest win rate factor)
• Pivot Lookback: 5 (day trading) | 8-10 (swing trading)
• Keep default weights initially
4. Thresholds:
• Premium: 6.0 (quality over quantity)
• Standard: 4.0 (balanced)
• Warning: 2 factors minimum
Trading Workflow
When Warning Fires (Yellow Diamond):
Note warning type (bearish/bullish)
Do not enter - this is preparation only
Monitor for full signal confirmation
Prepare entry parameters
When Signal Fires (Colored Triangle):
Identify type from color (Purple=DIV, Orange=LIQ, Aqua=OF, Red/Green=STD)
Check dashboard confidence score
Verify confluence on chart (wick, volume, MPI extreme, Fib level)
Confirm with your analysis (context, higher timeframe, news)
Enter with proper risk management
Risk Management (Not Provided by Indicator):
• Stop Loss: Beyond recent swing or 1.5-2.0× ATR
• Position Size: Risk 0.5-2% of capital per trade
• Take Profit: 2-3× ATR or next structural level
Performance Analysis (After 30-50 Signals)
Review Dashboard Statistics:
Overall Win Rate:
• Target >50% for profitability with 1:1.5+ RR
• <45% = system may not suit instrument
• >65% = consider tightening thresholds
Directional Analysis:
• Bullish >> Bearish = uptrend bias, avoid counter-trend shorts
• Bearish >> Bullish = downtrend bias, avoid counter-trend longs
Signal Type Ranking:
• Focus on highest win rate types (typically DIV/LIQ)
• If STD <40% = raise threshold or ignore STD signals
• If premium type <50% = investigate (may need parameter adjustment)
Optimize Settings:
• Too many weak signals → Raise thresholds (premium 7.0-8.0, standard 5.0-6.0)
• Too few signals → Lower thresholds or reduce detection strictness
• Adjust factor weights based on what appears in winning signals
What Makes This Original
1. Proprietary Market Pressure Index
Unique Methodology:
• Proportional intrabar allocation: Unlike binary volume classification (OBV), MPI uses close position within range for proportional pressure assignment
• Dual-timeframe normalization: EMA smoothing (14) + SMA normalization (28) for responsiveness with context
• Bounded oscillator with sensitivity control: -1 to +1 range enables cross-instrument comparison while sensitivity allows customization
• Active signal integration: MPI drives divergence detection, extreme requirements, exhaustion confirmation (not just display)
vs. Existing Indicators:
• MFI uses typical price × volume (different pressure measure)
• CMF accumulates over time (not bounded oscillator)
• OBV is cumulative and binary (not proportional or normalized)
2. Hierarchical Confluence Engine
Why Simple Mashups Fail: Most multi-indicator systems create decision paralysis (RSI says sell, MACD says buy).
This System's Solution:
• Six factors weighted by reliability (3.0 down to 1.0)
• Dual thresholds (premium 6.0, standard 4.0)
• Automatic signal triage by quality tier
• Color-coded visual prioritization
Orthogonal Detection: Each factor detects different failure mode:
• Divergence = momentum exhaustion
• Liquidity = institutional manipulation
• Order Flow = smart money positioning
• Wick = supply/demand rejection
• Volume = participation confirmation
• Velocity = parabolic exhaustion
Complementary, not redundant. Weighted synthesis creates unified confidence measure.
3. Self-Validating Performance System
The Problem: Most indicators never reveal actual performance. Traders never know if it works on their instrument.
This Solution:
• Forward-looking validation (signals tracked to pivot confirmation)
• Pivot-based success criteria (objective, mechanical)
• Segmented statistics (by direction and type)
• Real-time dashboard updates
Result: After 30-50 signals, you have statistically meaningful data on what actually works on your specific market. Transforms indicator into adaptive learning system.
Technical Notes
No Repainting:
• All signals use confirmed bar data (closed bars only)
• Pivot detection has inherent lookback lag (5 bars)
• Divergence lines drawn after confirmation (retroactive visualization)
• Signals fire on bar close
Forward-Looking Disclosure:
• Win rate validation looks forward 10 bars for pivot confirmation
• Creates forward bias in statistics , not signal generation
• Real-time performance may differ until validation period elapses
Lookback Limits:
• Fibonacci/S/R: Limited by limitDrawBars (default 100)
• MPI calculation: 28 bars maximum
• Signal storage: 20 per direction (configurable)
Visual Limits:
• Max lines/labels/boxes: 500 each
• Auto-clearing prevents overflow
Limitations & Disclaimers
Not a Complete Trading System:
• Does not provide stop loss, take profit, or position sizing
• Requires trader risk management and market context analysis
Reversal Bias:
• Designed specifically for reversal trading
• Not optimized for trend continuation or breakouts
Learning Period:
• Statistics meaningless until 20-30 mature signals
• Preferably 50+ for statistical confidence
Instrument Dependency:
• Best: Liquid instruments (major forex, large-caps, BTC/ETH)
• Poor: Illiquid small-caps, low-volume altcoins (order flow unreliable)
Timeframe Dependency:
• Optimal: 15m - 4H charts
• Not Recommended: <5m (noise) or >Daily (insufficient signals)
No Guarantee of Profit:
• Win rate >50% does not guarantee profitability (depends on RR, sizing, execution)
• Past performance ≠ future performance
• All trading involves risk of loss
Warning Signals:
• Warnings are NOT trade signals
• Trading warnings produces lower win rates
• For preparation only
Recommended Settings by Instrument
Forex Majors (15m-1H):
• MPI Sensitivity: 1.3-1.5 | Volume: 2.0 | Thresholds: 6.0/4.0
Crypto BTC/ETH (15m-4H):
• MPI Sensitivity: 2.0-2.5 | Volume: 2.5-3.0 | Velocity: 2.5-3.0 | Thresholds: 6.5-7.0/4.5-5.0
Large-Cap Stocks (5m-1H):
• MPI Sensitivity: 1.2-1.5 | Volume: 1.8-2.0 | Thresholds: 6.0/4.0
Index Futures ES/NQ (5m-30m):
• MPI Period: 10-14 | Sensitivity: 1.5 | Velocity: 1.8-2.0 | Thresholds: 5.5-6.0/4.0
Altcoins High Vol (1H-4H):
• MPI Period: 21 | Sensitivity: 2.0-3.0 | Volume: 3.0+ | Thresholds: 7.0-8.0/5.0 (very selective)
Alert Configuration
Built-In Alerts:
Bullish Signal (all types)
Bearish Signal (all types)
Bullish Divergence (DIV only)
Bearish Divergence (DIV only)
Setup:
• TradingView Alert → Select "Pressure Pivots - MPI"
• Choose condition
• Frequency: "Once Per Bar Close" (prevents repainting)
• Configure notifications (popup/email/SMS/webhook)
Recommended:
• Active traders: Enable all signals
• Selective traders: DIV only (highest quality)
In-Code Documentation
Every input parameter includes extensive tooltips (800+ words total) providing:
• What it controls
• How it affects calculations
• Range guidance (low/medium/high implications)
• Default justification
• Asset-specific recommendations
• Timeframe adjustments
Access: Hover over (i) icon next to any setting. Creates self-documenting learning system—no external docs required.
DskyzInvestments | Trade with insight. Trade with anticipation.
Volume Cluster Heatmap [BackQuant]Volume Cluster Heatmap
A visualization tool that maps traded volume across price levels over a chosen lookback period. It highlights where the market builds balance through heavy participation and where it moves efficiently through low-volume zones. By combining a heatmap, volume profile, and high/low volume node detection, this indicator reveals structural areas of support, resistance, and liquidity that drive price behavior.
What Are Volume Clusters?
A volume cluster is a horizontal aggregation of traded volume at specific price levels, showing where market participants concentrated their buying and selling.
High Volume Nodes (HVN) : Price levels with significant trading activity; often act as support or resistance.
Low Volume Nodes (LVN) : Price levels with little trading activity; price moves quickly through these areas, reflecting low liquidity.
Volume clusters help identify key structural zones, reveal potential reversals, and gauge market efficiency by highlighting where the market is balanced versus areas of thin liquidity.
By creating heatmaps, profiles, and highlighting high and low volume nodes (HVNs and LVNs), it allows traders to see where the market builds balance and where it moves efficiently through thin liquidity zones.
Example: Bitcoin breaking away from the high-volume zone near 118k and moving cleanly through the low-volume pocket around 113k–115k, illustrating how markets seek efficiency:
Core Features
Visual Analysis Components:
Heatmap Display : Displays volume intensity as colored boxes, lines, or a combination for a dynamic view of market participation.
Volume Profile Overlay : Shows cumulative volume per price level along the right-hand side of the chart.
HVN & LVN Labels : Marks high and low volume nodes with color-coded lines and labels.
Customizable Colors & Transparency : Adjust high and low volume colors and minimum transparency for clear differentiation.
Session Reset & Timeframe Control : Dynamically resets clusters at the start of new sessions or chosen timeframes (intraday, daily, weekly).
Alerts
HVN / LVN Alerts : Notify when price reaches a significant high or low volume node.
High Volume Zone Alerts : Trigger when price enters the top X% of cumulative volume, signaling key areas of market interest.
How It Works
Each bar’s volume is distributed proportionally across the horizontal price levels it touches. Over the lookback period, this builds a cumulative volume profile, identifying price levels with the most and least trading activity. The highest cumulative volume levels become HVNs, while the lowest are LVNs. A side volume profile shows aggregated volume per level, and a heatmap overlay visually reinforces market structure.
Applications for Traders
Identify strong support and resistance at HVNs.
Detect areas of low liquidity where price may move quickly (LVNs).
Determine market balance zones where price may consolidate.
Filter noise: because volume clusters aggregate activity into levels, minor fluctuations and irrelevant micro-moves are removed, simplifying analysis and improving strategy development.
Combine with other indicators such as VWAP, Supertrend, or CVD for higher-probability entries and exits.
Use volume clusters to anticipate price reactions to breaking points in thin liquidity zones.
Advanced Display Options
Heatmap Styles : Boxes, lines, or both. Boxes provide a traditional heatmap, lines are better for high granularity data.
Line Mode Example : Simplified line visualization for easier reading at high level counts:
Profile Width & Offset : Adjust spacing and placement of the volume profile for clarity alongside price.
Transparency Control : Lower transparency for more opaque visualization of high-volume zones.
Best Practices for Usage
Reduce the number of levels when using line mode to avoid clutter.
Use HVN and LVN markers in conjunction with volume profiles to plan entries and exits.
Apply session resets to monitor intraday vs. multi-day volume accumulation.
Combine with other technical indicators to confirm high-probability trading signals.
Watch price interactions with LVNs for potential rapid movements and with HVNs for possible support/resistance or reversals.
Technical Notes
Each bar contributes volume proportionally to the price levels it spans, creating a dynamic and accurate representation of traded interest.
Volume profiles are scaled and offset for visual clarity alongside live price.
Alerts are fully integrated for HVN/LVN interaction and high-volume zone entries.
Optimized to handle large lookback windows and numerous price levels efficiently without performance degradation.
This indicator is ideal for understanding market structure, detecting key liquidity areas, and filtering out noise to model price more accurately in high-frequency or algorithmic strategies.
Opening Range Gaps [TakingProphets]What is an Opening Range Gap (ORG)?
In ICT, the Opening Range Gap is defined as the price difference between the previous session’s close (e.g., 4:00 PM EST in U.S. indices) and the current day’s open (9:30 AM EST).
That gap is a liquidity void—an area where no trading occurred during regular hours.
Why ICT Traders Care About ORG
Liquidity Void (Gap Fill Logic)
-Because the gap is an untraded area, it naturally acts as a draw on liquidity.
-Price often seeks to rebalance by retracing into or fully filling this void.
Premium/Discount Sensitivity
-Once the ORG is defined, ICT treats it as a mini dealing range.
-Above EQ (Consequent Encroachment) = algorithmic premium (sell-sensitive).
-Below EQ = algorithmic discount (buy-sensitive).
-Price reaction at these levels gives a precise read on institutional intent intraday.
Support/Resistance from ORG
-If the session opens above prior close, the gap often acts as support until violated.
-If the session opens below prior close, the gap often acts as resistance until reclaimed.
Key ICT Concepts Anchored to ORG
Consequent Encroachment (CE): The midpoint of the gap. The algo is highly sensitive to CE as a decision point: reject → continuation; reclaim → reversal.
Draw on Liquidity (DoL): Price is algorithmically “pulled” toward gap fills, CE, or the opposite side of the ORG.
Order Flow Confirmation: If price ignores the gap and runs away from it, this signals strong institutional order flow in that direction.
Confluence with Other Tools: FVGs, OBs, and HTF PD arrays often overlap with ORG levels, strengthening setups.
Practical Application for Traders
Bias Formation:
Use ORG EQ as a line in the sand for intraday bias.
If price trades below ORG EQ after the open → look for short setups into the prior day’s low or external liquidity.
If price trades above ORG EQ → favor longs into highs/liquidity pools.
Execution Framework:
Wait for liquidity raids or market structure shifts at ORG edges (.00, .25, .50, .75).
Target: EQ, opposite quarter, or full gap fill.
Precision Reads:
ORG lines let traders anticipate where algorithms are likely to respond, providing mechanical invalidation and clear targets without clutter.
Rapid HTF Price Action DashboardRapid HTF Price Action Dashboard V2.0
Overview
Stop the constant switching between timeframes. The Rapid HTF Price Action Dashboard is an all-in-one analysis suite designed to give you a crystal-clear view of the market's true intent by projecting critical higher-timeframe (HTF) data directly onto your trading chart.
This tool is more than just a pattern indicator; it's a complete dashboard that provides institutional-grade insights into price action. It helps you anticipate market moves by showing you where liquidity lies and how the bigger players are positioning themselves, all from the comfort of your lower-timeframe chart.
Key Features
Multi-Timeframe Dashboard: A clean, intuitive panel on the right of your chart displays the last two closed higher-timeframe candles (Candle A & B) and the live, developing one (Candle C).
Projected HTF Levels: Automatically draws and projects the previous HTF candle's high and low across your chart, acting as critical dynamic support and resistance levels.
Advanced Pattern Recognition: Identifies seven high-conviction candlestick patterns based on our proprietary filtering system, designed to eliminate noise and pinpoint only the most potent signals.
The Logic: Why Our Signals Are More Accurate
This indicator goes far beyond textbook definitions. We don't just look for shapes; we look for the story behind the price action. Each pattern is filtered through a rigorous set of conditions to ensure it represents true market conviction.
Hammers & Inverted Hammers: The Liquidity Grab
Classic Hammer/IH patterns are often misleading. Ours are different. We identify them as true liquidity grab signals, a core concept used in ICT (Inner Circle Trader) methodologies.
A Hammer (H) is only valid if its low wick has pierced below the low of the previous candle (low < low ). This signifies a "stop hunt" where liquidity was absorbed below a key level before buyers aggressively pushed the price up.
An Inverted Hammer (IH) is only valid if its high wick has pierced above the high of the previous candle (high > high ). This shows liquidity was taken above a prior high before sellers took control and suppressed the price.
Harami: Filtering for Conviction
A classic Harami (an inside bar) can often just be a weak doji, signaling indecision. We filter this noise out.
Our Harami signal (BeH, BuH) requires the inside candle to have a meaningful body (defaulting to 30% of its own range, but fully customizable).
Furthermore, we have enhanced the logic to ensure the body of the inside candle is strictly contained within the body of the previous candle, making it a more precise and reliable signal of consolidation before a potential expansion.
Power Engulfing: A Signal of Overwhelming Force
We don't flag just any engulfing candle. We look for true displacement and momentum.
Our Power Engulfing pattern (BE, BuE) requires the body of the current candle to completely engulf the body of the previous candle.
Crucially, it must also close decisively beyond the entire range (including the wick) of the previous candle. A Bullish Engulfing must close above the previous high, and a Bearish Engulfing must close below the previous low. This confirms overwhelming force has entered the market and a reversal is highly probable.
How to Use the Dashboard
Set Your Reference Timeframe (refTF): Choose the higher timeframe you want to analyze (e.g., "240" for 4-Hour).
Identify the Narrative: Use the projected High/Low lines as your key support and resistance zones. A primary strategy is to wait for price to interact with these levels.
Anticipate the Draw on Liquidity: Watch as price approaches the previous HTF high or low. The dashboard helps you predict the market's next move. For example, if price is trading below the previous HTF low, you can anticipate a potential sweep of that level.
Confirm with a Signal: When a signal like a Hammer (H) appears on the dashboard after sweeping the previous low, it provides high-conviction confirmation that liquidity has been taken and price is ready to reverse.
Ultra VolumeVisualizes volume intensity using dynamic color gradients and percentile thresholds. Includes optional SMA, bar coloring, and adaptive liquidity boxes to highlight high- and low-volume zones in real time.
Introduction
The Ultra Volume indicator enhances volume analysis by categorizing volume bars into percentile-based intensity levels. It uses color-coded gradients to quickly identify periods of unusually high or low activity. The script also includes an optional simple moving average (SMA), bar coloring, and visual box overlays to highlight zones of significant liquidity shifts.
Detailed Description
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Volume Classification
Volume is segmented into five tiers: Extra High, High, Medium, Normal, and Low, using percentile ranks calculated over a dynamically adjusted historical window. This segmentation adapts based on the chart's timeframe – using 100 bars for daily and 1440/minutes for intraday – allowing for consistent behavior across resolutions.
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Color Gradients
Each volume bar is colored based on its percentile category, smoothly transitioning between thresholds for visual clarity. This makes it easy to spot volume spikes or droughts relative to recent history.
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Simple Moving Average (SMA)
An optional SMA can be plotted on top of the volume bars for trend comparison and baseline reference. Its length and color are fully customizable.
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Bar Coloring
You can optionally color the chart's candlesticks to reflect the same volume intensity as the histogram bars, reinforcing visual cues across the chart.
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Liquidity Boxes
Two adaptive box systems highlight zones of increased or decreased liquidity:
High Liquidity Boxes expand upward when price exceeds the previous box’s top.
Low Liquidity Boxes expand downward when price breaks the previous box’s bottom.
These boxes persist and auto-adjust over time unless reset, helping traders spot key zones of volume-driven price action.
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Box Indexing
A configurable index shift determines how far back in the chart the boxes originate. Setting this to 501 makes them "stick" to the candle where they were first created.
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Data Handling
A safety check ensures the script throws an error if volume data is unavailable (e.g., for some crypto or CFD symbols).
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Summary
Ultra Volume is a practical tool for traders who want more than just raw volume bars. With intelligent percentile-based classification, real-time adaptive liquidity zones, and fully customizable visual elements, it turns volume into a highly readable, actionable signal.
CandelaCharts - Fractal Range Model📝 Overview
The Fractal Range Model (FRM) is an all-encompassing and sophisticated trading framework that incorporates multiple market dynamics to provide a deeper understanding of price movements.
This model is built around several key principles, including Market Swing Points, Sweeps, Candle Mean, and Change in State of Delivery (CISD), which together offer a nuanced and effective approach to trading.
At its core, the model focuses on Market Swing Points, which represent crucial turning points in the market where price action shifts direction.
These points provide insight into potential reversals and momentum changes, allowing traders to identify key support and resistance areas.
Recognizing these swings is critical in anticipating future price movements and understanding the market’s underlying structure.
The Fractal Range Model (FRM) is a versatile trading strategy that adapts to various styles, whether you're into scalping, day trading, swing trading, or long-term investment. Its flexibility makes it suitable for traders with different time horizons and risk preferences, allowing it to be effectively applied across multiple market conditions.
📦 Features
Timeframe Alignment: This indicator reveals lower Timeframe movements within higher Timeframe candles, offering insights into micro trends, structure shifts, and key entry points.
Bias Selection: This feature lets analysts control bias and setup detection, viewing bullish, bearish, or neutral formations to align with higher Timeframe trends.
Double Purge Sweeps: A double purge is a type of Sweep where the price exceeds both the high and low of the previous candle (via wicks) and then closes within the range of the prior candle.
Time Filters: Sync Time and price by selecting custom Time windows to focus on relevant formations.
Higher Timeframe Candles: The Fractal Range Model integrates ICT Power of Three, helping traders spot key turning points and market transitions across Timeframes.
Higher Timeframe PD Arrays: The HTF PD Arrays (FVG, IFVG) are key points of interest that indicate significant market levels where valid sweeps are likely to occur.
Lower Timeframe PD Arrays: The LTF PD Arrays (FVG, IFVG), on the other hand, are used for identifying entry points.
Smart Money Technique: In the context of the Fractal Range Model (FRM), the SMT (Smart Money Technique) serves as a crucial confluence indicator that strengthens the reliability of a formed model.
Info Panel: Display a customizable table with key details like timeframe pairing, time to next candle close, bias, and time filter settings, with full control over size, location, and borders.
Suitable for any Market: Ideal for all markets - stocks, forex, crypto, futures, commodities and more - delivering consistent results and insights across diverse trading environments.
⚙️ Settings
Core
Status: Filter models based on status
Bias: Controls what model type will be displayed, bullish or bearish
Fractal: Controls the timeframe pairing will be used
Mean: Plots the equilibrium of the previous HTF candle
Liquidity: Displays the liquidity levels that belongs to the model
Sweep: Shows the sweep that forms a model
I-sweep: Controls the visibility of invalidated sweeps
D-purge: Plots the double purge sweeps
CISD: Displays the Change In State of Delivery for a model
Labels: Adjust the HTF candle label size
C-area: Highlights the region between current candle open and previous candle equilibrium
History
History: Controls the mount of past models displayed on the chart
Filters
Asia: Filter models based on Asia Killzone hours
London: Filter models based on London Killzone hours
NY AM: Filter models based on NY AM Killzone hours
NY Launch: Filter models based on NY Launch Killzone hours
NY PM: Filter models based on NY PM Killzone hours
Custom: Filter models based on user Custom hours
HTF
Candles: Controls the number of HTF candles that will be visible on the chart
Open: Highlights with a line the open price of current HTF candle
Show True Day Open: Display True Day Open line
Offset: Controls the distance of HTF from the current chart
Space: Controls the space between HTF candles
Size: Controls the size of HTF candles
PD Array: Displays ICT PD Arrays
CE Line: Style the equilibrium line of PD Array
Border: Style the border of PD Array
LTF
H/L Line: Displays on the LTF chart High and Low of each HTF candle
O/C Line: Displays on the LTF chart Open and Close of each HTF candle
PD Array: Displays ICT PD Arrays
CE Line: Style the equilibrium line of PD Array
Border: Style the border of PD Array
Projections
StDev: Controls standard deviation available levels
Labels: Controls the size of standard deviation levels
Anchor: Controls the anchor point of standard deviation levels (wick, body)
Lines: Controls the line widths and color of standard deviation levels
SMT
Show: Display SMT
Symbol: Symbol 1
Symbol: Symbol 2
Style: Controls the color of Bearish and Bullish SMTs
Dashboard
Panel: Display information about current model
💡 Framework
The model includes the following timeframe parings:
15s - 5m
1m - 15m
1m - 30m
2m - 20m
3m - 30m
3m - 60m
5m - 1H
15m - 4H
15m - 8H
30m - 9H
30m - 12H
1H - 1D
2H - 2D
3H - 3D
4H - 1W
8H - 2W
12H - 3W
1D - 1M
2D - 2M
1W - 3M
2W - 6M
3W - 9M
1M - 12M
The Fractal Range Model follows a specific lifecycle, which highlights the current state of the model and determines whether a trade opportunity is valid.
The model's lifecycle includes the following statuses:
Formation (grey)
Invalidation (red)
Success (green)
1. Formation
The Formation phase marks the initial setup of the Fractal Range Model. During this stage, the model identifies and plots key components, such as:
Sweeps: Market movements that indicate a potential reversal or strong shift in trend.
CISD (Change In State of Delivery): A structural change that provides insight into trend shifts.
Once these components are detected, the model automatically calculates and displays Projections and Liquidity Levels , offering insights into potential price action movements.
At this stage, the model also identifies and displays the following key elements:
HTF PD Arrays (Higher-Timeframe Price Delivery Arrays)
LTF PD Arrays (Lower-Timeframe Price Delivery Arrays)
Smart Money Technique (SMT)
If any of these elements are present, they will be automatically displayed on the chart.
2. Invalidation
A Fractal Range Model is considered invalidated when the price does not reach the 2 Standard Deviation level or the first identified liquidity level, and when the price breaks above the high that formed the Sweep.
Invalidation signals that the original setup is no longer reliable, and traders should avoid taking action based on the model's original parameters.
Key invalidation conditions:
Price fails to reach the 2 Standard Deviation level.
Price fails to reach the first liquidity level.
Price breaks the high/low that initiated the Sweep.
A potentially invalidated model is marked with a purple color above the label, indicating the sweep is invalidated by the next candle, but not the high that formed the sweep.
3. Success
A Fractal Range Model is considered successful when the price reaches the 2 Standard Deviation level or the first identified liquidity level. This indicates that the model's predictions align with actual market movements, confirming the setup's validity and providing a potential trading signal.
At this stage, alongside Projections and Liquidity levels, you'll also notice the C-area — the region between the current candle's open and the previous candle's mean. If respected, price action will follow the model's direction.
Key success conditions:
Price reaches the 2 Standard Deviation level.
Price reaches the first liquidity level.
By leveraging these phases, Formation, Invalidation, and Success, traders can effectively manage their positions, minimize risk, and capitalize on high-probability setups based on the Fractal Range Model.
⚡️ Showcase
Introducing Fractal Range Model is a powerful trading tool designed to elevate your market analysis and boost your trading success. Built with precision and advanced algorithms, this indicator helps you identify key trends, potential entry and exit points, and optimize your strategy for better decision-making.
History
HTF Candles
HTF PD Arrays
LTF PD Arrays
SMT
Unlock your full trading potential and experience the difference with Fractal Range Model — your ultimate tool for smarter, more informed trading decisions.
🚨 Alerts
This script offers alert options for all model types. The alerts need to be setup manually from Tradingview.
Bearish Model
A bearish model alert is triggered when a model forms, signaling a high sweep and CISD.
Bullish Model
A bullish model alert is triggered when a model forms, signaling a low sweep and CISD.
⚠️ Disclaimer
These tools are exclusively available on the TradingView platform.
Our charting tools are intended solely for informational and educational purposes and should not be regarded as financial, investment, or trading advice. They are not designed to predict market movements or offer specific recommendations. Users should be aware that past performance is not indicative of future results and should not rely on these tools for financial decisions. By using these charting tools, the purchaser agrees that the seller and creator hold no responsibility for any decisions made based on information provided by the tools. The purchaser assumes full responsibility and liability for any actions taken and their consequences, including potential financial losses or investment outcomes that may result from the use of these products.
By purchasing, the customer acknowledges and accepts that neither the seller nor the creator is liable for any undesired outcomes stemming from the development, sale, or use of these products. Additionally, the purchaser agrees to indemnify the seller from any liability. If invited through the Friends and Family Program, the purchaser understands that any provided discount code applies only to the initial purchase of Candela's subscription. The purchaser is responsible for canceling or requesting cancellation of their subscription if they choose not to continue at the full retail price. In the event the purchaser no longer wishes to use the products, they must unsubscribe from the membership service, if applicable.
We do not offer reimbursements, refunds, or chargebacks. Once these Terms are accepted at the time of purchase, no reimbursements, refunds, or chargebacks will be issued under any circumstances.
By continuing to use these charting tools, the user confirms their understanding and acceptance of these Terms as outlined in this disclaimer.
Big Whale Finder (BWF)The Big Whale Finder (BWF) indicator is a technical analysis tool designed to detect large, hidden orders in financial markets. These orders, often placed by institutional traders or "whales," are significant in size but executed in a way that minimizes their impact on the market price.
This tool uses volume-based analysis to identify these orders, focusing on the detection of unusual volume spikes occurring in price regions where the market remains stagnant or shows minimal movement. The indicator aims to help traders identify potential areas of institutional activity, providing a strategic advantage by recognizing patterns of hidden liquidity.
Core Logic and Methodology
The BWF indicator combines two key factors to identify potential "whale" activity:
Volume Analysis: The first condition evaluates the volume relative to its average over a defined period. This is done by calculating the Simple Moving Average (SMA) of the volume and comparing current volume levels against this average. When the volume is significantly higher than the historical average, it signals the presence of a potentially large order.
Volume Threshold=Current Volume>(Average Volume×Threshold Factor)
Volume Threshold=Current Volume>(Average Volume×Threshold Factor)
According to market theory, large trades or "whale" activities often require substantial volumes to be executed. Identifying these anomalies can offer insights into the behavior of institutional players who seek to execute large transactions without disturbing the market (Lo, 2004).
Price Movement Analysis: The second condition considers the price change in relation to the volume. Specifically, if high volumes are detected but the price remains relatively stable, this suggests that large orders are being executed without significantly impacting the market price.
This phenomenon often occurs in "liquidity pools" or through algorithms designed to mask the true size of the orders. The indicator uses a price change threshold to identify this stagnation, with the condition that price movement remains below a certain percentage threshold.
Price Stagnation=(∣Close−Open∣Open)
ICT Setup 03 [TradingFinder] Judas Swing NY 9:30am + CHoCH/FVG🔵 Introduction
Judas Swing is an advanced trading setup designed to identify false price movements early in the trading day. This advanced trading strategy operates on the principle that major market players, or "smart money," drive price in a certain direction during the early hours to mislead smaller traders.
This deceptive movement attracts liquidity at specific levels, allowing larger players to execute primary trades in the opposite direction, ultimately causing the price to return to its true path.
The Judas Swing setup functions within two primary time frames, tailored separately for Forex and Stock markets. In the Forex market, the setup uses the 8:15 to 8:30 AM window to identify the high and low points, followed by the 8:30 to 8:45 AM frame to execute the Judas move and identify the CISD Level break, where Order Block and Fair Value Gap (FVG) zones are subsequently detected.
In the Stock market, these time frames shift to 9:15 to 9:30 AM for identifying highs and lows and 9:30 to 9:45 AM for executing the Judas move and CISD Level break.
Concepts such as Order Block and Fair Value Gap (FVG) are crucial in this setup. An Order Block represents a chart region with a high volume of buy or sell orders placed by major financial institutions, marking significant levels where price reacts.
Fair Value Gap (FVG) refers to areas where price has moved rapidly without balance between supply and demand, highlighting zones of potential price action and future liquidity.
Bullish Setup :
Bearish Setup :
🔵 How to Use
The Judas Swing setup enables traders to pinpoint entry and exit points by utilizing Order Block and FVG concepts, helping them align with liquidity-driven moves orchestrated by smart money. This setup applies two distinct time frames for Forex and Stocks to capture early deceptive movements, offering traders optimized entry or exit moments.
🟣 Bullish Setup
In the Bullish Judas Swing setup, the first step is to identify High and Low points within the initial time frame. These levels serve as key points where price may react, forming the basis for analyzing the setup and assisting traders in anticipating future market shifts.
In the second time frame, a critical stage of the bullish setup begins. During this phase, the price may create a false break or Fake Break below the low level, a deceptive move by major players to absorb liquidity. This false move often causes smaller traders to enter positions incorrectly. After this fake-out, the price reverses upward, breaking the CISD Level, a critical point in the market structure, signaling a potential bullish trend.
Upon breaking the CISD Level and reversing upward, the indicator identifies both the Order Block and Fair Value Gap (FVG). The Order Block is an area where major players typically place large buy orders, signaling potential price support. Meanwhile, the FVG marks a region of supply-demand imbalance, signaling areas where price might react.
Ultimately, after these key zones are identified, a trader may open a buy position if the price reaches one of these critical areas—Order Block or FVG—and reacts positively. Trading at these levels enhances the chance of success due to liquidity absorption and support from smart money, marking an opportune time for entering a long position.
🟣 Bearish Setup
In the Bearish Judas Swing setup, analysis begins with marking the High and Low levels in the initial time frame. These levels serve as key zones where price could react, helping to signal possible trend reversals. Identifying these levels is essential for locating significant bearish zones and positioning traders to capitalize on downward movements.
In the second time frame, the primary bearish setup unfolds. During this stage, price may exhibit a Fake Break above the high, causing a brief move upward and misleading smaller traders into incorrect positions. After this false move, the price typically returns downward, breaking the CISD Level—a crucial bearish trend indicator.
With the CISD Level broken and a bearish trend confirmed, the indicator identifies the Order Block and Fair Value Gap (FVG). The Bearish Order Block is a region where smart money places significant sell orders, prompting a negative price reaction. The FVG denotes an area of supply-demand imbalance, signifying potential selling pressure.
When the price reaches one of these critical areas—the Bearish Order Block or FVG—and reacts downward, a trader may initiate a sell position. Entering trades at these levels, due to increased selling pressure and liquidity absorption, offers traders an advantage in profiting from price declines.
🔵 Settings
Market : The indicator allows users to choose between Forex and Stocks, automatically adjusting the time frames for the "Opening Range" and "Trading Permit" accordingly: Forex: 8:15–8:30 AM for identifying High and Low points, and 8:30–8:45 AM for capturing the Judas move and CISD Level break. Stocks: 9:15–9:30 AM for identifying High and Low points, and 9:30–9:45 AM for executing the Judas move and CISD Level break.
Refine Order Block : Enables finer adjustments to Order Block levels for more accurate price responses.
Mitigation Level OB : Allows users to set specific reaction points within an Order Block, including: Proximal: Closest level to the current price. 50% OB: Midpoint of the Order Block. Distal: Farthest level from the current price.
FVG Filter : The Judas Swing indicator includes a filter for Fair Value Gap (FVG), allowing different filtering based on FVG width: FVG Filter Type: Can be set to "Very Aggressive," "Aggressive," "Defensive," or "Very Defensive." Higher defensiveness narrows the FVG width, focusing on narrower gaps.
Mitigation Level FVG : Like the Order Block, you can set price reaction levels for FVG with options such as Proximal, 50% OB, and Distal.
CISD : The Bar Back Check option enables traders to specify the number of past candles checked for identifying the CISD Level, enhancing CISD Level accuracy on the chart.
🔵 Conclusion
The Judas Swing indicator helps traders spot reliable trading opportunities by detecting false price movements and key levels such as Order Block and FVG. With a focus on early market movements, this tool allows traders to align with major market participants, selecting entry and exit points with greater precision, thereby reducing trading risks.
Its extensive customization options enable adjustments for various market types and trading conditions, giving traders the flexibility to optimize their strategies. Based on ICT techniques and liquidity analysis, this indicator can be highly effective for those seeking precision in their entry points.
Overall, Judas Swing empowers traders to capitalize on significant market movements by leveraging price volatility. Offering precise and dependable signals, this tool presents an excellent opportunity for enhancing trading accuracy and improving performance
ICT Macros [LuxAlgo]The ICT Macros indicator aims to highlight & classify ICT Macros, which are time intervals where algorithmic trading takes place to interact with existing liquidity or to create new liquidity.
🔶 SETTINGS
🔹 Macros
Macro Time options (such as '09:50 AM 10:10'): Enable specific macro display.
Top Line , Mid Line , Bottom Line and Extending Lines options: Controls the lines for the specific macro.
🔹 Macro Classification
Length : A length to detect Market Structure Brakes and classify macro type based on detection.
Swing Area : Swing or Liquidity Area selection, highest/lowest of the wick or the candle bodies.
Accumulation , Manipulation and Expansion color options for the classified macros.
🔹 Others
Macro Texts : Controls both the size and the visibility of the macro text.
Alert Macro Times in Advance (Minutes) : This option will plot a vertical line presenting the start of the next macro time. The line will not appear all the time, but it will be there based on remaining minutes specified in the option.
Daylight Saving Time (DST) : Adjust time appropriate to Daylight Saving Time of the specific region.
🔶 USAGE
A macro is a way to automate a task or procedure which you perform on a regular basis.
In the context of ICT's teachings, a macro is a small program or set of instructions that unfolds within an algorithm, which influences price movements in the market. These macros operate at specific times and can be related to price runs from one level to another or certain market behaviors during specific time intervals. They help traders anticipate market movements and potential setups during specific time intervals.
To trade these effectively, it is important to understand the time of day when certain macros come into play, and it is strongly advised to introduce the concept of liquidity in your analysis.
Macros can be classified into three categories where the Macro classification is calculated based on the Market Structure prior to macro and the Market Structure during the macro duration:
Manipulation Macro
Manipulation macros are characterized by liquidity being swept both on the buyside and sellside.
Expansion Macro
Expansion macros are characterized by liquidity being swept only on the buyside or sellside. Prices within these macros are highly correlated with the overall trend.
Accumulation Macro
Accumulation macros are characterized by an accumulation of liquidity. Prices within these macros tend to range.
The script returns the maximum/minimum price values reached during the macro interval alongside the average between the maximum/minimum and extends them until a new macro starts. These levels can act as supports and resistances.
🔶 DETAILS
All required data for the macro detection and classification is retrieved using 1 minute data sets, this includes candles as well as pivot/swing highs and lows. This approach guarantees the visually presented objects are same (same highs/lows) on higher timeframes as well as the macro classification remain same as it is in 1 min charts.
8 Macros can be displayed by the script (4 are enabled by default):
02:33 AM 03:00 London Macro
04:03 AM 04:30 London Macro
08:50 AM 09:10 New York Macro
09:50 AM 10:10 New York Macro
10:50 AM 11:10 New York Macro
11:50 AM 12:10 New York Launch Macro
13:10 PM 13:40 New York Macro
15:15 PM 15:45 New York Macro
🔶 ALERTS
When an alert is configured, the user will have the ability to be notified in advance of the next Macro time, where the value specified in 'Alert Macro Times in Advance (Minutes)' option indicates how early to be notified.
🔶 LIMITATIONS
The script is supported on 1 min, 3 mins and 5 mins charts.
🔶 RELATED SCRIPTS
