Binary Options 1 Minute Signals [TradingFinder] 1 Min Strategy🔵 Introduction
At first sight, price movement in binary options appears random, but behind every move lies a clear logic of liquidity and market imbalance. The market is always driven by the hunt for liquidity and the continuous rebalancing that takes place around Fair Value Gaps (FVGs) and Order Blocks (OBs). These zones are where institutional activity is concentrated and where Smart Money creates the most significant reactions.
When price approaches a key liquidity zone, it often performs a Liquidity Sweep to capture orders resting around previous highs or lows. This move usually presents itself as a False Breakout. Price briefly breaks a level to trigger stop losses and collect liquidity, then quickly reverses direction. Understanding this false breakout behavior is essential for identifying high probability reversals in binary options trading.
After the liquidity sweep, price typically retraces into a Fair Value Gap or Order Block, where the market seeks balance and new orders are introduced. This interaction between liquidity, imbalance, and institutional order flow forms the core logic of every Smart Money trading model.
By focusing on Liquidity Sweeps, False Breakouts, and the structure of FVGs and OBs, traders can read the true intention behind price movements. What seems like random volatility becomes a structured cycle of liquidity collection and reaction, offering clear opportunities for precision-based binary entries.
Bullish Setup :
Bearish Setup :
🔵 How to Use
This indicator works within the Smart Money framework and focuses on the connection between Liquidity Sweep, False Breakout, Fair Value Gap (FVG) and Order Block (OB).
It is created to help traders identify the moment when the market finishes collecting liquidity and begins to show signs of reversal.
The indicator studies how price behaves around zones where liquidity is concentrated, such as previous highs and lows or areas with visible inefficiency. When a clear reaction forms and a valid candle pattern confirms the shift in direction, the indicator generates a signal that represents the activity of Smart Money.
This tool does not respond to random volatility or noise. It waits for structure, liquidity and confirmation to align together before providing an entry. As a result, every signal has a logical base related to institutional order flow rather than ordinary price fluctuations. This approach allows traders to focus only on the movements that reflect true liquidity behavior.
🟣 Long Setup
A bullish setup takes place when the market moves downward and reaches a sell-side liquidity zone located below previous swing lows. In this area, price performs a Liquidity Sweep by moving under key levels to trigger stop losses and capture liquidity from trapped sellers.
This movement usually appears as a False Breakout because the market breaks below a level for a short moment and then quickly moves back inside the range.
Around this zone, a bullish Order Block or Fair Value Gap (FVG) often exists, showing where institutional demand is active.
When the indicator detects the presence of liquidity collection together with a valid bullish confirmation candle near an OB or FVG, it creates a Call signal.
This marks the moment when Smart Money is shifting from selling pressure to accumulation, and a strong bullish move often follows. For binary entries, the best opportunity usually comes immediately after the confirmation candle closes.
The reaction tends to happen quickly because the liquidity grab has completed and new institutional buying pressure is entering the market. This type of setup often provides a clean and precise entry with a high probability of success.
🟣 Short Setup
A bearish setup happens when the market rises and enters a buy-side liquidity area above previous highs. Here, the market performs a Liquidity Sweep to trigger stop losses placed above those highs and to absorb liquidity from trapped buyers.
This pattern forms what traders recognize as a False Breakout because the price only breaks the level temporarily before reversing in the opposite direction. A bearish Order Block or Fair Value Gap (FVG) often appears around this zone, showing where institutional selling interest exists.
Once the liquidity sweep completes and a bearish confirmation candle closes, the indicator produces a Put signal that reflects the shift from buying to selling pressure by Smart Money.
This moment often leads to a fast downward reaction as the market rebalances and fills the nearby inefficiency.
The most effective entry for binary trading is right after the confirmation candle closes, when the false breakout and liquidity collection are both completed. The price usually reacts sharply as the market transitions from liquidity hunting to a new directional move. This setup represents a structured view of how liquidity drives market cycles and how Smart Money creates precise reversals through controlled imbalance and reaction.
🔵 Settings
Time Frame : Defines the timeframe used for analysis. If left blank, the indicator automatically uses the chart’s current timeframe.
Swing Period : Determines how many candles are used to identify structural turning points such as swing highs and swing lows. Higher values increase accuracy but reduce the number of signals.
Signal Type : Specifies the type of signal generated by the indicator. The option All shows every signal, Main Signal displays only the primary one, and Alternative Signal produces a secondary signal that appears one candle after the main signal for additional confirmation.
Candle Pattern : Enables candle pattern logic for reversal confirmation. When active, the indicator issues a signal only when a valid candle formation confirms the market reaction.
Candle LookBack Check : Verifies that the last few candles move in the opposite direction of the signal to be generated. This condition acts as a confirmation filter, ensuring that the signal appears only after a clear counter-move in price.
Last Candle Direction : Considers the direction of the most recent candle in the analysis. It helps determine whether the final candle moves with or against the current trend.
Last Candle Shadow Ratio : Sets the ratio between the last candle’s wick and body to refine confirmation accuracy. Higher values require longer wicks, indicating stronger rejection and a more reliable reversal pattern.
🔵 Conclusion
Trading with Smart Money logic means understanding how liquidity moves through the market.
Each Liquidity Sweep, False Breakout, Fair Value Gap (FVG) and Order Block (OB) reflects the process of collecting and redistributing orders.
This indicator captures that sequence and turns it into precise, structured signals for binary entries. When liquidity is absorbed and a candle confirmation appears, the market reveals its true direction.
At that moment, traders can act with confidence, following institutional flow instead of reacting to random price moves.
Success with this system comes from patience, confirmation, and a clear reading of liquidity behavior, the core principles behind every Smart Money reversal.
In den Scripts nach "liquidity" suchen
Turtle Soup ICT Strategy [TradingFinder] FVG + CHoCH/CSD🔵 Introduction
The ICT Turtle Soup trading setup, designed in the ICT style, operates by hunting or sweeping liquidity zones to exploit false breakouts and failed breakouts in key liquidity Zones, such as recent highs, lows, or major support and resistance levels.
This setup identifies moments when the price breaches these liquidity zones, triggering stop orders placed (Stop Hunt) by other traders, and then quickly reverses direction. These movements are often associated with liquidity sweeps that create temporary market imbalances.
The reversal is typically confirmed by one of three structural shifts : a Market Structure Shift (MSS), a Change of Character (CHoCH), or a break of the Change in State of Delivery (CISD). Each of these structural shifts provides a reliable signal to interpret market intent and align trading decisions with the expected price movement. After the structural shift, the price frequently pullback to a Fair Value Gap (FVG), offering a precise entry point for trades.
By integrating key concepts such as liquidity, liquidity sweeps, stop order activation, structural shifts (MSS, CHoCH, CISD), and price imbalances, the ICT Turtle Soup setup enables traders to identify reversal points and key entry zones with high accuracy.
This strategy is highly versatile, making it applicable across markets such as forex, stocks, cryptocurrencies, and futures. It offers traders a robust and systematic approach to understanding price movements and optimizing their trading strategies
🟣 Bullish and Bearish Setups
Bullish Setup : The price first sweeps below a Sell-Side Liquidity (SSL) zone, then reverses upward after forming an MSS or CHoCH, and finally pulls back to an FVG, creating a buying opportunity.
Bearish Setup : The price first sweeps above a Buy-Side Liquidity (BSL) zone, then reverses downward after forming an MSS or CHoCH, and finally pulls back to an FVG, creating a selling opportunity.
🔵 How to Use
To effectively utilize the ICT Turtle Soup trading setup, begin by identifying key liquidity zones, such as recent highs, lows, or support and resistance levels, in higher timeframes.
Then, monitor lower timeframes for a Liquidity Sweep and confirmation of a Market Structure Shift (MSS) or Change of Character (CHoCH).
After the structural shift, the price typically pulls back to an FVG, offering an optimal trade entry point. Below, the bullish and bearish setups are explained in detail.
🟣 Bullish Turtle Soup Setup
Identify Sell-Side Liquidity (SSL) : In a higher timeframe (e.g., 1-hour or 4-hour), identify recent price lows or support levels that serve as SSL zones, typically the location of stop-loss orders for traders.
Observe a Liquidity Sweep : On a lower timeframe (e.g., 15-minute or 30-minute), the price must move below one of these liquidity zones and then reverse. This movement indicates a liquidity sweep.
Confirm Market Structure Shift : After the price reversal, look for a structural shift (MSS or CHoCH) indicated by the formation of a Higher Low (HL) and Higher High (HH).
Enter the Trade : Once the structural shift is confirmed, the price typically pulls back to an FVG. Enter a buy trade in this zone, set a stop-loss slightly below the recent low, and target Buy-Side Liquidity (BSL) in the higher timeframe for profit.
🟣 Bearish Turtle Soup Setup
Identify Buy-Side Liquidity (BSL) : In a higher timeframe, identify recent price highs or resistance levels that serve as BSL zones, typically the location of stop-loss orders for traders.
Observe a Liquidity Sweep : On a lower timeframe, the price must move above one of these liquidity zones and then reverse. This movement indicates a liquidity sweep.
Confirm Market Structure Shift : After the price reversal, look for a structural shift (MSS or CHoCH) indicated by the formation of a Lower High (LH) and Lower Low (LL).
Enter the Trade : Once the structural shift is confirmed, the price typically pulls back to an FVG. Enter a sell trade in this zone, set a stop-loss slightly above the recent high, and target Sell-Side Liquidity (SSL) in the higher timeframe for profit.
🔵 Settings
Higher TimeFrame Levels : This setting allows you to specify the higher timeframe (e.g., 1-hour, 4-hour, or daily) for identifying key liquidity zones.
Swing period : You can set the swing detection period.
Max Swing Back Method : It is in two modes "All" and "Custom". If it is in "All" mode, it will check all swings, and if it is in "Custom" mode, it will check the swings to the extent you determine.
Max Swing Back : You can set the number of swings that will go back for checking.
FVG Length : Default is 120 Bar.
MSS Length : Default is 80 Bar.
FVG Filter : This refines the number of identified FVG areas based on a specified algorithm to focus on higher quality signals and reduce noise.
Types of FVG filter s:
Very Aggressive Filter: Adds a condition where, for an upward FVG, the last candle's highest price must exceed the middle candle's highest price, and for a downward FVG, the last candle's lowest price must be lower than the middle candle's lowest price. This minimally filters out FVGs.
Aggressive Filter: Builds on the Very Aggressive mode by ensuring the middle candle is not too small, filtering out more FVGs.
Defensive Filter: Adds criteria regarding the size and structure of the middle candle, requiring it to have a substantial body and specific polarity conditions, filtering out a significant number of FVGs.
Very Defensive Filter: Further refines filtering by ensuring the first and third candles are not small-bodied doji candles, retaining only the highest quality signals.
In the indicator settings, you can customize the visibility of various elements, including MSS, FVG, and HTF Levels. Additionally, the color of each element can be adjusted to match your preferences. This feature allows traders to tailor the chart display to their specific needs, enhancing focus on the key data relevant to their strategy.
🔵 Conclusion
The ICT Turtle Soup trading setup is a powerful tool in the ICT style, enabling traders to exploit false breakouts in key liquidity zones. By combining concepts of liquidity, liquidity sweeps, market structure shifts (MSS and CHoCH), and pullbacks to FVG, this setup helps traders identify precise reversal points and execute trades with reduced risk and increased accuracy.
With applications across various markets, including forex, stocks, crypto, and futures, and its customizable indicator settings, the ICT Turtle Soup setup is ideal for both beginner and advanced traders. By accurately identifying liquidity zones in higher timeframes and confirming structure shifts in lower timeframes, this setup provides a reliable strategy for navigating volatile market conditions.
Ultimately, success with this setup requires consistent practice, precise market analysis, and proper risk management, empowering traders to make smarter decisions and achieve their trading goals.
VR1 DEMA - Liquidity IdentifierThis custom Pine Script indicator, titled "VR1 DEMA - Liquidity Identifier", is designed to help traders identify periods of significant resistance to price movement, often indicating high liquidity areas where the market may encounter difficulty moving in one direction. The indicator analyzes the relationship between volume and price range, combined with bar volume conditions, to provide enhanced signals of potential liquidity buildup.
Key Features:
Customizable EMA Lengths:
Users can define the lengths of both the fast and slow Exponential Moving Averages (EMAs), with default values of 5 for the fast EMA and 13 for the slow EMA. These EMAs are calculated from the ratio of volume to price range, smoothing the data to detect trends in liquidity.
Dynamic Fast EMA Color:
The fast EMA changes color based on its relationship to the slow EMA:
Red when the fast EMA is above the slow EMA, signaling stronger resistance or greater liquidity.
White when the fast EMA is below the slow EMA, indicating potentially weaker resistance.
Liquidity Signal with Multiplier Condition:
The background of the chart changes to white when the volume-to-price ratio exceeds 1.5 times the fast EMA. This highlights potential areas of liquidity buildup where price movement may encounter stronger resistance. The 1.5 multiplier is adjustable, allowing for sensitivity customization.
Volume Condition for Enhanced Signals:
A new condition is added that requires the actual bar volume to exceed 1.2 times the 5-period EMA of average bar volume. This ensures that the background color only changes when there is not only increased liquidity but also significantly higher trading volume. The 1.2 multiplier is user-adjustable for further refinement.
Combined Liquidity and Volume Filtering:
Both conditions (volume-to-price ratio and actual volume) must be met for the background color to change. This double-filtering helps traders spot moments of unusual market activity more accurately.
Optional Volume/Price Range Visualization:
An optional plot of the volume-to-price ratio is included, providing a visual representation of how volume interacts with price movement in real-time. This can be enabled or disabled based on user preference.
User-Friendly Customization:
The script includes inputs for adjusting the fast and slow EMA lengths, as well as the multipliers for the volume-to-price ratio and actual volume conditions. These customizable parameters allow traders to tailor the indicator to their specific market strategies.
Use Case:
This indicator is particularly useful for identifying periods of high liquidity and resistance in the market, where price movement may stall or reverse. By combining volume-to-price ratio analysis with actual volume conditions, the indicator provides more reliable signals for detecting potential breakouts, reversals, or consolidation periods. The color-coded fast EMA and background shading make it easy to spot key moments of increased market activity and liquidity.
Price based concepts / quantifytools- Overview
Price based concepts incorporates a collection of multiple price action based concepts. Main component of the script is market structure, on top of which liquidity sweeps and deviations are built on, leaving imbalances the only standalone concept included. Each concept can be enabled/disabled separately for creating a selection of indications that one deems relevant for their purposes. Price based concepts are quantified using metrics that measure their expected behavior, such as historical likelihood of supportive price action for given market structure state and volume traded at liquidity sweeps. The concepts principally work on any chart, whether that is equities, currencies, cryptocurrencies or commodities, charts with volume data or no volume data. Essentially any asset that can be considered an ordinary speculative asset. The concepts also work on any timeframe, from second charts to monthly charts. None of the indications are repainted.
Market structure
Market structure is an analysis of support/resistance levels (pivots) and their position relative to each other. Market structure is considered to be bullish on a series of higher highs/higher lows and bearish on a series of lower highs/lower lows. Market structure shifts from bullish to bearish and vice versa on a break of the most recent pivot high/low, indicating weak ability to defend a key level from the dominating side. Supportive market structure typically provides lengthier and sustained trending environment, making it an ideal point of confluence for establishing directional bias for trades.
Liquidity sweeps
Liquidity sweeps are formed when price exceeds a pivot level that served as a provable level of demand once and is expected to display demand again when revisited. A simple way to look at liquidity sweeps is re-tests of untapped support/resistance levels.
Deviations
Deviations are formed when price exceeds a reference level (market structure shift level/liquidity sweep level) and shortly closes back in, leaving participating breakout traders in an awkward position. On further adverse movement, stuck breakout traders are forced to cover their underwater positions, creating ideal conditions for a lengthier reversal.
Imbalances
Imbalances, also known as fair value gaps or single prints, depict areas of inefficient and one sided transacting. Given inclination for markets to trade efficiently, price is naturally attracted to areas that lack proper participation, making imbalances ideal targets for entries or exits.
Key takeaways
- Price based concepts consists of market structure, liquidity sweeps, deviations and imbalances.
- Market structure shifts from bullish to bearish and vice versa on a break of the most recent pivot high/low, indicating weak ability to defend a key level from the dominating side.
- Supportive market structure tends to provide lengthier and sustained movement for the dominating side, making it an ideal foundation for establishing directional bias for trades.
- Liquidity sweeps are formed when price exceeds an untapped support/resistance level that served as a provable level of demand in the past, likely to show demand again when revisited.
- Deviations are formed when price exceeds a key level and shortly closes back in, leaving breakout traders in an awkward position. Further adverse movement compels trapped participants to cover their positions, creating ideal conditions for a reversal.
- Imbalances depict areas of inefficient and one sided transacting where price is naturally attracted to, making them ideal targets for entries or exits.
- Price based concepts are quantified using metrics that measure expected behavior, such as historical likelihood of supportive structure and volume traded at liquidity sweeps.
- For practical guide with practical examples, see last section.
Accessing script 🔑
See "Author's instructions" section, found at bottom of the script page.
Disclaimer
Price based concepts are not buy/sell signals, a standalone trading strategy or financial advice. They also do not substitute knowing how to trade. Example charts and ideas shown for use cases are textbook examples under ideal conditions, not guaranteed to repeat as they are presented. Price based concepts notify when a set of conditions are in place from a purely technical standpoint. Price based concepts should be viewed as one tool providing one kind of evidence, to be used in conjunction with other means of analysis.
Price based concepts are backtested using metrics that reasonably depict their expected behaviour, such as historical likelihood of supportive price movement on each market structure state. The metrics are not intended to be elaborate and perfect, but to serve as a general barometer for feedback created by the indications. Backtesting is done first and foremost to exclude scenarios where the concepts clearly don't work or work suboptimally, in which case they can't be considered as valid evidence. Even when the metrics indicate historical reactions of good quality, price impact can and inevitably does deviate from the expected. Past results do not guarantee future performance.
- Example charts
Chart #1 : BTCUSDT
Chart #2 : EURUSD
Chart #3 : ES futures
Chart #4 : NG futures
Chart #5 : Custom timeframes
- Concepts
Market structure
Knowing when price has truly pivoted is much harder than it might seem at first. In this script, pivots are determined using a custom formula based on volatility adjusted average price, a fundamentally different approach to the widely used highest/lowest price within X amount of bars. The script calculates average price within set period and adjusts it to volatility. Using this formula, the script determines when price has turned significantly enough and aggressively enough to constitute a relevant pivot, resulting in high accuracy while ruling out subjective decision making completely. Users can adjust length of market structure basis and sensitivity of volatility adjustment to achieve desired magnitude of pivots, reflected on the average swing metrics. Note that structure pivots are backpainted. Typical confirmation time for a pivot is within 2-3 bars after peak in price.
Market structure shifts
Generally speaking, traders consider market structure to have shifted when most recent structure high/low gets taken out, flipping underlying bias from one side over to the other (e.g. from bullish structure favoring upside to bearish structure favoring downside). However, there are many ways to approach the concept and the most popular method might not always be the best one. Users can determine their own market structure shift rules by choosing source (close, high, low, ohlc4 etc.) for determining structure shift. Users can also choose additional rules for structure shift, such as two consecutive closes above/below pivot to qualify as a valid shift.
Liquidity sweeps
Users can set maximum amount of bars liquidity levels are considered relevant from the moment of confirmed pivot. By default liquidity levels are monitored for 250 bars and then discarded. Level of tolerance can be set to anything between 100 and 1000 bars. For each liquidity sweep, relative volume (volume relative to volume moving average) is stored and added to average calculations for keeping track of typical depth of liquidity found at sweeps.
Deviations
Users can set a maximum amount of bars price has to spend above/below reference level to consider a deviation to be in place. By default set to 6 bars.
Imbalances
Users can set a desired fill point for imbalances using the following options: 100%, 75%, 50%, 25%. Users can also opt for excluding insignificant imbalances to attain better relevance in indications.
- Backtesting
Built-in backtesting is based on metrics that are considered to reasonably quantify expected behaviour of the main concept, market structure. Structure feedback is monitored using two metrics, supportive structure and structure period gain. Rest of the metrics provided are informational in nature, such as average swing and average relative volume traded at liquidity sweeps. Main purpose of the metrics is to form a general barometer for monitoring whether or not the concepts can be viewed as valid evidence. When the concepts are clearly not working optimally, one should adjust expectations accordingly or take action to improve performance. To make any valid conclusions of performance, sample size should also be significant enough to eliminate randomness effectively. If sample size on any individual chart is insufficient, one should view feedback scores on multiple correlating and comparable charts to make up for the loss.
For more elaborate backtesting, price based concepts can be used in any other script that has a source input, including fully mechanic strategies utilizing Tradingview's native backtester. Each concept and their indications (e.g. higher low on a bearish structure, lower high on a bullish structure, market structure shift up, imbalance filled etc.) can be utilized separately and used as a component in a backtesting script of your choice.
Structure feedback
Structure feedback is monitored using two metrics, likelihood of supportive price movement following a market structure shift and average structure period gain. If either of the two employed tests indicate failed reactions beyond a tolerable level, one should take action to improve feedback by adjusting the settings. If feedback metrics after adjusting the settings are still insufficient, the concepts are working suboptimally for the given chart and cannot be regarded as valid technical evidence as they are.
Metric #1 : Supportive structure
Each structure pivot is benchmarked against its respective structure shift level. Feedback is considered successful if structure pivot takes place above market structure shift level (in the case of bullish structure) or below market structure shift level (in the case of bearish structure). Structure feedback constitutes as one test indicating how often a market structure state results in price movement that can be considered supportive.
Metric #2 : Structure period gain
Each structure period is expected to present favorable appreciation, measured from one market structure shift level to another. E.g. bullish structure period gain is measured from market structure shift up level to market structure shift down level that ends the bullish structure period. Bearish structure is measured in a vice versa manner, from market structure shift down level to market structure shift up level that ends the bearish structure period. Feedback is considered successful if average structure period gain is supportive for a given structure (positive for bullish structure, negative for bearish structure).
Additional metrics
On top of structure feedback metrics, percentage gain for each swing (distance between a pivot to previous pivot) is recorded and stored to average calculations. Average swing calculations shed light on typical pivot magnitude for better understanding changes made in market structure settings. Average relative volume traded at liquidity sweep on the other hand gives a clue of depth of liquidity typically found on a sweeps.
Feedback scores
When market structure (basis for most concepts) is working optimally, quality threshold for both feedback metrics are met. By default, threshold for supportive structure is set to 66%, indicating valid feedback on 2/3 of backtesting periods on average. On top, average structure period gain needs to be positive (for bullish structures) and negative (for bearish structure) to qualify as valid feedback. When both tests are passed, a tick indicating valid feedback will appear next to feedback scores, otherwise an exclamation mark indicating suboptimal performance on either or both. If both or either test fail, market structure parameters need to be optimized for better performance or one needs to adjust expectations accordingly.
Verifying backtest calculations
Backtest metrics can be toggled on via input menu, separately for bullish and bearish structure. When toggled on, both cumulative and average counters used in backtesting will appear on "Data Window" tab. Calculation states are shown at a point in time where cursor is hovered. E.g. when hovering cursor on 4th of January 2021, backtest calculations as they were during this date will be shown.
- Alerts
Available alerts are the following.
- HH/HL/LH/LL/EQL/EQH on a bullish/bearish structure
- Bullish/bearish market structure shift
- Bullish/bearish imbalance created
- Bullish/bearish imbalance filled
- Bullish/bearish liquidity sweep
- Bullish/bearish deviation
- Visuals
Each concept can be enabled/disabled separately for creating a selection indications that one deems relevant for their purposes. On top, each concept has a stealth visual option for more discreet visuals.
Unfilled imbalances and untapped liquidity levels can be extended forward to better gauge key areas of interest.
Liquidity sweeps have an intensity option, using color and width to visualize volume traded at sweep.
Market structure states and market structure shifts can be visualized as chart color.
Metric table can be offsetted horizontally or vertically from any four corners of the chart, allowing space for tables from other scripts.
Table sizes, label sizes and colors are fully customizable via input menu.
- Practical guide
The basic idea behind market structure is that a side (bulls or bears) have shown significant weakness on a failed attempt to defend a key level (most recent pivot high/low). In the same way, a side has shown significant strength on a successful attempt to break through a key level. This successful break through a key level often leads to sustained lengthier movement for the side that provably has the upper hand, making it an ideal tool for establishing directional bias.
Multi-timeframe view of market structure provides crucial guidance for analyzing market structure states on any individual timeframe. If higher timeframe market structure is bullish, it doesn't make sense to expect contradicting lower timeframe market structure to provide significant adverse movement, but rather a normal correction within a long term trend. In the same way, if lower timeframe market structure is in agreement with higher timeframe market structure, one can expect a reliable trending environment to ensue as multiple points of confluence are in place.
Bullish structure can be considered constructive on a series of higher highs and higher lows, indicating strong interest from bulls to sustain an uptrend. Vice versa is true for bearish structure, a series of lower highs and lower lows can be considered constructive. When structure does not indicate strong interest to maintain a supportive trend (lower highs on bullish structure, higher lows on bearish structure), a structure shift and a turn in trend might be nearing.
Market structure shifts are of great interest for breakout traders who position for continuation. Structure shifts can indeed be fertile ground for executing a breakout trade, but breakouts can easily turn into fakeouts that leave participants in an awkward position. When price moves further away from the underwater participants, potential for snowball effect of covering positions and driving price further away is elevated.
Liquidity sweeps as a concept is based on the premise that pivoting price is evidence of meaningful depth of liquidity found at/around pivot. If liquidity existed at a pivot once, it is likely to exist there in the future as well. When price grinds against liquidity, it is on a path of resistance rather than path of least resistance. Pivots are also attractive placements for traders to set stop-losses, which act as fuel for price to move to the opposite direction when swept and triggered.
Behind tightly formed pivots are potentially many stop-loss orders lulled in the comfort of having many layers of levels protecting their position. Compression that leaves such clusters of unswept liquidity rarely goes unvisited.
As markets strive for efficient and proper transacting most of the time, imbalances serve as points in price where price is naturally attracted to. However, imbalances too are contextual and sometimes one sided trading is rewarded with follow through, rather than with a fill. Identifying market regimes give further clue into what to expect from imbalances. In a ranging environment, one can expect imbalances to fill relatively quick, making them ideal targets for entries and exits.
On a strongly trending environment on the other hand imbalances tend to stick for a much longer time. In such environments continuation can be expected with no fills or only partial fills. Signs of demand preventing fill attempts serve as additional clues for imminent continuation.
Confluence Engine [BullByte]CONFLUENCE ENGINE
Multi-Factor Technical Analysis Framework
OVERVIEW
Confluence Engine is a multi-dimensional technical analysis framework that evaluates market conditions across five distinct analytical pillars simultaneously. Rather than relying on a single indicator or signal source, this tool synthesizes Structure, Momentum, Volume, Volatility, and Pattern analysis into a unified scoring system that identifies high-probability trading opportunities when multiple technical factors align.
The core philosophy behind this indicator stems from a fundamental observation: isolated signals frequently fail, but when multiple independent analytical methods agree, the probability of a successful trade increases substantially. This indicator was developed after extensive research into why traders often receive conflicting signals from different indicators on their charts, leading to analysis paralysis and poor decision-making.
THE PROBLEM AND SOLUTION
The Problem:
Most traders use multiple indicators independently, often receiving contradictory signals. One indicator says "buy" while another says "wait." This creates confusion and leads to missed opportunities, premature entries based on incomplete analysis, difficulty quantifying how strong a setup actually is, and inconsistent decision-making across different market conditions.
The Solution:
Confluence Engine addresses this by providing a single, unified score (0-100) that represents the aggregate strength of a trading setup. Instead of mentally weighing five different indicators, traders receive a clear numerical score indicating setup quality, visual tier classification (ULTRA, HIGH, STANDARD), specific identification of which factors are strong or weak, and actionable guidance on what to watch for next.
THE FIVE ANALYTICAL DIMENSIONS
Each dimension was selected because it measures a fundamentally different aspect of market behavior:
STRUCTURE ANALYSIS
Evaluates price position relative to key levels and recent swing points. Markets respect structure - previous highs, lows, and areas where price reversed. This dimension identifies when price interacts with these critical levels and measures the quality of that interaction.
What it detects: Price approaching or sweeping swing highs/lows, reclaim patterns after false breakouts, EMA alignment and trend structure, exhaustion after extended moves.
MOMENTUM ANALYSIS
Measures the underlying strength and direction of price movement. Strong moves are characterized by momentum preceding price. This dimension evaluates whether momentum supports the current price direction.
What it detects: Oversold/overbought conditions with reversal potential, momentum divergence states, directional movement strength (ADX-based), momentum shifts before price confirmation.
VOLUME ANALYSIS
Volume validates price movement. Significant moves require participation. This dimension measures current volume relative to recent averages to determine if market participants are genuinely committing to the move.
What it detects: Volume spikes confirming price action, below-average volume warning of weak moves, climactic volume at potential reversals, volume confirmation of rejection patterns.
VOLATILITY ANALYSIS
Markets alternate between compression (low volatility) and expansion (high volatility). This dimension identifies these phases and recognizes when compression is likely to resolve into directional movement.
What it detects: Volatility squeeze conditions (Bollinger inside Keltner), squeeze release direction, ATR expansion indicating breakout potential, compression duration for timing breakouts.
PATTERN ANALYSIS
Candlestick patterns reflect the battle between buyers and sellers within each bar. This dimension evaluates the quality and context of reversal and continuation patterns.
What it detects: Engulfing patterns with quality scoring, hammer and shooting star formations, rejection wicks indicating trapped traders, pattern confluence with other factors.
WHAT MAKES THIS INDICATOR ORIGINAL Not a mashup
This is NOT a mashup of indicators displayed together. The Confluence Engine represents an integrated analytical framework with the following unique characteristics:
Unified Scoring System: All five dimensions feed into a proprietary scoring algorithm that weights and combines their signals. The output is a single 0-100 score, not five separate readings.
Multi-Factor Gate: Beyond just scoring, the system requires a minimum number of factors to be "active" (meeting their individual thresholds) before allowing signals. This prevents signals based on one extremely strong factor masking four weak ones.
Regime-Aware Adjustments: The engine detects the current market regime (trending, ranging, volatile, weak) and automatically adjusts factor weights and score multipliers. A structure signal means something different in a trending market versus a ranging market.
Adaptive Risk Management: Take-profit and stop-loss levels are not static. They adapt based on current volatility, market regime, and signal quality - providing tighter targets in low-volatility environments and wider targets when volatility expands.
Liquidity Sweep Detection: A distinctive feature that identifies when price has swept beyond a swing high/low and then reclaimed back inside. This pattern often indicates stop hunts followed by reversals.
Signal Quality Tiers: Rather than just "signal" or "no signal," the engine classifies setups into tiers. ULTRA (80+) represents highest probability setups with all factors aligned. HIGH (70-79) represents strong setups with multiple factors confirming. STANDARD meets minimum threshold for acceptable setups.
HOW THE SCORING WORKS
Each of the five factors generates a raw score from 0-100 based on current market conditions. These raw scores are then weighted according to the selected trading style (Balanced, Scalper, Swing, Range, Trend), adjusted based on current market regime detection, modified by higher timeframe alignment (if enabled), bonused when multiple factors exceed their activation thresholds simultaneously, and multiplied by session factors (if session filter is enabled).
The result is a final Bull Score and Bear Score, each ranging from 0-100, representing the current strength of long and short setups respectively.
Signal Generation Requirements:
- Score meets minimum threshold (configurable: 60-95)
- Required number of factors are "active" (default: 3 of 5)
- Market regime is not blocked (if blocking enabled)
- Higher timeframe alignment passes (if required)
- Cooldown period from last signal has elapsed
UNDERSTANDING THE DASHBOARDS
Main Dashboard (Top Right)
The main dashboard displays real-time scores and market context:
LONG Score - Current bullish setup strength (0-100) with quality tier displayed
SHORT Score - Current bearish setup strength (0-100) with quality tier displayed
Regime - Current market state showing TREND UP, TREND DN, VOLATILE, RANGE, or WEAK
HTF - Higher timeframe alignment showing BULL, BEAR, NEUT, or OFF
Squeeze - Volatility state showing SQZ (in squeeze), REL+ (bullish release), REL- (bearish release), or NORM
Gate - Factor count versus requirement, for example 4/3 means 4 factors active with 3 required
Sweep L/S - Liquidity sweep status for long and short setups
ATR% - Current ATR as percentile of recent range indicating relative volatility
Vol - Current volume relative to 20-period average
R:R - Current risk-reward ratio based on adaptive TP/SL calculations
Trade - Active trade status and unrealized profit/loss percentage
Analysis Dashboard (Bottom Left)
The analysis dashboard provides actionable guidance:
Signal Readiness - Visual progress bars showing how close each direction is to generating a signal
Blocking Factors - Identifies which specific factor is weakest and preventing signals
Recommended Action - Context-aware guidance such as WATCH, WAIT, MANAGE, or SCAN
Watch For - Specific events to monitor for setup completion
Opportunity Level - Overall market opportunity rating from EXCELLENT to VERY POOR
Timing - Contextual timing guidance based on current conditions
Status Bar (Bottom Center)
Compact view displaying Long Score, Gate Status, Current State, Gate Status, and Short Score in a single row for quick reference.
Dashboard Size - Auto Mode Explained
When Dashboard Size is set to "Auto", the indicator intelligently adjusts text size based on your current chart timeframe to optimize readability:
Auto-Sizing Logic:
1-Minute to 5-Minute Charts → Tiny
- Lower timeframes show more bars on screen
- Tiny text prevents dashboard from obscuring price action
- Recommended for scalping and high-frequency monitoring
15-Minute Charts → Small
- Balanced size for intraday trading
- Readable without being intrusive
1-Hour to Daily Charts → Normal
- Standard size for most trading styles
- Optimal readability for swing trading
Weekly and Monthly Charts → Large
- Larger text for position trading
- Fewer bars visible so space is available
Manual Override:
You can override auto-sizing for any dashboard individually:
- Dashboard Size (All): Sets master size applied to all dashboards
- Main Dashboard Size: Override for top-right dashboard specifically
- Analysis Panel Size: Override for bottom-left panel specifically
- Status Bar Size: Override for bottom-center bar specifically
Example Use Case:
Trading on 5m chart (default = Tiny) but you have good eyesight and large monitor:
- Set "Dashboard Size (All)" to "Small" or "Normal" for better readability
- Individual dashboards will use your override instead of auto-sizing
Recommendation:
Start with Auto mode and only adjust if dashboards are too large or too small for your monitor/eyesight.
UNDERSTANDING SIGNAL LABELS
When a signal generates, a label appears with trade information:
Minimal Style Example:
LONG 85
Shows tier icon, direction, and score only.
Detailed Style Example:
ULTRA LONG
Score: 85
Entry: 50250.50
TP1: 50650.25
TP2: 51500.75
SL: 49850.25
R:R 1:2.5
Regime: TREND UP
HTF: BULL
Tier Icons Explained:
indicates ULTRA quality with score 80 or higher
indicates HIGH quality with score between 70 and 79
indicates STANDARD quality with score meeting minimum threshold
UNDERSTANDING TRADE ZONES
When a signal generates, visual elements appear on the chart:
Entry Line (Purple) marks the entry price level
TP1 Line (Blue Dashed) marks the first take-profit target
TP2 Line (Cyan Dashed) marks the final take-profit target
SL Line (Orange Dotted) marks the stop-loss level
Trade Zone Box shows shaded area from SL to TP2
These elements extend forward as price progresses. When TP1 is hit, its line becomes solid to indicate achievement. When the trade completes at either TP2 or SL, all elements are cleaned up and the entry label converts to a compact ghost label for historical reference.
Exit Labels Explained:
+X.XX% indicates first target reached with partial profit secured
+X.XX% indicates full target reached with maximum profit achieved
-X.XX% indicates stop-loss triggered
TP1 Hit, SL... indicates stopped out after TP1 was already hit (optional display)
OPPOSITE SIGNAL HANDLING
When market conditions shift dramatically, the engine may generate a signal in the opposite direction while an existing trade is active. This represents a significant change in confluence and is handled automatically:
Automatic Trade Reversal Process:
1. Detection: New signal triggers opposite to current trade direction (e.g., SHORT signal while LONG trade is active)
2. Current Trade Closure:
- All visual elements (entry line, TP/SL lines, trade zone) are deleted
- Current trade is marked as closed
3. Entry Label Conversion:
- The detailed entry label is converted to a compact ghost label
- Ghost label shows direction + score (e.g., "LONG 75")
- Marked with "OPP" outcome to indicate opposite signal closure
- Moved to a non-interfering position below/above price
4. New Trade Initialization:
- Fresh entry label created for new direction
- New TP1, TP2, SL levels calculated based on new signal quality
- Trade zone and price lines drawn for new trade
Example Scenario:
You enter a LONG trade at score 72. Price moves sideways for 8 bars, then market structure breaks down. Confluence shifts heavily bearish with a sweep reclaim bear + momentum + volume spike, generating a SHORT signal at score 81. The engine automatically:
- Closes the LONG trade
- Converts "LONG 72" entry label to a small ghost label
- Opens new SHORT trade at current price
- Displays new SHORT entry label with full trade details
Trading Implication:
This behavior ensures the engine is always aligned with the highest-probability direction based on current confluence. It prevents you from holding a position when all five factors have flipped against you.
Note: This does NOT happen for every small score change. The opposite signal must meet all signal generation requirements (minimum score, gate pass, regime check, HTF alignment) before triggering. Typically occurs during strong trend reversals or major support/resistance breaks.
EXAMPLE TRADE : LONG
Instrument and Exchange: Bitcoin / TetherUS (BTC/USDT) on Binance
Timeframe: 5-minute
Timestamp: Nov 27, 2025 12:39 UTC
Indicator Script: Confluence Engine v1.0
Trade Type: Long (Example Trade)
Setting Used: Default
Signal Details:
- Tier: HIGH
- Score: 70
- Entry Price: 90040.70
- TP1 Target: 90868.63
- TP2 Target: 92110.52
- Stop Loss: 89325.94
- Risk Reward: 1:2.9
Trade Outcome:
- TP1 hit after 12 bars (+0.95%)
- TP2 hit after 28 bars (+2.85%)
- Total gain: +2.85% on full position
EXAMPLE TRADE : SHORT with Dashboard Explanation and interpretation
Instrument and Exchange: Ethereum / U.S. Dollar (ETH/USD) — Coinbase
Timeframe: 1-hour
Timestamp (screenshot): Nov 28, 2025 16:41 UTC
Indicator Script: Confluence Engine v1.0
Trade Type: Short (Example Trade)
Setting Used: Default
Signal Details
-Tier: STANDARD (STD)
-Score: 64
-Entry Price: 3037.26
-TP1 Target: 2981.61 (-55.65 pts)
-TP2 Target: 2898.12 (-139.14 pts)
-Stop Loss: 3099.79 (+62.53 pts)
-Risk:Reward: ≈ 1 : 2.2 (TP2/SL)
-Market Context at Signal
-Regime: TREND UP (contextual regime at time of signal) — mixed environment for shorts
-HTF Alignment: OFF (no higher-timeframe confirmation)
-Gate Status: 3 / 3 (minimum factor groups active — gate passed)
-Squeeze Status: NORM (no active compression breakout)
-Volume: ~1.8× average (elevated participation)
-ATR%: 57% (elevated volatility)
Analysis Dashboard Reading (what the user sees)
-Long Readiness: Needs +36 points to qualify.
-Short Readiness: Needs +11 points to qualify (closer but not auto-entering).
-Blocking Factors: Structure = 0 — the single decisive blocker preventing fresh signals.
-Opportunity Level: VERY POOR (roughly 20 / 100) — low quality environment for adding positions.
-Timing: Wait for better setup (do not add new positions).
-Trade Outcome (screenshot moment)
-Trade state: Active SHORT (opened earlier).
-Live P&L (snapshot): +0.14% (managing trade).
-TP1/TP2: Targets shown on chart (TP1 2981.61, TP2 2898.12). Not closed yet at screenshot.
-Visuals: Entry label, TP/SL lines and trade zone are displayed and being extended while trade is active.
Interpretation
The engine produced a standard short (Score 64) while the market showed elevated volume and volatility but no HTF confirmation. Although the Gate passed (3/3), Structure = 0 blocks the indicator from issuing fresh entries — this is intentional and by design: one missing factor (structure) is enough to prevent new signals even when other factors look supportive. The currently open short is being managed (partial targets and SL visible), but the system's recommendation is to manage the existing trade only and not open new shorts until structure or HTF alignment improves.
Why this example matters (teaching point)
-Gate ≠ Go: Gate pass (factor count) alone does not force fresh trades — the system enforces additional checks (structure, regime, HTF) to avoid lower-quality setups.
-Volume & Volatility are necessary but not sufficient: High volume and wide ATR create movement but do not replace structural validation.
-Active trade vs new entries: The script will continue to manage an already open trade but will not create a new signal while a blocking factor remains. This prevents overtrading and reduces false positives.
-Practical trader actions shown by the example
-Manage existing SHORT only: Trail to breakeven if TP1 is taken; scale out at TP1; hold remaining if price respects trend and structure reclaims.
-Do not add fresh positions: Wait for Structure > 0 or a HTF alignment that lifts the block.
-Watch for signals that matter: Sweep reclaim, HTF alignment turning bullish for shorts (i.e., HTF changes to BEAR), or a squeeze release with volume spike — these can clear the blocker and validate new entries.
RECOMMENDED TIMEFRAMES
For Scalping on 1m, 5m, or 15m charts: Use higher factor thresholds and shorter cooldowns. The faster pace requires stricter filtering.
For Day Trading on 15m, 30m, or 1H charts: This provides a balance of signal frequency and reliability suitable for most active traders.
For Swing Trading on 1H, 4H, or Daily charts: Expect higher quality signals with longer hold periods and fewer false signals.
For Position Trading on Daily or Weekly charts: Focus on ULTRA signals only for maximum conviction on longer-term positions.
Higher Timeframe Alignment Recommendations:
When trading 5m, use 1H as your HTF
When trading 15m, use 1H or 4H as your HTF
When trading 1H, use 4H or Daily as your HTF
When trading 4H, use Daily as your HTF
The general rule is to select an HTF that is 4 to 12 times your trading timeframe.
TRADING STYLE PRESETS
Balanced (Default)
Equal weighting across all five factors at 20% each. Suitable for most market conditions and recommended as starting point.
Scalper
Emphasizes Volume at 30% and Volatility at 30%. Designed for quick in-and-out trades on lower timeframes where immediate momentum and volatility expansion matter most.
Swing Trader
Emphasizes Structure at 30% and Momentum at 30%. Focuses on catching larger moves where trend direction and key levels are paramount.
Range Trader
Emphasizes Structure at 35% and Pattern at 25%. Optimized for sideways markets where support/resistance levels and reversal patterns dominate.
Trend Follower
Emphasizes Momentum at 40%. Designed for trending markets where staying with the dominant direction is the priority.
QUALITY MODE SETTINGS
Custom Mode
Set your own minimum score threshold. Lower thresholds between 60 and 65 generate more signals but with lower average quality. Higher thresholds of 75 or above generate fewer but higher-quality signals.
High Quality Mode
Uses minimum score of 70. Recommended for most users as it filters out marginal setups while still providing reasonable signal frequency.
Ultra Only Mode
Uses minimum score of 80 for maximum selectivity. Only the highest-conviction setups generate signals. Recommended for swing and position traders or during uncertain market conditions.
REGIME DETECTION
The engine continuously evaluates market conditions and classifies them into five states:
TREND UP
Characteristics: Strong ADX reading with EMAs aligned in bullish order
Trading Implications: Long signals receive score boost while short signals are suppressed. Momentum factor gains additional weight.
TREND DN
Characteristics: Strong ADX reading with EMAs aligned in bearish order
Trading Implications: Short signals receive score boost while long signals are suppressed. Momentum factor gains additional weight.
VOLATILE
Characteristics: High ATR percentile, wide Bollinger Bands, elevated volume
Trading Implications: Both directions remain viable but wider stops are recommended. Volume factor gains additional weight.
RANGE
Characteristics: Low ADX reading, narrow Bollinger Bands, low ATR percentile
Trading Implications: Structure signals are emphasized while momentum signals are suppressed. Pattern recognition becomes more important.
WEAK
Characteristics: Unclear or mixed conditions that do not fit other categories
Trading Implications: Reduced confidence in all signals. Consider waiting for clearer market conditions.
Filter Mode Options:
Off - Regime is detected and displayed but no score adjustments are applied
Adjust Scores - Automatically modifies factor weights based on current regime
Block Weak Regimes - Prevents signals from generating when regime is RANGE or WEAK
VOLATILITY SQUEEZE DETECTION
A volatility squeeze occurs when Bollinger Bands contract inside the Keltner Channel, indicating reduced volatility and potential energy building for a breakout.
Squeeze States Explained:
SQZ with bar count (example: SQZ 15)
Indicates currently in squeeze for the displayed number of bars. A score penalty is applied during this phase because compression represents uncertainty about direction.
REL+ (Release Bullish)
Indicates squeeze has released with price above the basis line. Score bonus is applied for long setups as this often precedes strong upward moves.
REL- (Release Bearish)
Indicates squeeze has released with price below the basis line. Score bonus is applied for short setups as this often precedes strong downward moves.
NORM (Normal)
No active squeeze detected. Standard scoring applies.
Trading Implication:
Squeeze releases often produce strong directional moves. The engine detects both the squeeze duration and the release direction, awarding bonus points to signals that align with the release. Longer squeeze duration often corresponds to more powerful breakouts.
LIQUIDITY SWEEP DETECTION
Markets often sweep beyond obvious support and resistance levels to trigger stops before reversing. The engine detects these patterns:
Bullish Sweep Reclaim
Price sweeps below recent swing low, triggering stop losses, then reclaims back above the swing low. This often indicates smart money accumulation after retail stops are collected.
Bearish Sweep Reclaim
Price sweeps above recent swing high, triggering stop losses, then reclaims back below the swing high. This often indicates smart money distribution after retail stops are collected.
Sweep Status in Dashboard:
RCL (Reclaim) - Reclaim has been confirmed. This receives highest structure score as the pattern is complete.
PND (Pending) - Sweep has occurred and price is near the level but full reclaim not yet confirmed. Watching for completion.
ACT (Active) - Sweep is currently in progress with price beyond the swing level.
Dash (-) - No sweep activity detected.
MULTI-FACTOR GATE SYSTEM
Beyond overall score, the engine counts how many individual factors meet their activation threshold.
Example Calculation:
Structure score 45 with threshold 35 equals ACTIVE
Momentum score 25 with threshold 30 equals INACTIVE
Volume score 50 with threshold 35 equals ACTIVE
Volatility score 40 with threshold 30 equals ACTIVE
Pattern score 35 with threshold 30 equals ACTIVE
Result: 4 of 5 factors are active
If minimum required factors is set to 3, this example passes the gate and receives a 4-factor bonus.
Gate Bonuses:
4 factors active adds 8 points to final score (default setting)
5 factors active adds 15 points to final score (perfect confluence)
Purpose:
This mechanism prevents scenarios where one extremely high factor score masks four weak factors. A score of 75 with only 2 active factors is less reliable than a score of 70 with 4 active factors.
ADAPTIVE RISK MANAGEMENT
Take-profit and stop-loss distances adjust dynamically based on three inputs:
Volatility Influence (default 40% weight)
Low ATR percentile produces tighter targets
High ATR percentile produces wider targets
This ensures stops are not too tight in volatile conditions or too wide in calm conditions.
Regime Influence (default 30% weight)
Trending market with aligned signal produces extended targets
Ranging market produces contracted targets
Volatile regime produces wider stops for protection
Score Influence (default 30% weight)
ULTRA signals (high conviction) receive extended targets
STANDARD signals receive standard targets
Higher conviction justifies larger profit expectations.
You can configure the weight of each influence in settings to match your trading style.
SESSION FILTER (Optional Feature)
When enabled, the engine applies score multipliers based on the trading session:
Asian Session (default 0.9x multiplier)
Characterized by lower volatility and ranging tendency. Score reduction reflects reduced opportunity.
London Session (default 1.1x multiplier)
Characterized by high volatility and trend initiation. Score boost reflects increased opportunity.
London/NY Overlap (default 1.2x multiplier)
Characterized by highest liquidity and strongest moves. Maximum score boost reflects peak trading conditions.
New York Session (default 1.05x multiplier)
Characterized by volatility but typically after initial moves have occurred.
Configure your UTC offset in settings to align session detection with your chart timezone.
ALERT SYSTEM
The indicator provides comprehensive alerts with dynamic data:
Signal Alerts:
- ULTRA Long Signal with full trade details
- ULTRA Short Signal with full trade details
- HIGH Long Signal with key levels
- HIGH Short Signal with key levels
- Any Long Signal with basic info
- Any Short Signal with basic info
Trade Management Alerts:
- TP1 Reached with profit percentage
- TP2 Full Target with total profit
- Stop Loss Hit with loss percentage and status
Technical Event Alerts:
- Squeeze Release
- Liquidity Sweep
- Perfect Confluence
- Regime Change
All alerts include actual calculated values such as score, entry price, target levels, stop level, and risk-reward ratio at the time of trigger.
AUTOMATIC SETTINGS VALIDATION
The indicator performs comprehensive validation when first loaded on a chart. If configuration errors are detected, a warning label appears on the chart with specific guidance.
Critical Errors (Prevent Signal Generation):
ULTRA threshold must exceed HIGH threshold
- Example error: HIGH = 75, ULTRA = 70
- Fix: Ensure ULTRA threshold is higher than HIGH threshold
- Default safe values: HIGH = 70, ULTRA = 80
Minimum factors cannot exceed 5
- The gate requires 3 to 5 factors (you cannot require 6 of 5 factors)
- Fix: Set minimum active factors to 3, 4, or 5
TP2 multiplier must exceed TP1 multiplier
- Example error: TP1 = 3.0 ATR, TP2 = 2.0 ATR
- Fix: Ensure TP2 (final target) is farther than TP1 (partial target)
- Default safe values: TP1 = 2.0, TP2 = 5.0
Swing lookback minimum is 3 bars
- Liquidity sweep detection requires at least 3 bars to identify swing highs/lows
- Fix: Increase swing lookback period to 3 or higher
ATR period minimum is 5 bars
- ATR calculation requires sufficient data for accuracy
- Fix: Increase ATR period to 5 or higher (14 recommended)
Higher timeframe must be larger than chart timeframe
- Example error: Trading on 1H chart with MTF set to 15m
- Fix: Select HTF that is 4-12x your chart timeframe
- Example: If trading 15m, use 1H or 4H as HTF
Warnings (Signal Generation Continues):
Score threshold below 50 generates many signals
- Lower thresholds increase signal frequency but reduce quality
- Recommendation: Use minimum 60 for active trading, 70+ for swing trading
Cooldown below 3 bars may cause signal clustering
- Very short cooldowns can produce multiple signals in quick succession
- Recommendation: Use 5+ bars for lower timeframes, 3+ for higher timeframes
Validation Label Display:
When errors are detected, a label appears at the top of the chart showing:
SETTINGS QUICK REFERENCE
Signal Quality Section:
Quality Mode: High Quality recommended for most users
Custom Minimum Score: Used when Quality Mode is set to Custom (range 30-95)
HIGH Threshold: Score required for HIGH tier classification (default 70)
ULTRA Threshold: Score required for ULTRA tier classification (default 80)
Regime Engine Section:
Enable Regime Detection: Activates automatic market state classification
Filter Mode: Off, Adjust Scores, or Block Weak Regimes
ADX Strong Threshold: ADX level indicating strong trend (default 25)
ADX Weak Threshold: ADX level indicating ranging conditions (default 15)
Show Regime Background: Displays subtle background color for current regime
Liquidity and Squeeze Section:
Enable Liquidity Sweep Detection: Activates sweep and reclaim pattern detection
Swing Lookback Period: Bars used to identify swing highs and lows (default 8)
Reclaim Threshold: Percentage of range price must reclaim after sweep (default 15%)
Enable Volatility Squeeze Detection: Activates Bollinger/Keltner squeeze detection
Keltner Channel Multiplier: Width multiplier for Keltner Channel (default 1.5)
Squeeze Penalty: Points subtracted during active squeeze (default 25)
Squeeze Release Bonus: Points added on squeeze release (default 20)
Enable Multi-Factor Gate: Requires minimum factors active before signaling
Minimum Active Factors: How many factors must meet threshold (default 3)
Individual Factor Thresholds: Customize activation threshold for each factor
4-Factor Bonus: Points added when 4 of 5 factors active (default 8)
5-Factor Bonus: Points added when all 5 factors active (default 15)
MTF Confluence Section:
Enable MTF Confluence: Activates higher timeframe trend analysis
Higher Timeframe: Select timeframe for trend alignment (recommend 4-12x chart TF)
Require HTF Alignment: Block signals opposing higher timeframe trend
Show HTF EMAs: Display higher timeframe EMA 21 and EMA 50 on chart
Trading Style Section:
Enable Style Weighting: Activates factor weight adjustments based on style
Trading Style: Balanced, Scalper, Swing Trader, Range Trader, or Trend Follower
Custom Weights: Individual weight sliders when fine-tuning is needed
Session Filter Section:
Enable Session Filter: Activates session-based score multipliers
Your UTC Offset: Your timezone offset for accurate session detection
Session Multipliers: Individual multipliers for Asian, London, New York, and Overlap sessions
Risk Parameters Section:
ATR Period: Period for Average True Range calculation (default 14)
TP1 ATR Multiple: First target distance as ATR multiple (default 2.0)
TP2 ATR Multiple: Final target distance as ATR multiple (default 5.0)
SL ATR Multiple: Stop loss distance as ATR multiple (default 2.0)
Enable Adaptive TP/SL: Activates dynamic adjustment based on conditions
Volatility Weight: Influence of ATR percentile on adaptive calculation (default 40%)
Regime Weight: Influence of market regime on adaptive calculation (default 30%)
Score Weight: Influence of signal score on adaptive calculation (default 30%)
Appearance Section:
Color Theme: Matrix (green/red), Dark (modern dark), or Light (clean light)
Label Detail: Minimal (score only), Standard (key info), or Detailed (full breakdown)
Dashboard Size Controls: Master size and individual overrides for each dashboard
Show Trade Zones: Display shaded box from SL to TP2 for active trades
Show TP/SL Labels: Display price labels on target and stop lines
Show Trailing Exit Labels: Display exit label when stopped after TP1 hit
Show Main Dashboard: Toggle main dashboard visibility (top right)
Show Analysis Dashboard: Toggle analysis panel visibility (bottom left)
Show Status Bar: Toggle compact status bar visibility (bottom center)
Performance Section:
Performance Mode: Reduces visual elements on lower timeframes automatically
Max Ghost Labels: Maximum historical signal labels to retain (default 50)
Signal Cooldown: Minimum bars between signals in same direction (default 5)
Enable Script Alerts: Controls whether alert() calls fire automatically (default ON)
- ON: Dynamic alerts with calculated values fire automatically
- OFF: alert() suppressed, alertcondition() still available for manual creation
- Use OFF when testing settings or monitoring multiple instruments visually
- Toggle per-chart for selective alert coverage across watchlist
Show Factor Markers: Display shapes on chart when 3, 4, or 5 factors align
Show Score Breakdown: Display detailed factor scores table in debug panel
Show Regime Debug: Display regime state and ADX value in debug panel
Show MTF Debug: Display higher timeframe status in debug panel
DEBUG MODE AND FACTOR MARKERS
The indicator includes optional debug tools for traders who want deeper insight into the scoring mechanics and factor analysis. These features are disabled by default to keep the chart clean but can be enabled in the Debug Mode settings group.
FACTOR MARKERS
When "Show Factor Markers" is enabled, visual shapes appear on the chart indicating confluence states:
Perfect Confluence (5/5 Factors Active)
A circle appears below the bar for bullish or above the bar for bearish setups. This represents maximum confluence where all five analytical dimensions meet their activation thresholds simultaneously. A small label showing "5/5" also appears. This is a rare occurrence and typically precedes the highest quality signals. Background color shifts to highlight this exceptional alignment.
Strong Confluence (4/5 Factors Active)
A diamond shape appears below the bar for bullish or above the bar for bearish setups. This represents strong confluence with four of five factors active. A label showing "4/5" appears when this state is first achieved. This level of confluence is associated with high-quality setups.
Ready Confluence (3/5 Factors Active)
A triangle appears below the bar (pointing up) for bullish or above the bar (pointing down) for bearish setups. This represents the minimum confluence level required when gate is set to 3 factors. No label appears for this level to reduce visual clutter.
Confluence Background
When factor markers are enabled, a subtle background color appears indicating the current confluence state. Stronger colors indicate higher confluence levels. Bullish confluence shows green tints while bearish confluence shows red tints.
Purpose of Factor Markers:
These markers help traders visualize when confluence is building before a signal triggers. You might see a 4/5 diamond appear one or two bars before the actual signal, giving you advance notice that conditions are aligning. This can help with preparation and timing.
DEBUG PANEL (Bottom Right)
When any debug option is enabled, a debug panel appears in the bottom right corner of the chart providing detailed scoring information.
Score Breakdown Table
When "Show Score Breakdown" is enabled, the panel displays:
Factor column showing Structure, Momentum, Volume, Volatility, and Pattern
Bull column showing raw score (0-100) for each bullish factor
Bear column showing raw score (0-100) for each bearish factor
Weight column showing current percentage weight for each factor
Below the factor rows :
FINAL row shows the calculated final Bull and Bear scores after all adjustments
Adj row shows total adjustments applied including gate bonus, squeeze adjustment, and exhaustion adjustment with positive or negative sign
This breakdown allows you to see exactly which factors are contributing to the score and which are lagging. If you notice Structure consistently low, you know to wait for better price positioning relative to swing levels.
Regime Debug
When "Show Regime Debug" is enabled, the panel displays:
Current regime state (TREND UP, TREND DN, VOLATILE, RANGE, WEAK)
Current ADX value driving the regime classification
This helps you understand why certain score adjustments are being applied and verify the regime detection is working as expected for current market conditions.
MTF Debug
When "Show MTF Debug" is enabled, the panel displays:
Current MTF alignment status (BULL, BEAR, NEUT)
The higher timeframe being analyzed
This confirms the higher timeframe data is being read correctly and shows you the trend bias from the larger timeframe perspective.
Using Debug Mode Effectively
For Learning: Enable all debug options when first using the indicator to understand how scores are calculated and what drives signal generation.
For Optimization: Use score breakdown to identify which factors are consistently weak in your chosen market and timeframe. This can inform whether to adjust factor thresholds or switch trading styles.
For Troubleshooting: If signals seem inconsistent, enable debug to see exactly what values the engine is working with. This helps identify if a specific factor is behaving unexpectedly.
For Live Trading: Disable debug features to keep chart clean and reduce visual distraction. The main dashboards provide sufficient information for trade execution.
Debug Settings Summary:
Show Factor Markers - Displays shapes on chart when 3, 4, or 5 factors align. Useful for seeing confluence build before signals trigger.
Show Score Breakdown - Displays detailed table with all raw factor scores, weights, and adjustments. Useful for understanding exactly how final score is calculated.
Show Regime Debug - Adds regime state and ADX value to debug panel. Useful for verifying regime detection accuracy.
Show MTF Debug - Adds higher timeframe status and timeframe to debug panel. Useful for confirming MTF data is loading correctly.
PERFORMANCE CONSIDERATIONS
On lower timeframes such as 1-minute and 5-minute charts, the indicator creates visual elements including labels, lines, and boxes that may impact performance on slower devices.
Performance Mode automatically reduces visual elements, optimizes calculation frequency, and limits historical ghost labels when enabled.
Configure Max Ghost Labels (default 50) to control how many historical signal labels are retained on the chart.
NON-REPAINTING DESIGN
Signal Integrity:
All entry and exit signals generate only on confirmed (closed) bars using barstate.isconfirmed checks. This ensures signals do not appear and disappear during bar formation.
Higher Timeframe Data:
MTF analysis uses request.security with lookahead disabled (barmerge.lookahead_off) to prevent future data from influencing current calculations.
Visual Elements:
Lines, boxes, and labels for active trades update in real-time for monitoring purposes but this visual updating does not affect signal generation logic. Entry decisions are made solely on confirmed bar data.
DISCLAIMER
Trading financial instruments involves substantial risk of loss and is not suitable for all investors. Past performance does not guarantee future results. This indicator is a technical analysis tool provided for educational purposes only. It does not constitute financial advice, trading recommendations, or solicitation to buy or sell any financial instrument.
The developer makes no representations regarding the accuracy of signals or the profitability of trading based on this indicator. Users assume full responsibility for their trading decisions and should conduct their own analysis before entering any trade.
Always use proper risk management. Never risk more than you can afford to lose. Consider consulting a qualified financial advisor before making trading decisions.
VERSION HISTORY
v1.0 - Initial Release
- Five-factor confluence scoring system
- Regime detection and automatic adaptation
- Liquidity sweep and reclaim detection
- Volatility squeeze state machine
- Multi-factor gate with bonus system
- Adaptive risk management
- Comprehensive alert system
- Three dashboard display panels
- Session filter with multipliers
- Multiple trading style presets
- Theme customization options
Developed by BullByte
Pine Script v6
2025
ICT Turtle Soup (Riz)The ICT Turtle Soup Complete System is an advanced implementation of the Inner Circle Trader's interpretation of the classic Turtle Soup pattern, designed to identify and trade liquidity sweeps at key market levels. This strategy capitalizes on the systematic stop-loss hunting behavior of institutional traders by detecting when price temporarily breaches significant support/resistance levels to trigger retail stop-losses, then quickly reverses direction.
Core Trading Logic
Liquidity Sweep Detection Method
The strategy monitors five critical liquidity pools where retail traders commonly place stop-loss orders:
⦁ Yesterday's High/Low: Previous daily session extremes
⦁ Daily High/Low: Rolling 20-day period extremes
⦁ 4-Hour High/Low: 30-period extremes on 4H timeframe
⦁ 1-Hour High/Low: 50-period extremes on hourly timeframe
⦁ Recent High/Low: Current timeframe extremes (20-40 bars based on trading mode)
Entry Signal Generation Process
Buy Signal (Sell-Side Liquidity Sweep):
1. Price penetrates below a key support level by a minimum threshold (5-15 ticks depending on signal quality settings)
2. The penetration bar must show strong rejection with at least 30-50% of the candle's range closing back above the swept level
3. Multi-timeframe confirmation checks for structure shift on lower timeframe (break of recent swing high)
4. Confluence scoring system evaluates 7 factors, requiring minimum 3 confirmations:
⦁ Liquidity sweep detected (weighted 2x)
⦁ Higher timeframe bullish market structure
⦁ Lower timeframe bullish break of structure
⦁ Bullish Fair Value Gap presence
⦁ Bullish Order Block formation
⦁ ICT Kill Zone timing alignment
Sell Signal (Buy-Side Liquidity Sweep):
Mirror opposite of buy signal logic, detecting sweeps above resistance levels with bearish rejection.
Risk Management & Position Sizing
Stop Loss Placement:
⦁ Calculated using ATR (Average True Range) multiplied by an adaptive factor
⦁ Base multipliers: Scalping (1.0x), Day Trading (1.5x), Swing Trading (2.0x)
⦁ Further adjusted by signal quality: Conservative (-20%), Balanced (0%), Aggressive (+20%)
⦁ Positioned beyond the liquidity sweep point to avoid re-sweeping
Take Profit Targets:
⦁ TP1: 2.0R (Risk-Reward ratio)
⦁ TP2: 3.5R
⦁ TP3: 5.0R
⦁ All levels rounded to tick precision for accurate order placement
Advanced Features & Filters
Multi-Timeframe Structure Analysis
The system performs top-down analysis across three timeframes:
⦁ Higher Timeframe (HTF): Determines primary trend bias
⦁ Medium Timeframe (MTF): Confirms intermediate structure
⦁ Lower Timeframe (LTF): Identifies precise entry triggers
ICT Kill Zones
Incorporates time-based filtering for optimal trading sessions:
⦁ Asian Session (8PM-12AM UTC)
⦁ London Session (2AM-5AM UTC)
⦁ New York Session (7AM-10AM UTC)
⦁ London Close (10AM-12PM UTC)
Smart Money Concepts Integration
⦁ Fair Value Gaps (FVG): Identifies and displays price inefficiencies that act as magnets
⦁ Order Blocks: Marks institutional accumulation/distribution zones
⦁ Mitigation Detection: Automatically removes FVGs and Order Blocks when price fills them
⦁ Duplicate Sweep Prevention: 10-bar lookback prevents multiple signals at same level
Adaptive Trading Modes
Three pre-configured modes automatically adjust all parameters:
⦁ Scalping: Tight stops, quick targets, 15-minute to 1-hour focus
⦁ Day Trading: Balanced approach, 4-hour to daily analysis
⦁ Swing Trading: Wide stops, extended targets, daily to weekly perspective
⦁ Custom Mode: Full manual control of all parameters
Signal Quality Management
⦁ Conservative: Requires 5/7 confluence factors, tighter sweep threshold (5 ticks), 50% minimum rejection
⦁ Balanced: Standard 3/7 confluence, moderate threshold (10 ticks), 30% rejection
⦁ Aggressive: Only 2/7 confluence needed, wider threshold (15 ticks), 20% rejection
Visual Components & Dashboard
Real-Time Information Panel
Displays current market conditions including:
⦁ Active trading mode and quality settings
⦁ Timeframe configuration (HTF/MTF/LTF)
⦁ Market bias from higher timeframes
⦁ Current kill zone status
⦁ Liquidity sweep detection status
⦁ Confluence scoring for both directions
⦁ Risk parameters and targets
Trade Visualization
⦁ Entry, stop-loss, and three take-profit levels with precise price labels
⦁ Automatic cleanup when targets are hit or new signals appear
⦁ Maximum of one active setup displayed for chart clarity
⦁ Color-coded boxes for Fair Value Gaps and Order Blocks
How to Use This Indicator
Recommended Timeframes
⦁ Scalping Mode: 1-minute to 5-minute charts
⦁ Day Trading Mode: 5-minute to 15-minute charts
⦁ Swing Trading Mode: 1-hour to 4-hour charts
Optimal Market Conditions
⦁ Works best in ranging or trending markets with clear support/resistance levels
⦁ Most effective during high-liquidity sessions (London/New York overlap)
⦁ Avoid using during major news events unless specifically targeting news-driven sweeps
Signal Interpretation
1. Wait for triangle signal (up/down) with confluence score
2. Verify the swept level shown in the dashboard
3. Confirm risk-reward ratios match your trading plan
4. Enter at market or set limit order at indicated entry level
5. Place stop-loss and take-profit orders at displayed levels
Customization Tips
⦁ Adjust Signal Quality based on market volatility (Conservative for volatile, Aggressive for quiet)
⦁ Modify sweep threshold if getting too many/few signals
⦁ Toggle individual liquidity levels based on their relevance to your timeframe
⦁ Use Kill Zone filter for session-specific trading
Risk Disclaimer
This indicator identifies potential trade setups based on liquidity sweep patterns but does not guarantee profitable outcomes. Past performance does not indicate future results. Always use proper risk management and never risk more than you can afford to lose. The indicator should be used as part of a comprehensive trading plan that includes your own analysis and risk tolerance assessment.
Liquidations Levels [RunRox]📈 Liquidation Levels is an indicator designed to visualize key price levels on the chart, highlighting potential reversal points where liquidity may trigger significant price movements.
Liquidity is essential in trading - price action consistently moves from one liquidity area to another. We’ve created this free indicator to help traders easily identify and visualize these liquidity zones on their charts.
📌 HOW IT WORKS
The indicator works by marking visible highs and lows, points widely recognized by traders. Because many traders commonly place their stop-loss orders beyond these visible extremes, significant liquidity accumulates behind these points. By analyzing trading volume and visible extremes, the indicator estimates areas where clusters of stop-loss orders (liquidity pools) are likely positioned, giving traders valuable insights into potential market moves.
As shown in the screenshot above, the price aggressively moved toward Sell-Side liquidity. After sweeping this liquidity level for the second time, it reversed and began targeting Buy-Side liquidity. This clearly demonstrates how price moves from one liquidity pool to another, continually seeking out liquidity to fuel its next directional move.
As shown in the screenshot, price levels with fewer anticipated trader stop-losses are indicated by less vibrant, faded colors. When the lines become more saturated and vivid, it signals that sufficient liquidity - in the form of clustered stop-losses has accumulated, potentially attracting price movement toward these areas.
⚙️ SETTINGS
🔹 Period – Increasing this setting makes the marked highs and lows more significant, filtering out minor price swings.
🔹 Low Volume – Select the color displayed for low-liquidity levels.
🔹 High Volume – Select the color displayed for high-liquidity levels.
🔹 Levels to Display – Choose between 1 and 15 nearest liquidity levels to be shown on the chart.
🔹 Volume Sensitivity – Adjust the sensitivity of the indicator to volume data on the chart.
🔹 Show Volume – Enable or disable the display of volume values next to each liquidity level.
🔹 Max Age – Limits displayed liquidity levels to those not older than the specified number of bars.
✅ HOW TO USE
One method of using this indicator is demonstrated in the screenshot above.
Price reached a high-liquidity level and showed an initial reaction. We then waited for a second confirmation - a liquidity sweep followed by a clear market structure break - to enter the trade.
Our target is set at the liquidity accumulated below, with the stop-loss placed behind the manipulation high responsible for the liquidity sweep.
By following this approach, you can effectively identify trading opportunities using this indicator.
🔶 We’ve made every effort to create an indicator that’s as simple and user-friendly as possible. We’ll continue to improve and enhance it based on your feedback and suggestions in the future.
Quantify [Entry Model] | FractalystWhat’s the indicator’s purpose and functionality?
Quantify is a machine learning entry model designed to help traders identify high-probability setups to refine their strategies.
➙ Simply pick your bias, select your entry timeframes, and let Quantify handle the rest for you.
Can the indicator be applied to any market approach/trading strategy?
Absolutely, all trading strategies share one fundamental element: Directional Bias
Once you’ve determined the market bias using your own personal approach, whether it’s through technical analysis or fundamental analysis, select the trend direction in the Quantify user inputs.
The algorithm will then adjust its calculations to provide optimal entry levels aligned with your chosen bias. This involves analyzing historical patterns to identify setups with the highest potential expected values, ensuring your setups are aligned with the selected direction.
Can the indicator be used for different timeframes or trading styles?
Yes, regardless of the timeframe you’d like to take your entries, the indicator adapts to your trading style.
Whether you’re a swing trader, scalper, or even a position trader, the algorithm dynamically evaluates market conditions across your chosen timeframe.
How can this indicator help me to refine my trading strategy?
1. Focus on Positive Expected Value
• The indicator evaluates every setup to ensure it has a positive expected value, helping you focus only on trades that statistically favor long-term profitability.
2. Adapt to Market Conditions
• By analyzing real-time market behavior and historical patterns, the algorithm adjusts its calculations to match current conditions, keeping your strategy relevant and adaptable.
3. Eliminate Emotional Bias
• With clear probabilities, expected values, and data-driven insights, the indicator removes guesswork and helps you avoid emotional decisions that can damage your edge.
4. Optimize Entry Levels
• The indicator identifies optimal entry levels based on your selected bias and timeframes, improving robustness in your trades.
5. Enhance Risk Management
• Using tools like the Kelly Criterion, the indicator suggests optimal position sizes and risk levels, ensuring that your strategy maintains consistency and discipline.
6. Avoid Overtrading
• By highlighting only high-potential setups, the indicator keeps you focused on quality over quantity, helping you refine your strategy and avoid unnecessary losses.
How can I get started to use the indicator for my entries?
1. Set Your Market Bias
• Determine whether the market trend is Bullish or Bearish using your own approach.
• Select the corresponding bias in the indicator’s user inputs to align it with your analysis.
2. Choose Your Entry Timeframes
• Specify the timeframes you want to focus on for trade entries.
• The indicator will dynamically analyze these timeframes to provide optimal setups.
3. Let the Algorithm Analyze
• Quantify evaluates historical data and real-time price action to calculate probabilities and expected values.
• It highlights setups with the highest potential based on your selected bias and timeframes.
4. Refine Your Entries
• Use the insights provided—entry levels, probabilities, and risk calculations—to align your trades with a math-driven edge.
• Avoid overtrading by focusing only on setups with positive expected value.
5. Adapt to Market Conditions
• The indicator continuously adapts to real-time market behavior, ensuring its recommendations stay relevant and precise as conditions change.
How does the indicator calculate the current range?
The indicator calculates the current range by analyzing swing points from the very first bar on your charts to the latest available bar it identifies external liquidity levels, also known as BSLQ (buy-side liquidity levels) and SSLQ (sell-side liquidity levels).
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
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.
What does the multi-timeframe functionality offer?
You can incorporate up to 4 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.
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.
How does the Indicator Identifies Positive Expected Values?
Quantify instantly calculates whether a trade setup has the potential to generate positive expected value (EV).
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.
How can I know that the setup I'm going to trade with has a positive 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.
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.
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.
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.
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.
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.
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.
What machine learning techniques are used in Quantify?
Quantify offers two main machine learning approaches:
1. Adaptive Learning (Fixed Sample Size): The algorithm learns from the entire dataset without resampling, maintaining a stable model that adapts to the latest market conditions.
2. Bootstrap Resampling: This method creates multiple subsets of the historical data, allowing the model to train on varying sample sizes. This technique enhances the robustness of predictions by ensuring that the model is not overfitting to a single dataset.
How does machine learning affect the expected value calculations in Quantify?
Machine learning plays a key role in improving the accuracy of expected value (EV) calculations. By analyzing historical price action, liquidity hits, and market bias patterns, the model continuously adjusts its understanding of risk and reward, allowing the expected value to reflect the most likely market movements. This results in more precise EV predictions, helping traders focus on setups that maximize profitability.
What is the Kelly Criterion, and how does it work in Quantify?
The Kelly Criterion is a mathematical formula used to determine the optimal position size for each trade, maximizing long-term growth while minimizing the risk of large drawdowns. It calculates the percentage of your portfolio to risk on a trade based on the probability of winning and the expected payoff.
Quantify integrates this with user-defined inputs to dynamically calculate the most effective position size in percentage, aligning with the trader’s risk tolerance and desired exposure.
How does Quantify use the Kelly Criterion in practice?
Quantify uses the Kelly Criterion to optimize position sizing based on the following factors:
1. Confidence Level: The model assesses the confidence level in the trade setup based on historical data and sample size. A higher confidence level increases the suggested position size because the trade has a higher probability of success.
2. Max Allowed Drawdown (User-Defined): Traders can set their preferred maximum allowed drawdown, which dictates how much loss is acceptable before reducing position size or stopping trading. Quantify uses this input to ensure that risk exposure aligns with the trader’s risk tolerance.
3. Probabilities: Quantify calculates the probabilities of success for each trade setup. The higher the probability of a successful trade (based on historical price action and liquidity levels), the larger the position size suggested by the Kelly Criterion.
What is a trailing stoploss, and how does it work in Quantify?
A trailing stoploss is a dynamic risk management tool that moves with the price as the market trend continues in the trader’s favor. Unlike a fixed take profit, which stays at a set level, the trailing stoploss automatically adjusts itself as the market moves, locking in profits as the price advances.
In Quantify, the trailing stoploss is enhanced by incorporating market structure liquidity levels (explain above). This ensures that the stoploss adjusts intelligently based on key price levels, allowing the trader to stay in the trade as long as the trend remains intact, while also protecting profits if the market reverses.
Why would a trader prefer a trailing stoploss based on liquidity levels instead of a fixed take-profit level?
Traders who use trailing stoplosses based on liquidity levels prefer this method because:
1. Market-Driven Flexibility: The stoploss follows the market structure rather than being static at a pre-defined level. This means the stoploss is less likely to be hit by small market fluctuations or false reversals. The stoploss remains adaptive, moving as the market moves.
2. Riding the Trend: Traders can capture more profit during a sustained trend because the trailing stop will adjust only when the trend starts to reverse significantly, based on key liquidity levels. This allows them to hold positions longer without prematurely locking in profits.
3. Avoiding Premature Exits: Fixed stoploss levels may exit a trade too early in volatile markets, while liquidity-based trailing stoploss levels respect the natural flow of price action, preventing the trader from exiting too soon during pullbacks or minor retracements.
🎲 Becoming the House: Gaining an Edge Over the Market
In American roulette, the casino has a 5.26% edge due to the presence of the 0 and 00 pockets. On even-money bets, players face a 47.37% chance of winning, while true 50/50 odds would require a 50% chance. This edge—the gap between the payout odds and the true probabilities—ensures that, statistically, the casino will always win over time, even if individual players win occasionally.
From a Trader’s Perspective
In trading, your edge comes from identifying and executing setups with a positive expected value (EV). For example:
• If you identify a setup with a 55.48% chance of winning and a 1:1 risk-to-reward (RR) ratio, your trade has a statistical advantage over a neutral (50/50) probability.
This edge works in your favor when applied consistently across a series of trades, just as the casino’s edge ensures profitability across thousands of spins.
🎰 Applying the Concept to Trading
Like casinos leverage their mathematical edge in games of chance, you can achieve long-term success in trading by focusing on setups with positive EV and managing your trades systematically. Here’s how:
1. Probability Advantage: Prioritize trades where the probability of success (win rate) exceeds the breakeven rate for your chosen risk-to-reward ratio.
• Example: With a 1:1 RR, you need a win rate above 50% to achieve positive EV.
2. Risk-to-Reward Ratio (RR): Even with a win rate below 50%, you can gain an edge by increasing your RR (e.g., a 40% win rate with a 2:1 RR still has positive EV).
3. Consistency and Discipline: Just as casinos profit by sticking to their mathematical advantage over thousands of spins, traders must rely on their edge across many trades, avoiding emotional decisions or overleveraging.
By targeting favorable probabilities and managing trades effectively, you “become the house” in your trading. This approach allows you to leverage statistical advantages to enhance your overall performance and achieve sustainable profitability.
What Makes the Quantify Indicator Original?
1. Data-Driven Edge
Unlike traditional indicators that rely on static formulas, Quantify leverages probability-based analysis and machine learning. It calculates expected value (EV) and confidence levels to help traders identify setups with a true statistical edge.
2. Integration of Market Structure
Quantify uses market structure liquidity levels to dynamically adapt. It identifies key zones like swing highs/lows and liquidity traps, enabling users to align entries and exits with where the market is most likely to react. This bridges the gap between price action analysis and quantitative trading.
3. Sophisticated Risk Management
The Kelly Criterion implementation is unique. Quantify allows traders to input their maximum allowed drawdown, dynamically adjusting risk exposure to maintain optimal position sizing. This ensures risk is scientifically controlled while maximizing potential growth.
4. Multi-Timeframe and Liquidity-Based Trailing Stops
The indicator doesn’t just suggest fixed profit-taking levels. It offers market structure-based trailing stop-loss functionality, letting traders ride trends as long as liquidity and probabilities favor the position, which is rare in most tools.
5. Customizable Bias and Adaptive Learning
• Directional Bias: Traders can set a bullish or bearish bias, and the indicator recalculates probabilities to align with the trader’s market outlook.
• Adaptive Learning: The machine learning model adapts to changes in data (via resampling or bootstrap methods), ensuring that predictions stay relevant in evolving markets.
6. Positive EV Focus
The focus on positive EV setups differentiates it from reactive indicators. It shifts trading from chasing signals to acting on setups that statistically favor profitability, akin to how professional quant funds operate.
7. User Empowerment
Through features like customizable timeframes, real-time probability updates, and visualization tools, Quantify empowers users to make data-informed decisions.
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.
SMC Liquidity ZonesThis script implements a "Smart Money Concept (SMC) Liquidity Zones" indicator in Pine Script™ for TradingView. It helps identify key liquidity zones, detect potential order blocks, and highlight market structure breaks. The script is designed for traders who use liquidity concepts and order blocks to make informed trading decisions based on price action.
1. Indicator Overview:
The "SMC Liquidity Zones" indicator plots areas of high and low liquidity and detects potential order blocks after price breaks these zones. It also highlights market structure shifts when price moves past the liquidity zones, allowing traders to identify potential areas of price reversal or continuation.
2. Key Features:
Liquidity Zones:
Liquidity zones are regions where price is likely to experience strong reactions due to resting orders (buy or sell).
The script identifies these zones by looking for pivot highs and pivot lows using a customizable lookback period.
High Liquidity Zone: Found at pivot highs, indicating a potential zone of sell-side liquidity (where sellers may overwhelm buyers).
Low Liquidity Zone: Found at pivot lows, indicating a potential buy-side liquidity zone (where buyers may absorb selling pressure).
Order Blocks Detection:
After a liquidity zone is broken, the script marks an order block.
Order Block: An area where institutional traders (smart money) might have placed large orders, and price is expected to return to this area for liquidity.
When the price closes above the high liquidity zone, the previous high is assumed to form the order block high, while the closing price forms the order block low.
Similarly, when price closes below the low liquidity zone, the previous low is assumed to form the order block low, and the closing price forms the order block high.
Market Structure Breaks:
Bullish Market Structure Break: Occurs when price closes above the high liquidity zone, potentially signaling an upward trend.
Bearish Market Structure Break: Occurs when price closes below the low liquidity zone, signaling a potential downward trend.
The script highlights these breaks by changing the chart’s background color to green for bullish structure and red for bearish structure.
Customizable Settings:
Pivot Lookback Period: You can set the lookback period to adjust how the indicator identifies pivot highs and lows.
Visibility of Liquidity Zones and Order Blocks: The script provides options to toggle the display of liquidity zones and order blocks on or off, allowing traders to customize the chart view.
3. Code Structure:
Liquidity Zones Identification:
The script uses the ta.pivothigh() and ta.pivotlow() functions to detect pivot points over a customizable lookback period.
These pivots mark significant areas of price where liquidity might rest, and the zones are displayed using dashed lines—red for high liquidity and green for low liquidity.
Order Block Logic:
When price breaks through a liquidity zone (either above or below), the script marks an order block. This block is a potential area where price could return, creating opportunities for entries or exits.
The order block is visualized as a blue box on the chart, indicating areas where smart money may have positioned their orders.
Market Structure Break Highlights:
The background color changes based on whether the market has broken into a bullish or bearish structure:
Bullish Market Structure: Green background.
Bearish Market Structure: Red background.
This visual cue helps traders quickly assess market sentiment and potential future price direction.
4. Use Case:
This indicator is particularly suited for traders following Smart Money Concepts (SMC), liquidity-based trading, or order block strategies. It helps them:
Identify potential price reaction zones (liquidity zones).
Spot order blocks, which are areas where institutional traders are likely to have placed large orders.
Recognize market structure shifts, signaling potential trend reversals or continuations.
Highlight trading opportunities based on liquidity breaks and market structure changes.
ICT Judas Swing | Flux Charts💎 GENERAL OVERVIEW
Introducing our new ICT Judas Swing Indicator! This indicator is built around the ICT's "Judas Swing" strategy. The strategy looks for a liquidity grab around NY 9:30 session and a Fair Value Gap for entry confirmation. For more information about the process, check the "HOW DOES IT WORK" section.
Features of the new ICT Judas Swing :
Implementation of ICT's Judas Swing Strategy
2 Different TP / SL Methods
Customizable Execution Settings
Customizable Backtesting Dashboard
Alerts for Buy, Sell, TP & SL Signals
📌 HOW DOES IT WORK ?
The strategy begins by identifying the New York session from 9:30 to 9:45 and marking recent liquidity zones. These liquidity zones are determined by locating high and low pivot points: buyside liquidity zones are identified using high pivots that haven't been invalidated, while sellside liquidity zones are found using low pivots. A break of either buyside or sellside liquidity must occur during the 9:30-9:45 session, which is interpreted as a liquidity grab by smart money. The strategy assumes that after this liquidity grab, the price will reverse and move in the opposite direction. For entry confirmation, a fair value gap (FVG) in the opposite direction of the liquidity grab is required. A buyside liquidity grab calls for a bearish FVG, while a sellside grab requires a bullish FVG. Based on the type of FVG—bullish for buys and bearish for sells—the indicator will then generate a Buy or Sell signal.
After the Buy or Sell signal, the indicator immediately draws the take-profit (TP) and stop-loss (SL) targets. The indicator has three different TP & SL modes, explained in the "Settings" section of this write-up.
You can set up alerts for entry and TP & SL signals, and also check the current performance of the indicator and adjust the settings accordingly to the current ticker using the backtesting dashboard.
🚩 UNIQUENESS
This indicator is an all-in-one suit for the ICT's Judas Swing concept. It's capable of plotting the strategy, giving signals, a backtesting dashboard and alerts feature. Different and customizable algorithm modes will help the trader fine-tune the indicator for the asset they are currently trading. Three different TP / SL modes are available to suit your needs. The backtesting dashboard allows you to see how your settings perform in the current ticker. You can also set up alerts to get informed when the strategy is executable for different tickers.
⚙️ SETTINGS
1. General Configuration
Swing Length -> The swing length for pivot detection. Higher settings will result in
FVG Detection Sensitivity -> You may select between Low, Normal, High or Extreme FVG detection sensitivity. This will essentially determine the size of the spotted FVGs, with lower sensitivies resulting in spotting bigger FVGs, and higher sensitivies resulting in spotting all sizes of FVGs.
2. TP / SL
TP / SL Method ->
a) Dynamic: The TP / SL zones will be auto-determined by the algorithm based on the Average True Range (ATR) of the current ticker.
b) Fixed : You can adjust the exact TP / SL ratios from the settings below.
Dynamic Risk -> The risk you're willing to take if "Dynamic" TP / SL Method is selected. Higher risk usually means a better winrate at the cost of losing more if the strategy fails. This setting is has a crucial effect on the performance of the indicator, as different tickers may have different volatility so the indicator may have increased performance when this setting is correctly adjusted.
Change in State of Delivery (CISD) [LuxAlgo]The Change In State Of Delivery (CISD) indicator detects and displays Change in State Of Delivery, a concept related to market structures.
Users can choose between two different CISD detection methods. Various filtering options are also included to filter out less significant CISDs.
🔶 USAGE
A Change in State of Delivery (CISD) is a concept closely related to market structures, where price breaks a level of interest, confirming trends and their continuations from the resulting breakouts.
Unlike more traditional market structures which rely on swing points, CISDs rely on a persistent sequence of candles, using the sequence extremes as breakout levels.
CISDs are detected as follows:
Bullish: The price closes above the opening price of the first candle in a sequence of bearish candles (or its own opening price if it's the only candle).
Bearish: The price closes below the opening price of the first candle in a sequence of bullish candles (or its own opening price if it's the only candle).
If a newly detected CISD aligns with the indicator's current established trend, this confirms a trend continuation (represented with a dashed line).
On the other hand, if a newly detected CISD is in the opposite direction to the detected trend it can confirm a trend reversal (represented with a solid line).
🔹 Liquidity Sweep Detection Method
Using Liquidity Sweeps to update CISD breakout levels allows us to obtain less frequent and more relevant levels that are less sensitive to noisy price variations.
Sweeps are obtained from detected Swing Points , with a higher Swing Length allowing us to obtain longer-term swing levels and potentially more detected sweeps from a specific level over time.
Note: The 'Swing Length' setting is only applicable on the Liquidity Sweep Detection Method and will only change the Liquidity levels.
A Liquidity Sweep is valid when the price reaches an important liquidity level , after which the price closes below/above this level.
Bullish scenario: The price goes below a previous unbroken Swing Low but closes above.
Bearish scenario: The price goes above a previous unbroken Swing High but closes below.
After a Liquidity Sweep has been detected, the last level of importance acts as support/resistance . Breaking this level in the other direction changes the state of delivery .
Users must keep observing the price and significant levels, as highlighted by the white rectangle in the above example.
🔹 CISD Filtering
Users can adjust the following two settings:
Minimum CISD Duration: The minimum length of the 'CISD' line
Maximum Swing Validity: The maximum length of the 'CISD' line; potential CISD lines that aren't broken are deleted when exceeding the limit.
The chart can get cluttered when the Minimum CISD Duration is low. Users could focus on a switch in trend (first solid line CISD ), where the following dashed CISD lines can be seen as extra opportunities/confirmations.
🔶 DETAIL
🔹 Using Different Timeframes
When an important liquidity level (Previous Swing high/low, FVG, etc.) is reached on the higher timeframe, the user can move to a lower timeframe to check whether there is a CISD .
Above example:
The high of the last candle breaches a liquidity level (previous Swing High). The opening price of the last candle acts as a trigger/confirmation level.
A confirmed CISD is seen in a lower timeframe, just after this Liquidity Sweep. This could be an early opportunity.
Later, a confirmed CISD on the higher timeframe is established.
🔶 SETTINGS
Detection Method: Classic or Liquidity Sweep
Swing Length: Period used for the swing detection, with higher values returning longer-term Swing Levels.
Minimum CISD Duration: The minimum length of the CISD line
Maximum Swing Validity: The maximum length of the CISD line; potential CISD lines that aren't broken are deleted when exceeding the limit.
ICT Turtle Soup | Flux Charts💎 GENERAL OVERVIEW
Introducing our new ICT Turtle Soup Indicator! This indicator is built around the ICT "Turtle Soup" model. The strategy has 5 steps for execution which are described in this write-up. For more information about the process, check the "HOW DOES IT WORK" section.
Features of the new ICT Turtle Soup Indicator :
Implementation of ICT's Turtle Soup Strategy
Adaptive Entry Method
Customizable Execution Settings
Customizable Backtesting Dashboard
Alerts for Buy, Sell, TP & SL Signals
📌 HOW DOES IT WORK ?
The ICT Turtle Soup strategy may have different implementations depending on the selected method of the trader. This indicator's implementation is described as :
1. Mark higher timerame liquidity zones.
Liquidity zones are where a lot of market orders sit in the chart. They are usually formed from the long / short position holders' "liquidity" levels. There are various ways to find them, most common one being drawing them on the latest high & low pivot points in the chart, which this indicator does.
2. Mark current timeframe market structure.
The market structure is the current flow of the market. It tells you if the market is trending right now, and the way it's trending towards. It's formed from swing higs, swing lows and support / resistance levels.
3. Wait for market to make a liquidity grab on the higher timeframe liquidity zone.
A liquidity grab is when the marked liquidity zones have a false breakout, which means that it gets broken for a brief amount of time, but then price falls back to it's previous position.
4. Buyside liquidity grabs are "Short" entries and Sellside liquidity grabs are "Long" entries by default.
5. Wait for the market-structure shift in the current timeframe for entry confirmation.
A market-structure shift happens when the current market structure changes, usually when a new swing high / swing low is formed. This indicator uses it as a confirmation for position entry as it gives an insight of the new trend of the market.
6. Place Take-Profit and Stop-Loss levels according to the risk ratio.
This indicator uses "Average True Range" when placing the stop-loss & take-profit levels. Average True Range calculates the average size of a candle and the indicator places the stop-loss level using ATR times the risk setting determined by the user, then places the take-profit level trying to keep a minimum of 1:1 risk-reward ratio.
This indicator follows these steps and inform you step by step by plotting them in your chart.
🚩UNIQUENESS
This indicator is an all-in-one suit for the ICT's Turtle Soup concept. It's capable of plotting the strategy, giving signals, a backtesting dashboard and alerts feature. It's designed for simplyfing a rather complex strategy, helping you to execute it with clean signals. The backtesting dashboard allows you to see how your settings perform in the current ticker. You can also set up alerts to get informed when the strategy is executable for different tickers.
⚙️SETTINGS
1. General Configuration
MSS Swing Length -> The swing length when finding liquidity zones for market structure-shift detection.
Higher Timeframe -> The higher timeframe to look for liquidity grabs. This timeframe setting must be higher than the current chart's timeframe for the indicator to work.
Breakout Method -> If "Wick" is selected, a bar wick will be enough to confirm a market structure-shift. If "Close" is selected, the bar must close above / below the liquidity zone to confirm a market structure-shift.
Entry Method ->
"Classic" : Works as described on the "HOW DOES IT WORK" section.
"Adaptive" : When "Adaptive" is selected, the entry conditions may chance depending on the current performance of the indicator. It saves the entry conditions and the performance of the past entries, then for the new entries it checks if it predicted the liquidity grabs correctly with the current setup, if so, continues with the same logic. If not, it changes behaviour to reverse the entries from long / short to short / long.
2. TP / SL
TP / SL Method -> If "Fixed" is selected, you can adjust the TP / SL ratios from the settings below. If "Dynamic" is selected, the TP / SL zones will be auto-determined by the algorithm.
Risk -> The risk you're willing to take if "Dynamic" TP / SL Method is selected. Higher risk usually means a better winrate at the cost of losing more if the strategy fails. This setting is has a crucial effect on the performance of the indicator, as different tickers may have different volatility so the indicator may have increased performance when this setting is correctly adjusted.
Global Liquidity IndexThe Global Liquidity Index offers a consolidated view of all major central bank balance sheets from around the world. For consistency and ease of comparison, all values are converted to USD using their relevant forex rates and are expressed in trillions. The indicator incorporates specific US accounts such as the Treasury General Account (TGA) and Reverse Repurchase Agreements (RRP), both of which are subtracted from the Federal Reserve's balance sheet to give a more nuanced view of US liquidity. Users have the flexibility to enable or disable specific central banks and special accounts based on their preference. Only central banks that both don’t engage in currency pegging and have reliable data available from late 2007 onwards are included in this aggregated liquidity model.
Global Liquidity Index = Federal Reserve System (FED) - Treasury General Account (TGA) - Reverse Repurchase Agreements (RRP) + European Central Bank (ECB) + People's Bank of China (PBC) + Bank of Japan (BOJ) + Bank of England (BOE) + Bank of Canada (BOC) + Reserve Bank of Australia (RBA) + Reserve Bank of India (RBI) + Swiss National Bank (SNB) + Central Bank of the Russian Federation (CBR) + Central Bank of Brazil (BCB) + Bank of Korea (BOK) + Reserve Bank of New Zealand (RBNZ) + Sweden's Central Bank (Riksbank) + Central Bank of Malaysia (BNM).
This tool is beneficial for anyone seeking to get a snapshot of global liquidity to interpret macroeconomic trends. By examining these balance sheets, users can deduce policy trajectories and evaluate the global economic climate. It also offers insights into asset pricing and assists investors in making informed capital allocation decisions. Historically, riskier assets, such as small caps and cryptocurrencies, have typically performed well during periods of rising liquidity. Thus, it may be prudent for investors to avoid additional risk unless there's a consistent upward trend in global liquidity.
Quasimodo (QML) Pattern [Kodexius]Quasimodo (QML) Pattern is a market structure indicator that automatically detects Bullish and Bearish Quasimodo formations using confirmed swing pivots, then visualizes the full structure directly on the chart. The script focuses on the classic liquidity-grab narrative of the QML: a sweep beyond a prior swing (the Head) followed by a decisive market structure break (MSB), leaving behind a clearly defined reaction zone between the Left Shoulder and the Head.
Detection is built on pivot highs and lows, so patterns are evaluated only after swing points are validated. Once a valid 4 pivot sequence is identified, the indicator draws the pattern legs, highlights the internal triangle area to emphasize the grab, marks the MSB leg, and projects a QML zone that can be used as a potential area of interest for retests.
This tool is designed for traders who work with structure, liquidity concepts, and reversal/continuation triggers, and who want a clean, repeatable QML visualization without manually marking swings.
🔹 Features
🔸 Confirmed Pivot Based Structure Mapping
The script uses classic built-in pivot logic to detect swing highs and swing lows.
🔸 Automatic Bullish and Bearish QML Detection
The indicator evaluates the most recent 4 pivots and checks for a valid alternating sequence (High-Low-High-Low or Low-High-Low-High). When the sequence matches QML requirements, the script classifies the setup as bullish or bearish:
Bullish logic (structure reversal up):
- Left Shoulder is a pivot Low
- Head is a lower Low than the Left Shoulder (liquidity sweep)
- MSB pivot exceeds the Reaction pivot
Bearish logic (structure reversal down):
- Left Shoulder is a pivot High
- Head is a higher High than the Left Shoulder (liquidity sweep)
- MSB pivot breaks below the Reaction pivot
🔸 Full Pattern Visualization (Legs + Highlighted Core)
When a pattern triggers, the script draws:
Three main legs: Left Shoulder to Reaction, Reaction to Head, Head to MSB
A shaded triangular highlight over the internal structure to make the liquidity-grab shape easy to spot at a glance
🔸 QML Zone Projection
A QML Zone box is drawn using the price range defined between the Left Shoulder and the Head, then extended to the right to remain visible as price develops. This zone is intended to act as a practical reference area for potential retests and reaction planning after MSB confirmation.
🔸 MSB Emphasis
A dotted MSB line is drawn between the Reaction point and the MSB point to visually emphasize the confirmation leg that completes the pattern logic.
🔸 Clean Point Tagging and Directional Labeling
Key points are labeled directly on the chart:
- “LS” at the Left Shoulder
- “Head” at the sweep pivot
- “MSB” at the break pivot
A directional label (“Bullish QML” or “Bearish QML”) is also printed to quickly identify the detected bias.
🔸 Configurable Visual Style
All main visual components are user configurable:
- Bullish and bearish colors
- Line width
- Label size
🔸 Efficient Update Logic
Pattern checks are only performed when a new pivot is confirmed, avoiding unnecessary repeated calculations on every bar. The most recent pattern’s projected elements (zone and label positioning) are updated as new bars print to keep the latest setup readable.
🔹 Calculations
This section summarizes the core logic used for detection and plotting.
1. Pivot Detection (Swing Highs and Lows)
The script relies on confirmed pivots using the user inputs:
Left Bars: how many bars must exist to the left of the pivot
Right Bars: how many bars must exist to the right to confirm it
float ph = ta.pivothigh(leftLen, rightLen)
float pl = ta.pivotlow(leftLen, rightLen)
When a pivot is confirmed, its true bar index is the pivot bar, not the current bar, so the script stores:
bar_index
2. Pivot Storage and History Window
Each pivot is stored as a structured object containing:
- price
- index
- isHigh (true for pivot high, false for pivot low)
A rolling history is maintained (up to 50 pivots) to keep processing stable and memory usage controlled.
3. Sequence Validation (Alternation Check)
The pattern evaluation always uses the latest 4 pivots:
p0: Left Shoulder candidate
p1: Reaction candidate
p2: Head candidate
p3: MSB candidate
Before checking bullish/bearish rules, the script enforces alternating pivot types:
bool correctSequence =
(p0.isHigh != p1.isHigh) and
(p1.isHigh != p2.isHigh) and
(p2.isHigh != p3.isHigh)
This prevents invalid structures like consecutive highs or consecutive lows from being interpreted as QML.
4. Bullish QML Conditions
A bullish QML is evaluated when the Left Shoulder is a Low:
Head must be lower than Left Shoulder (sweep)
MSB must be higher than Reaction (break)
if not p0.isHigh
if p2.price < p0.price and p3.price > p1.price
// Bullish QML confirmed
Interpretation:
p2 < p0 represents the liquidity grab below the prior swing low
p3 > p1 represents the market structure break above the reaction high
5. Bearish QML Conditions
A bearish QML is evaluated when the Left Shoulder is a High:
Head must be higher than Left Shoulder (sweep)
MSB must be lower than Reaction (break)
if p0.isHigh
if p2.price > p0.price and p3.price < p1.price
// Bearish QML confirmed
Interpretation:
p2 > p0 represents the liquidity grab above the prior swing high
p3 < p1 represents the market structure break below the reaction low
6. Drawing Logic (Structure, Highlight, Zone, Labels)
When confirmed, the script draws:
Three connecting legs (LS to Reaction, Reaction to Head, Head to MSB)
A shaded triangle using a transparent “ghost” line to enable filling
A dotted MSB emphasis line between Reaction and MSB
A QML Zone box spanning the LS to Head price range and projecting to the right
Point labels: LS, Head, MSB
A direction label: “Bullish QML” or “Bearish QML”
7. Latest Pattern Extension
To keep the newest setup readable, the script updates the most recently detected pattern by extending its projected elements as new bars print:
QML zone right edge is pushed forward
The main label x position is pushed forward
This keeps the last identified QML zone visible as price evolves, without having to redraw historical patterns on every bar.
FOMC Sweep Reaction AP Capital – FOMC Sweep Reaction v1.0
AP Capital – FOMC Sweep Reaction v1.0 is a news-reaction and liquidity-based trading tool designed specifically to track and trade FOMC volatility on Gold (XAUUSD) and other highly reactive instruments.
The indicator focuses on liquidity sweeps, structure breaks, and EMA reclaims that commonly occur around Federal Reserve interest-rate decisions and Powell speeches, helping traders identify high-probability reversal or continuation moves after the initial spike.
🔍 What This Indicator Detects
This tool highlights the most repeatable FOMC behaviours observed across multiple months of broker data:
• Sweeps of previous day’s high or low
• Stop-hunt wicks into liquidity pools
• EMA13 reclaim after the news spike
• Break and close beyond short-term structure
• Momentum shift following volatility exhaustion
The goal is not to predict the news, but to react to confirmed price behaviour after liquidity has been taken.
📌 Core Features
• FOMC Sweep Detection
Identifies aggressive wicks into prior highs/lows during news volatility
• EMA Reclaim Confirmation
Uses EMA13 to validate momentum shift after the sweep
• Market Structure Awareness
Filters reactions that fail to break structure to avoid false reversals
• Session-Aligned Logic
Designed around London → NY → FOMC release timing
• Clean Visuals
Minimal chart clutter for fast decision-making during volatile conditions
🧠 How to Use
Wait for FOMC release / Powell speech
Allow price to sweep previous liquidity (PDH / PDL / local extremes)
Observe reclaim of EMA13
Enter only after structure confirmation
Manage trade using EMA trailing or structure-based exits
⚠️ This is a reaction system, not a prediction tool.
📊 Best Use Cases
• XAUUSD (Gold)
• NASDAQ / US indices
• High-impact macro news events
• 5-min to 15-min timeframes
⚠️ Important Notes
• News volatility is extreme — risk management is essential
• Not designed for low-volatility or ranging markets
• Best combined with a clear trading plan and strict risk rules
📎 Disclaimer
This indicator is for educational purposes only and does not constitute financial advice. Trading during high-impact news events involves significant risk.
ICT Anchored Market Structures with Validation [LuxAlgo]The ICT Anchored Market Structures with Validation indicator is an advanced iteration of the original Pure-Price-Action-Structures tool, designed for price action traders.
It systematically tracks and validates key price action structures, distinguishing between true structural shifts/breaks and short-term sweeps to enhance trend and reversal analysis. The indicator automatically highlights structural points, confirms breakouts, identifies sweeps, and provides clear visual cues for short-term, intermediate-term, and long-term market structures.
A distinctive feature of this indicator is its exclusive reliance on price patterns. It does not depend on any user-defined input, ensuring that its analysis remains robust, objective, and uninfluenced by user bias, making it an effective tool for understanding market dynamics.
🔶 USAGE
Market structure is a cornerstone of price action analysis. This script automatically detects real-time market structures across short-term, intermediate-term, and long-term levels, simplifying trend analysis for traders. It assists in identifying both trend reversals and continuations with greater clarity.
Market structure shifts and breaks help traders identify changes in trend direction. A shift signals a potential reversal, often occurring when a swing high or low is breached, suggesting a transition in trend. A break, on the other hand, confirms the continuation of an established trend, reinforcing the current direction. Recognizing these shifts and breaks allows traders to anticipate price movement with greater accuracy.
It’s important to note that while a CHoCH may signal a potential trend reversal and a BoS suggests a continuation of the prevailing trend, neither guarantees a complete reversal or continuation. In some cases, CHoCH and BoS levels may act as liquidity zones or areas of consolidation rather than indicating a clear shift or continuation in market direction. The indicator’s validation component helps confirm whether the detected CHoCH and BoS are true breakouts or merely liquidity sweeps.
🔶 DETAILS
🔹 Market Structures
Market structures are derived from price action analysis, focusing on identifying key levels and patterns in the market. Swing point detection, a fundamental concept in ICT trading methodologies and teachings, plays a central role in this approach.
Swing points are automatically identified based exclusively on market movements, without requiring any user-defined input.
🔹 Utilizing Swing Points
Swing points are not identified in real-time as they form. Short-term swing points may appear with a delay of up to one bar, while the identification of intermediate and long-term swing points is entirely dependent on subsequent market movements. Importantly, this detection process is not influenced by any user-defined input, relying solely on pure price action. As a result, swing points are generally not intended for real-time trading scenarios.
Instead, traders often analyze historical swing points to understand market trends and identify potential entry and exit opportunities. By examining swing highs and lows, traders can:
Recognize Trends: Swing highs and lows provide insight into trend direction. Higher swing highs and higher swing lows signify an uptrend, while lower swing highs and lower swing lows indicate a downtrend.
Identify Support and Resistance Levels: Swing highs often act as resistance levels, referred to as Buyside Liquidity Levels in ICT terminology, while swing lows function as support levels, also known as Sellside Liquidity Levels. Traders can leverage these levels to plan their trade entries and exits.
Spot Reversal Patterns: Swing points can form key reversal patterns, such as double tops or bottoms, head and shoulders, and triangles. Recognizing these patterns can indicate potential trend reversals, enabling traders to adjust their strategies effectively.
Set Stop Loss and Take Profit Levels: In ICT teachings, swing levels represent price points with expected clusters of buy or sell orders. Traders can target these liquidity levels/pools for position accumulation or distribution, using swing points to define stop loss and take profit levels in their trades.
Overall, swing points provide valuable information about market dynamics and can assist traders in making more informed trading decisions.
🔹 Logic of Validation
The validation process in this script determines whether a detected market structure shift or break represents a confirmed breakout or a sweep.
The breakout is confirmed when the close price is significantly outside the deviation range of the last detected structural price. This deviation range is defined by the 17-period Average True Range (ATR), which creates a buffer around the detected market structure shift or break.
A sweep occurs when the price breaches the structural level within the deviation range but does not confirm a breakout. In this case, the label is updated to 'SWEEP.'
A visual box is created to represent the price range where the breakout or sweep occurs. If the validation process continues, the box is updated. This box visually highlights the price range involved in a sweep, helping traders identify liquidity events on the chart.
🔶 SETTINGS
The settings for Short-Term, Intermediate-Term, and Long-Term Structures are organized into groups, allowing users to customize swing points, market structures, and visual styles for each.
🔹 Structures
Swings and Size: Enables or disables the display of swing highs and lows, assigns icons to represent the structures, and adjusts the size of the icons.
Market Structures: Toggles the visibility of market structure lines.
Market Structure Validation: Enable or disable validation to distinguish true breakouts from liquidity sweeps.
Market Structure Labels: Displays or hides labels indicating the type of market structure.
Line Style and Width: Allows customization of the style and width of the lines representing market structures.
Swing and Line Colors: Provides options to adjust the colors of swing icons, market structure lines, and labels for better visualization.
🔶 RELATED SCRIPTS
Pure-Price-Action-Structures.
Market-Structures-(Intrabar).
Apex Edge – Wolfe Wave HunterApex Edge – Wolfe Wave Hunter
The modern Wolfe Wave, rebuilt for the algo era
This isn’t just another Wolfe Wave indicator. Classic Wolfe detection is rigid, outdated, and rarely tradable. Apex Edge – Wolfe Wave Hunter re-engineers the pattern into a modern, SMC-driven model that adapts to today’s liquidity-dominated markets. It’s not about drawing pretty shapes – it’s about extracting precision entries with asymmetric risk-to-reward potential.
🔎 What it does
Automatic Wolfe Wave Detection
Identifies bullish and bearish Wolfe Wave structures using pivot-based logic, symmetry filters, and slope tolerances.
Channel Glow Zones
Highlights the Wolfe channel and projects it forward into the future (bars are user-defined). This allows you to see the full potential of the trade before price even begins its move.
Stop Loss (SL) & Entry Arrow
At the completion of Wave 5, the algo prints a Stop Loss line and a tiny entry arrow (green for bullish, red for bearish). but the colours can be changed in user settings. This is the “execution point” — where the Wolfe setup becomes tradable.
Target Projection Lines
TP1 (EPA): Derived from the traditional 1–4 line projection.
TP2 (1.272 Fib): Optional secondary profit target.
TP3 (1.618 Fib): Optional extended target for large runners.
All TP lines extend into the future, so you can track them as price evolves.
Volume Confirmation (optional)
A relative volume filter ensures Wave 5 is formed with meaningful market participation before a setup is confirmed.
Alerts (ready out of the box)
Custom alerts can be fired whenever a bullish or bearish Wolfe Wave is confirmed. No need to babysit the charts — let the script notify you.
⚙️ Customisation & User Control
Every trader’s market and style is different. That’s why Wolfe Wave Hunter is fully customisable:
Arrow Colours & Size
Works on both light and dark charts. Choose your own bullish/bearish entry arrow colours for maximum visibility.
Tolerance Levels
Adjust symmetry and slope tolerance to refine how strict the channel rules are.
Tighter settings = fewer but cleaner zones.
Looser settings = more frequent setups, but with slightly lower structural quality.
Channel Glow Projection
Define how many bars forward the channel is drawn. This controls how far into the future your Wolfe zones are extended.
Stop Loss Line Length
Keep the SL visible without it extending infinitely across your chart.
Take Profit Line Colors
Each TP projection can be styled to your preference, allowing you to clearly separate TP1, TP2, and TP3.
This isn’t a one-size-fits-all tool. You can shape Wolfe detection logic to match the pairs, timeframes, and market conditions you trade most.
🚀 Why it’s different
Classic Wolfe waves are rare — this script adapts the model into something practical and tradeable in modern markets.
Liquidity-aligned — many setups align with structural sweeps of Wave 3 liquidity before driving into profit.
Entry built-in — most Wolfe scripts only draw the structure. Wolfe Wave Hunter gives you a precise entry point, SL, and projected TPs.
Backtest-friendly — you’ll quickly discover which assets respect Wolfe waves and which don’t, creating your own high-probability Wolfe watchlist.
⚠️ Limitations & Disclaimer
Not all markets respect Wolfe Waves. Some FX pairs, metals, and indices respect the structure beautifully; others do not. Backtest and create your own shortlist.
No guaranteed sweeps. Many entries occur after a liquidity sweep of Wave 3, but not all. The algo is designed to detect Wolfe completion, not enforce textbook liquidity rules.
Probabilistic, not predictive. Wolfe setups don’t win every time. Always use risk management.
High-RR focus. This is not a high-frequency tool. It’s designed for precision, asymmetric setups where risk is small and reward potential is large.
✅ The Bottom Line
Apex Edge – Wolfe Wave Hunter is a modern reimagination of the Wolfe Wave. It blends structural geometry, liquidity dynamics, and algo-driven execution into a single tool that:
Detects the pattern automatically
Provides SL, entry, and TP levels
Offers alerts for hands-off trading
Allows deep customisation for different markets
When it hits, it delivers outstanding risk-to-reward. Backtest, refine your tolerances, and build your watchlist of assets where Wolfe structures consistently pay.
This isn’t just Wolfe detection — it’s Wolfe trading, rebuilt for the modern trader.
Developer Notes - As always with the Apex Edge Brand, user feedback and recommendations will always be respected. Simply drop us a message with your comments and we will endeavour to address your needs in future version updates.
M2 Liqudity WaveGlobal Liquidity Wave Indicator (M2-Based)
The Global Liquidity Wave Indicator is designed to track and visualize the impact of global M2 liquidity on risk assets—especially those highly correlated to monetary expansion, like Bitcoin, MSTR, and other macro-sensitive equities.
Key features include:
Leading Signal: Historically leads Bitcoin price action by approximately 70 days, offering traders and analysts a forward-looking edge.
Wave-Based Projection: Visualizes a "probability cloud"—a smoothed band representing the most likely trajectory for Bitcoin based on changes in global liquidity.
Min/Max Offset Controls: Adjustable offsets let you define the range of lookahead windows to shape the wave and better capture liquidity-driven inflection points.
Explicit Offset Visualization: Option to manually specify an exact offset to fine-tune the overlay, ideal for testing hypotheses or aligning with macro narratives.
Macro Alignment: Particularly effective for assets with high sensitivity to global monetary policy and liquidity cycles.
This tool is not just a chart overlay—it's a lens into the liquidity engine behind the market, helping anticipate directional bias in advance of price moves.
How to use?
- Enable the indicator for BTCUSD.
- Set Offset Range Start and End to 70 and 115 days
- Set Specific Offset to 78 days (this can change so you'll need to play around)
FAQ
Why a global liquidity wave?
The global liquidity wave accounts for variability in how much global liquidity affects an underlying asset. Think of the Global Liquidity Wave as an area that tracks the most probable path of Bitcoin, MSTR, etc. based on the total global liquidity.
Why the offset?
Global liquidity takes time to make its way into assets such as #Bitcoin, Strategy, etc. and there can be many reasons for that. It's never a specific number of days of offset, which is why a global liquidity wave is helpful in tracking probable paths for highly correlated risk assets.
One Shot One Kill ICT [TradingFinder] Liquidity MMXM + CISD OTE🔵 Introduction
The One Shot One Kill trading setup is one of the most advanced methods in the field of Smart Money Concept (SMC) and ICT. Designed with a focus on concepts such as Liquidity Hunt, Discount Market, and Premium Market, this strategy emphasizes precise Price Action analysis and market structure shifts. It enables traders to identify key entry and exit points using a structured Trading Model.
The core process of this setup begins with a Liquidity Hunt. Initially, the price targets areas like the Previous Day High and Previous Day Low to absorb liquidity. Once the Change in State of Delivery(CISD)is broken, the market structure shifts, signaling readiness for trade entry. At this stage, Fibonacci retracement levels are drawn, and the trader enters a position as the price retraces to the 0.618 Fibonacci level.
Part of the Smart Money approach, this setup combines liquidity analysis with technical tools, creating an opportunity for traders to enter high-accuracy trades. By following this setup, traders can identify critical market moves and capitalize on reversal points effectively.
Bullish :
Bearish :
🔵 How to Use
The One Shot One Kill setup is a structured and advanced trading strategy based on Liquidity Hunt, Fibonacci retracement, and market structure shifts (CISD). With a focus on precise Price Action analysis, this setup helps traders identify key market movements and plan optimal trade entries and exits. It operates in two scenarios: Bullish and Bearish, each with distinct steps.
🟣 Bullish One Shot One Kill
In the Bullish scenario, the process starts with the price moving toward the Previous Day Low, where liquidity is absorbed. At this stage, retail sellers are trapped as they enter short trades at lower levels. Following this, the market reverses upward and breaks the CISD, signaling a shift in market structure toward bullishness.
Once this shift is identified, traders draw Fibonacci levels from the lowest point to the highest point of the move. When the price retraces to the 0.618 Fibonacci level, conditions for a buy position are met. The target for this trade is typically the Previous Day High or other significant liquidity zones where major buyers are positioned, offering a high probability of price reversal.
🟣 Bearish One Shot One Kill
In the Bearish scenario, the price initially moves toward the Previous Day High to absorb liquidity. Retail buyers are trapped as they enter long trades near the highs. After the liquidity hunt, the market reverses downward, breaking the CISD, which signals a bearish shift in market structure. Following this confirmation, Fibonacci levels are drawn from the highest point to the lowest point of the move.
When the price retraces to the 0.618 Fibonacci level, a sell position is initiated. The target for this trade is usually the Previous Day Low or other key liquidity zones where major sellers are active.
This setup provides a precise and logical framework for traders to identify market movements and enter trades at critical reversal points.
🔵 Settings
🟣 CISD Logical settings
Bar Back Check : Determining the return of candles to identify the CISD level.
CISD Level Validity : CISD level validity period based on the number of candles.
🟣 LIQUIDITY Logical settings
Swing period : You can set the swing detection period.
Max Swing Back Method : It is in two modes "All" and "Custom". If it is in "All" mode, it will check all swings, and if it is in "Custom" mode, it will check the swings to the extent you determine.
Max Swing Back : You can set the number of swings that will go back for checking.
🟣 CISD Display settings
Displaying or not displaying swings and setting the color of labels and lines.
🟣 LIQUIDITY Display settings
Displaying or not displaying swings and setting the color of labels and lines.
🔵 Conclusion
The One Shot One Kill setup is one of the most effective and well-structured trading strategies for identifying and capitalizing on key market movements. By incorporating concepts such as Liquidity Hunt, CISD, and Fibonacci retracement, this setup allows traders to enter trades with high precision at optimal points.
The strategy emphasizes detailed Price Action analysis and the identification of Smart Money behavior, helping traders to execute successful trades against the general market trend.
With a focus on identifying liquidity in the Previous Day High and Low and aligning it with Fibonacci retracement levels, this setup provides a robust framework for entering both bullish and bearish trades.
The combination of liquidity analysis and Fibonacci retracement at the 0.618 level enables traders to minimize risk and exploit major market moves effectively.
Ultimately, success with the One Shot One Kill setup requires practice, patience, and strict adherence to its rules. By mastering its concepts and focusing on high-probability setups, traders can enhance their decision-making skills and build a sustainable and professional trading approach.
QuantFrame | FractalystWhat’s the purpose of this indicator?
The purpose of QuantFrame is to provide traders with a systematic approach to analyzing market structure, eliminating subjectivity, and enhancing decision-making. By clearly identifying and labeling structural breaks, QuantFrame helps traders:
1. Refine Market Analysis: Transition from discretionary market observation to a structured framework.
2. Identify Key Levels: Highlight important liquidity and invalidation zones for potential entries, exits, and risk management.
3. Streamline Multi-Timeframe Analysis: Track market trends and structural changes across different timeframes seamlessly.
4. Enhance Consistency: Reduce guesswork by following a rule-based methodology for identifying structural breaks.
How Does This Indicator Identify Market Structure?
1. Swing Detection
• The indicator identifies key swing points on the chart. These are local highs or lows where the price reverses direction, forming the foundation of market structure.
2. Structural Break Validation
• A structural break is flagged when a candle closes above a previous swing high (bullish) or below a previous swing low (bearish).
• Break Confirmation Process:
To confirm the break, the indicator applies the following rules:
• Valid Swing Preceding the Break: There must be at least one valid swing point before the break.
3. Numeric Labeling
• Each confirmed structural break is assigned a unique numeric ID starting from 1.
• This helps traders track breaks sequentially and analyze how the market structure evolves over time.
4. Liquidity and Invalidation Zones
• For every confirmed structural break, the indicator highlights two critical zones:
1. Liquidity Zone (LIQ): Represents the structural liquidity level.
2. Invalidation Zone (INV): Acts as Invalidation point if the structure fails to hold.
What do the extremities show us on the charts?
When using QuantFrame for market structure analysis, the extremities—Liquidity Level (LIQ) and Invalidation Level (INV)—serve as critical reference points for understanding price behavior and making informed trading decisions.
Here's a detailed explanation of what these extremities represent and how they function:
Liquidity Level (LIQ)
Definition: The Liquidity Level is a key price zone where the market is likely to retest, consolidate, or seek liquidity. It represents areas where orders are concentrated, making it a high-probability reaction zone.
Purpose: Traders use this level to anticipate potential pullbacks or continuation patterns. It helps in identifying areas where price may pause or reverse temporarily due to the presence of significant liquidity.
Key Insight: If a candle closes above or below the LIQ, it results in another break of structure (BOS) in the same direction. This indicates that price is continuing its trend and has successfully absorbed liquidity at that level.
Invalidation Level (INV)
Definition: The Invalidation Level marks the threshold that, if breached, signifies a structural shift in the market. It acts as a critical point where the current market bias becomes invalid.
Purpose: This level is often used as a stop-loss or re-evaluation point for trading strategies. It ensures that traders have a clear boundary for risk management.
Key Insight: If a candle closes above or below the INV, it signals a shift in market structure:
A closure above the INV in a bearish trend indicates a shift from bearish to bullish bias.
A closure below the INV in a bullish trend indicates a shift from bullish to bearish bias.
What does the top table display?
The top table in QuantFrame serves as a multi-timeframe trend overview. Here’s what it provides:
1. Numeric Break IDs Across Multiple Timeframes:
• Each numeric break corresponds to a confirmed structural break on a specific timeframe, helping traders track the most recent breaks systematically.
2. Trend Direction via Text Color:
• The color of the text reflects the current trend direction:
• Blue indicates a bullish structure.
• Red signifies a bearish structure.
3. Higher Timeframe Insights Without Manual Switching:
• The table eliminates the need to switch between timeframes by presenting a consolidated view of the market trend across multiple timeframes, saving time and improving decision-making.
What is the Multi-Timeframe Trend Score (MTTS)?
MTTS is a score that quantifies trend strength and direction across multiple timeframes.
How does MTTS work?
1. Break Detection:
• Analyzes bullish and bearish structural breaks on each timeframe.
2. Trend Scoring:
• Scores each timeframe based on the frequency and quality of bullish/bearish breaks.
3. MTTS Calculation:
• Averages the scores across all timeframes to produce a unified trend strength value.
How is MTTS interpreted?
• ⬆ (Above 50): Indicates an overall bullish trend.
• ⬇ (Below 50): Suggests an overall bearish trend.
• ⇅ (Exactly 50): Represents a neutral or balanced market structure.
How to Use QuantFrame?
1. Implement a Systematic Market Structure Framework:
• Use QuantFrame to analyze market structure objectively by identifying key structural breaks and marking liquidity (LIQ) and invalidation (INV) zones.
• This eliminates guesswork and provides a clear framework for understanding market movements.
2. Leverage MTTS for Directional Bias:
• Refer to the MTTS table to identify the multi-timeframe directional bias, giving you the broader market context.
• Align your trading decisions with the overall trend or structure to improve accuracy and consistency.
3. Apply Your Preferred Entry Model:
• Once the market context is clear, use your preferred entry model to capitalize on the identified structure and trend.
• Manage trades dynamically as price delivers, using the provided liquidity and invalidation zones for risk management.
What Makes QuantFrame Original?
1. Objective Market Structure Analysis:
• Unlike subjective methods, QuantFrame uses a rule-based approach to identify structural breaks, ensuring consistency and reducing emotional decision-making.
2. Multi-Timeframe Integration:
• The MTTS table consolidates trend data across multiple timeframes, offering a bird’s-eye view of market trends without the need to switch charts manually.
• This unique feature allows traders to align strategies with higher-timeframe trends for more informed decision-making.
3. Liquidity and Invalidation Zones:
• Automatically marks Liquidity (LIQ) and Invalidation (INV) zones for every structural break, providing actionable levels for entries, exits, and risk management.
• These zones help traders define their risk-reward setups with precision.
4. Dynamic Trend Scoring (MTTS):
• The Multi-Timeframe Trend Score (MTTS) quantifies trend strength and direction across selected timeframes, offering a single, consolidated metric for market sentiment.
• This score is visualized with intuitive symbols (⬆, ⬇, ⇅) for quick decision-making.
5. Numeric Labeling of Breaks:
• Each structural break is assigned a unique numeric ID, making it easy to track, analyze, and backtest specific market scenarios.
6. Systematic Yet Flexible:
• While it provides a structured framework for market analysis, QuantFrame seamlessly integrates with any trading style. Traders can use it alongside their preferred entry models, adapting it to their unique strategies.
7. Enhanced Market Context:
• By combining structural insights with directional bias (via MTTS), the indicator equips traders with a complete market context, enabling them to make better-informed decisions.
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.
Follow Through Day (FTD) + Sweep [TrendX_]The Follow Through Day (FTD) + Sweep indicator is a Trend-following tool mixing William O'Neil's original FTD concept and Liquidity concept. This indicator helps you identify potential subsequent bullish trends with greater precision by combining volume analysis, price action, and liquidity concepts.
💎 FEATURES
Follow Through Day Candle (FTD Candle)
The FTD, pioneered by William O'Neil, serves as a reliable signal for identifying the beginning of new bull markets. It's particularly valuable because it combines multiple market factors - price action, volume, and timing - to confirm genuine market reversals rather than temporary bounces.
The power of the FTD lies in its ability to distinguish between ordinary market fluctuations and significant trend changes. By requiring specific criteria to be met across multiple sessions, it helps filter out false signals and identifies high-probability reversal points where institutional investors are likely beginning to accumulate positions.
Sweep Area
The Sweep area feature enhances the traditional FTD concept by incorporating modern liquidity analysis. This overlay identifies zones where large market participants are likely to trigger stop losses before continuing the trend. These areas often represent optimal entry points for traders looking to join the new uptrend with reduced risk.
🔎 BREAKDOWN
FTD Candle
The FTD formation process occurs in two distinct phases: Setup and Completion.
Setup Phase
Strong Market Decline
The market must first experience a significant downtrend
This selling pressure helps clear out weak hands and creates oversold conditions
The decline creates the potential energy for a powerful reversal
First Recovery Session
Marks the initial sign of buying pressure emerging
Often characterized by a strong reversal candle
Represents the first indication that selling pressure may be exhausting
Recovery Confirmation
The second and third days must maintain prices above the new pivot low
This consolidation period helps confirm the validity of the initial bounce
Shows that sellers are no longer in control of price action
Completion Phase:
Supply Test Session
Low volume indicates diminishing selling pressure
Price remains above the pivot low
Creates the foundation for institutional buyers to begin accumulating
Breakout Day
Price increase exceeds average profit of bullish candles
Volume increases by at least 15% compared to previous session
Shows strong institutional commitment to the new uptrend
Timing Window
Must occur between the 4th and 8th candle after First Recovery Session
This specific timing helps confirm the sustainability of the reversal
Based on O'Neil's research of historical market bottoms
FTD Sweep
The Post-FTD Phase introduces the Sweep concept, which is crucial for understanding how large market participants operate. This feature leverages the liquidity concept because institutional traders often need to trigger stop losses to accumulate larger positions at better prices. This helps:
Create liquidity pools for large position entries
Shake out weak hands before continuing the trend
Test the strength of the new trend by absorbing selling pressure
⚙️ USAGE
Sweep + TP & SL Strategy
Example: BTCUSDT (1D) - Replay back to 9th November 2024
After an FTD candle forms, traders can adopt a systematic approach to enhance their trading strategy. First, they should determine the swing range and convert the post-FTD zone into concrete stop loss and take profit levels, which are based on the price action during the FTD formation. Next, traders should wait for a sweep formation, as this indicates that institutional players are accumulating positions. A quick price rejection from the sweep level should be observed before executing an entry.
The reasoning behind this strategy is rooted in market microstructure. By waiting for the sweep, traders position themselves alongside institutional players who need to build large positions without causing adverse price movement. The sweep creates the liquidity they need, and the subsequent move often represents the true trend continuation.
DISCLAIMER
This indicator is not financial advice, it can only help traders make better decisions. There are many factors and uncertainties that can affect the outcome of any endeavor, and no one can guarantee or predict with certainty what will occur. Therefore, one should always exercise caution and judgment when making decisions based on past performance.
Hourly Trading System (Zeiierman)█ Overview
The Hourly Trading System (Zeiierman) is designed to enhance your trading by highlighting critical price levels and trends on an hourly basis. This indicator plots the open prices of hourly and 4-hour candles, visualizes retests, displays average price lines, and overlays higher timeframe candlesticks. It is particularly beneficial for intraday traders seeking to capitalize on short-term price movements and volume patterns.
█ How It Works
This indicator works by plotting significant price levels and zones based on hourly and 4-hour candle opens. It also includes functionalities for identifying retests of these levels, calculating and displaying average prices, and showing high and low labels for each hour.
█ Timeframe
The Hourly Trading System is designed to be used on the 1-minute or 5-minute timeframe. This system is tailored for intraday trading, allowing traders to find optimal entries around hourly opening levels and providing an easy method to identify the hourly trend. It works effectively on any market.
█ How to Use
Trend Analysis
Quickly gauge where the current price stands relative to key hourly and 4-hour levels. The plotted lines and zones serve as potential support and resistance areas, helping traders identify crucial points for entry or exit.
Utilize the 1-hour average and higher timeframe candles to understand the overall market trend. Aligning intraday strategies with larger trends can enhance trading decisions.
Use the bar coloring to quickly gauge the 1-hour trend on a lower timeframe. The bar colors indicate whether the hourly trend is bullish (green) or bearish (red), helping traders make quicker decisions in alignment with the overall trend.
Retest Identification
Enable retest signals to see where the price retested the hourly open levels. These retest points often signal strong price reactions, offering opportunities for trades based on support/resistance flips.
One effective strategy to incorporate is looking for price flips when a new hour starts. This approach involves monitoring price action at the beginning of each hour. If the price breaks and retests the hourly open level with strong momentum, it could indicate a potential trend reversal or continuation. This strategy is effective in volatile markets where price movements are significant at the start of each new hour.
Liquidity Sweep Strategy
Another common and effective strategy is the liquidity sweep. This involves identifying key levels where liquidity is likely to accumulate, such as previous hour highs and lows, and observing how the price interacts with these price levels. When the price sweeps through these levels, triggering stop-loss orders or pending orders, it often results in a sharp price movement followed by a reversal. Traders can capitalize on these movements by entering trades in the direction of the reversal once the liquidity sweep has occurred.
Equal Highs and Lows Strategy
The Equal Highs and Lows strategy leverages the concept of identifying levels where the price forms multiple highs or lows at the same level over different hourly periods. These equal highs and lows often indicate strong support or resistance levels where liquidity is accumulated. When the price approaches these levels, it is likely to trigger stop-loss orders and lead to significant price movements. Traders can look for breakouts or reversals around these levels to enter trades with higher probability setups.
█ Settings
Zone Width: Specifies the width of the zone around the 1-Hour Open as a percentage. Adjust this to widen or narrow the zone.
Show Retests: Enables or disables the display of retest markers. Retest markers show where the price has retested the 1-Hour Open line.
Number of Retests: Sets the number of retests to display. Adjust this to see more or fewer retest markers.
Volume Filter: Enables or disables the volume filter for retests. Use this to highlight retests with significant volume.
Volume Filter Length: Sets the length of the volume filter, smoothing the volume data to reduce noise.
1-Hour Average Line: Enables or disables the 1-hour average price line. This line shows the average price over the past hour.
Hourly High & Low Labels: Enables or disables the display of hourly high and low labels, marking the highest and lowest prices within each hour.
Candlesticks: Enables or disables the display of candlesticks on the chart, providing a detailed view of price action.
Bar Color: Enables or disables bar coloring based on price direction, with up bars in green and down bars in red.
Timeframe: Sets the timeframe for higher timeframe candles. Adjust this to match the period you want to analyze.
Number of Candles: Sets the number of higher timeframe candles to display. Increase this to see more candles on the chart.
Location: Sets the location for higher timeframe candles, allowing you to position them left or right on the chart.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Global Liquidity Index (Candles)The Global Liquidity Index (Candles) provides a comprehensive overview of major central bank balance sheets worldwide, presenting values converted to USD for consistency and comparability, following relevant forex rates. This indicator, based on the code developed by user ingeforberg , incorporates essential US accounts including the Treasury General Account (TGA) and Reverse Repurchase Agreements (RRP), subtracted from the Federal Reserve's balance sheet to offer a nuanced perspective on US liquidity. Users can tailor their analysis by selectively enabling or disabling specific central banks and special accounts according to their preferences. The index exclusively includes central banks abstaining from currency pegging and with reliable data accessible since late 2007, ensuring a robust aggregated liquidity model.
The calculation of the Global Liquidity Index involves subtracting the Treasury General Account (TGA) and Reverse Repurchase Agreements (RRP) from the Federal Reserve System (FED) and adding the balance sheets of major central banks worldwide: the European Central Bank (ECB), the People's Bank of China (PBC), the Bank of Japan (BOJ), the Bank of England (BOE), the Bank of Canada (BOC), the Reserve Bank of Australia (RBA), the Reserve Bank of India (RBI), the Swiss National Bank (SNB), the Central Bank of the Russian Federation (CBR), the Central Bank of Brazil (BCB), the Bank of Korea (BOK), the Reserve Bank of New Zealand (RBNZ), Sweden's Central Bank (Riksbank), and the Central Bank of Malaysia (BNM).
This tool proves invaluable for individuals seeking a consolidated perspective on global liquidity to interpret macroeconomic trends. Analyzing these balance sheets enables users to discern policy trajectories and assess the global economic landscape, providing insights into asset pricing and assisting investors in making well-informed capital allocation decisions. Historically, assets perceived as riskier, such as small caps and cryptocurrencies, have tended to perform favorably during periods of escalating liquidity. Thus, investors may exercise caution regarding additional risk exposure unless a sustained upward trend in global liquidity is evident.
Main differences between the original and updated indicators:
The "Global Liquidity Index (Candles)" script, compared to the original "Global Liquidity Index" script, offers a more detailed and visually rich representation of liquidity data.
"Global Liquidity Index (Candles)" employs candlestick visualization to represent liquidity data. Each candlestick encapsulates open, high, low, and close prices over a given period. This format provides granular insights into liquidity fluctuations, facilitating a more nuanced analysis.
By using candlesticks, the script offers traders detailed information about liquidity dynamics. They can analyze the patterns formed by candlesticks to discern trends, reversals, and market sentiment shifts, aiding in making informed trading decisions.
