Smart Money Setup 06 [TradingFinder] Liquidity Sweeps + OB Swing🔵 Introduction
Smart Money, managed by large investors, injects significant capital into financial markets by entering real capital markets.
Capital entering the market by this group of individuals is called smart money. Traders can profit from financial markets by following such individuals.
Therefore, smart money can be considered one of the effective methods for analyzing financial markets.
Sometimes, before a market movement, fluctuation movements that create price movement cause many traders' "Stop Loss" to be triggered. These movements are created in various patterns.
One of these patterns is similar to an "Expanding Triangle", which touches the stop loss of individuals who have placed their stop loss in the cash area in the form of 5 consecutive openings.
To better understand this setup, pay attention to the images below.
Bullish Setup Details :
Bearish Setup Details :
🔵 How to Use
After adding the indicator to the chart, wait for trading opportunities to appear. By changing the "Time Frame" and "Pivot Period", you can see different trading positions.
In general, the smaller the "Time Frame" and "Pivot Period", the more likely trading opportunities will appear.
Bullish Setup Details on Chart :
Bearish Setup Details on Chart :
🔵 Settings
You have access to "Pivot Period", "Order Block Refine", and "Refine Mode" through settings.
By changing the "Pivot Period", you can change the range of zigzag that identifies the setup.
Through "Order Block Refine", you can specify whether you want to refine the width of the order blocks or not. It is set to "On" by default.
Through "Refine Mode", you can specify how to improve order blocks.
If you are "risk-averse", you should set it to "Defensive" mode because in this mode, the width of the order blocks decreases, the number of your trades decreases, and the "reward-to-risk ratio "increases.
If you are on the opposite side and are "risk-taker", you can set it to "Aggressive" mode. In this mode, the width of the order blocks increases, and the likelihood of losing positions decreases.
Search in scripts for "liquidity"
Swing Trade IndicatorThis is a Swing Trade Indicator that combines several technical indicators to analyze market conditions and generate trade signals. I've included two tables that provide real-time information to help you analyze the market and track trades: the Market Status Table and the Trade Tracking Table. These tables are overlaid on the TradingView chart and are customizable in terms of position and visibility.
Simple Moving Averages (SMAs):
Determines trend direction (e.g., bullish if fastMA > slowMA).
Calculates the average closing price over a set period:
fastMA: 21-period SMA (short-term trend).
slowMA: 50-period SMA (medium-term trend).
ultraSlowMA: 200-period SMA (long-term trend).
How:
ta.sma(close, fastLength) computes the SMA of the closing price over fastLength bars (similarly for slowLength and ultraSlowLength).
Volume Analysis:
Identifies potential liquidity spikes.
Measures trading volume to detect high activity.
Average volume over liquidityPeriod (20 bars).
Standard deviation of volume to set a dynamic threshold.
How:
avgVolume = ta.sma(volume, liquidityPeriod): Average volume.
volumeStdDev = ta.stdev(volume, liquidityPeriod): Volatility of volume.
highVolume = volume > avgVolume + volumeStdDev * volumeThresholdMultiplier: Flags high volume if it exceeds the average plus a multiplier (default 1.0) times the standard deviation.
Relative Strength Index (RSI):
Filters entries to avoid overextended markets.
Measures momentum and overbought/oversold conditions.
14-period RSI with thresholds at 60 (overbought) and 40 (oversold).
How:
rsiValue = ta.rsi(close, rsiLength) calculates RSI based on price changes over 14 bars.
Average Directional Index (ADX):
Gauges whether the trend is strong enough to trade.
Assesses trend strength.
14-period ADX.
How:
Calculates True Range (tr), Plus Directional Movement (plusDM), and Minus Directional Movement (minusDM).
Smooths these with ta.rma (Running Moving Average) over adxLength (14).
Computes plusDI and minusDI (directional indicators), then dx (difference), and finally adxValue = ta.rma(dx, adxLength) for trend strength.
Classifies as "Strong" (≥40), "Moderate" (≥20), or "Weak" (<20).
Moving Average Convergence Divergence (MACD) (Optional):
Optional filter for entry conditions if useMacdFilter is enabled.
Tracks momentum and trend changes.
Fast EMA (12), Slow EMA (26), Signal Line (9).
How:
= ta.macd(close, macdFastLength, macdSlowLength, macdSignalLength) computes the MACD components.
macdBullish = macdLine > signalLine: Bullish signal.
macdBearish = macdLine < signalLine: Bearish signal.
Liquidity Zones:
Confirms entries near key levels and suggests next trade setups.
Identifies support and resistance levels based on recent price extremes.
Dynamic levels over 20 bars (if useDynamicLevels is true).
How:
highLiquidityLevel1 = ta.highest(high, 20): Highest high in last 20 bars.
highLiquidityLevel2 = ta.highest(high , 20): Highest high from 20 to 40 bars ago.
highLiquidityLevel3 = ta.lowest(low, 20): Lowest low in last 20 bars.
highLiquidityLevel4 = ta.lowest(low , 20): Lowest low from 20 to 40 bars ago.
Upper and lower zones are derived (upperLevel, lowerLevel), with a midpoint between them.
How It Calculates Entries and Exits
Long Entry:
Basic Conditions (longEntry):
close > fastMA: Price is above the 21-period SMA.
fastMA > slowMA: Short-term trend is above medium-term trend (bullish).
rsiValue < rsiOverbought: RSI below 60 (not overbought).
(not useMacdFilter or macdBullish): If MACD filter is off, ignore it; if on, MACD must be bullish.
Confirmed Entry (confirmedLongEntry):
longEntry is true.
close >= highLiquidityLevel3 * 0.95 and close <= highLiquidityLevel3 * 1.05: Price is within 5% of the lower liquidity level (support).
Action: Sets currentPosition = 'long', records entry price and bar, plots a green triangle below the bar.
Short Entry:
Basic Conditions (shortEntry):
close < fastMA: Price is below the 21-period SMA.
fastMA < slowMA: Short-term trend is below medium-term trend (bearish).
rsiValue > rsiOversold: RSI above 40 (not oversold).
(not useMacdFilter or macdBearish): If MACD filter is off, ignore it; if on, MACD must be bearish.
Confirmed Entry (confirmedShortEntry):
shortEntry is true.
close <= highLiquidityLevel1 * 1.05 and close >= highLiquidityLevel1 * 0.95: Price is within 5% of the upper liquidity level (resistance).
Action: Sets currentPosition = 'short', records entry price and bar, plots a red triangle above the bar.
Exit Conditions
Note: The exit logic is defined but commented out in the script (//longExit and //shortExit), meaning it doesn’t automatically exit positions. It calculates stop-loss and take-profit levels for manual use:
Long Exit (if uncommented):
close < stopLossLevelLong: Price falls below stop-loss (entry price × (1 - 1.5%)).
close > takeProfitLevelLong: Price exceeds take-profit (entry price × (1 + 1.5% × 2.0)).
Short Exit (if uncommented):
close > stopLossLevelShort: Price rises above stop-loss (entry price × (1 + 1.5%)).
close < takeProfitLevelShort: Price falls below take-profit (entry price × (1 - 1.5% × 2.0)).
Suggested Levels: The script provides suggestedLongSL, suggestedLongTP, suggestedShortSL, and suggestedShortTP in the Market Status Table, based on liquidity levels rather than entry price, for manual exits.
Users Can Edit Settings:
Market Status Table Position: Dropdown (e.g., "top_right" to "bottom_left").
Trade Tracking Table Position: Dropdown (e.g., "bottom_right" to "middle_center").
Visibility Toggles (checkboxes):
Show Tables: Enable/disable tables (default: true).
Show Liquidity Zones: Not plotted but affects logic (default: true).
Show Entry Points: Show/hide entry triangles (default: true).
Use Dynamic Levels: Enable/disable liquidity zones (default: true).
Use MACD for Entry Filter: Add MACD to entry conditions (default: false).
Show MACD on Chart: Not implemented but reserved (default: false).
Indicator Periods:
Fast MA Length: Integer (default: 21, e.g., change to 10).
Slow MA Length: Integer (default: 50, e.g., change to 30).
Ultra Slow MA Length: Integer (default: 200, e.g., change to 100).
Liquidity Detection Period: Integer (default: 20, e.g., change to 10).
RSI Length: Integer (default: 14, e.g., change to 7).
ADX Length: Integer (default: 14, e.g., change to 20).
MACD Fast/Slow/Signal Length: Integers (default: 12/26/9, e.g., 9/21/5).
Thresholds:
Volume Threshold Multiplier: Float (default: 1.0, e.g., 1.5 for stricter high volume).
RSI Overbought: Integer (default: 60, e.g., 70).
RSI Oversold: Integer (default: 40, e.g., 30).
Stop Loss %: Float (default: 1.5, e.g., 2.0, range 0.1-10).
Take Profit Ratio: Float (default: 2.0, e.g., 3.0, range 1.0-5.0).
Liquidity Threshold (%): Float (default: 2.0, e.g., 1.5, range 0.5-5.0).
SMC Fake Zones + InsideBarThis indicator is useful for whom trade with "Smart Money Concept (SMC)" strategy.
It helps SMD traders to identify fake or weak zones in the chart, So they can avoid taking position in this zones.
This indicator marks "Asia session" as well as "London and New York's Lunch Time (one hour before London and NY session starts)" zones.
It also marks Inside Bar candles which SMC trades consider as order flow. You can mark every Inside Bar or only those with opposite color via setting options.
*** As we know in SMC rules
1- Supply and Demand zones in "Asia session and Lunch Times" are fake zones for SMC trading and price will engulf them in most of times.
2- "Asia session high and low" has huge liquidity and usually price sweep that in London session.
This indicator will helps traders to visually identify those Fake zones and Asia session liquidity.
* You can change session times based on your time zone in settings.
* You can set options to show all Inside Bars or only with Opposite color in settings.
OrderFlow [Probabilities] | FractalystWhat's the indicator's purpose and functionality?
The indicator is designed to incorporate probabilities with buyside and sellside liquidity, as well as premium and discount ranges within the market. It also provides traders with a multi-timeframe functionality for observing liquidity levels and probabilities across two timeframes without the need to manually switch between them.
These levels are often used in smart money trading concepts for identifying key areas of interest, such as potential reversal points, areas of accumulation or distribution, and zones of high liquidity.
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What's the purpose of these levels? What are the underlying calculations?
1. Understanding Swing highs and Swing Lows
Swing High: A Swing High is formed when there is a high with 2 lower highs to the left and right.
Swing Low: A Swing Low is formed when there is a low with 2 higher lows to the left and right.
2. Understanding the purpose and the underlying calculations behind Buyside , Sellside and Equilibrium levels.
3. Identifying Discount and Premium Zones.
4. Importance of Risk-Reward in Premium and Discount Ranges
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How does the script calculate probabilities?
The script calculates the probability of each liquidity level individually. Here's the breakdown:
1. Upon the formation of a new range, the script waits for the price to reach and tap into equilibrium or the 50% level. Status: "⏸" - Inactive
2. Once equilibrium is tapped into, the equilibrium 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.
5. Finally, the number of successful occurrences for each side is divided by the overall count individually to calculate the range probabilities.
Note: The calculations are performed independently for each directional range. A range is considered bearish if the previous breakout was through a sellside liquidity. Conversely, a range is considered bullish if the most recent breakout was through a buyside liquidity.
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What does the multi-timeframe functionality offer?
Enabling and selecting a higher timeframe in the indicator's user-input settings allows you to access not only the current range information but also the liquidity sides, status, price levels, and probabilities of a higher timeframe without needing to switch between timeframes and mark up the levels manually.
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What are the multi-timeframe underlying calculations?
The script uses the same calculations (mentioned above) and requests the data such as price levels, bar time, probabilities and booleans from the user-input timeframe.
Non-repainting Security Function with Lookahead ON
//Function to fetch data for a given timeframe
getHTFData(timeframe_,exp_) =>
request.security(syminfo.tickerid, timeframe_,exp_ ,lookahead = barmerge.lookahead_on)
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How to use the indicator?
1. Add the indicator to your TradingView chart.
2. Choose the pair you want to analyze/trade.
3. Enable the HTF in user-input settings and choose a timeframe as for your higher timeframe bias.
4. (Important) : Ensure that the probabilities on both timeframes are aligned in one direction. If not, switch between timeframes until you find a pair of timeframes that are in line with each other and have higher probabilities on one liquidity side.
For Swing traders:
Use Hourly timeframes (1H/2H/4H/8H/12H) as your current timeframe and 1D/3D/1W/2W for your higher timeframe (HTF).
Entry: Hourly Equilibrium level. (Limit order)
Stoploss: Place it on the side where the probability is lower than 50%.
Break-even level/TP1: Hourly breakout of the liquidity.
TP2: Target the Higher Timeframe (HTF) liquidity level where the probability is higher than 50%.
2H/1D COINBASE:BTCUSD
For Day traders:
Use minutely timeframes (5m/15m/30m) as your current timeframe and 1H/2H/4H/8H/12H for your higher timeframe (HTF).
Entry: Minutely Equilibrium level. (Limit order)
Stoploss: Place it on the side where the probability is lower than 50%.
Break-even level/TP1: Minutely breakout of the liquidity.
TP2: Target the Higher Timeframe (HTF) liquidity level where the probability is higher than 50%.
1H/5m COINBASE:BTCUSD
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User-input settings and customizations
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What makes this indicator original?
1. Real-time calculation of probabilities directly on your charts.
2. Multi-timeframe functionality, enabling effortless observation of liquidity levels and probabilities across two timeframes.
3. Status label for clear identification of whether price has reached equilibrium.
4. All levels are updated only upon candle closure above or below liquidity levels, ensuring it remains a non-repainting indicator.
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Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer.
Crypto USD LiquidityThe "Crypto USD Liquidity " indicator is designed to offer a comprehensive analysis of liquidity dynamics within the cryptocurrency market, specifically focusing on various stablecoins. This versatile tool allows users to tailor their analysis by adjusting key parameters such as the Rate of Change (ROC) length and the smoothing rate.
The indicator incorporates a user-friendly interface with options to selectively display the supply data for major stablecoins, including USDT, BUSD, USDC, DAI, and TUSD . Users can toggle these options to observe and compare the liquidity trends of different stablecoin assets.
The total liquidity is computed as the summation of the selected stablecoin supplies, providing a holistic view of the overall crypto market liquidity. The Rate of Change (ROC) and its smoothing are then applied to the aggregated liquidity data. This process helps users identify trends and potential turning points in the liquidity landscape.
The visual representation on the chart includes a color-coded display: positive changing ROC values are shaded in green, indicating potential increases in liquidity, while negative values are shaded in red, suggesting potential decreases. This color scheme enhances the user's ability to quickly interpret the changing dynamics of stablecoin liquidity.
Moreover, the script includes a Zero Line for reference and overlays the raw ROC values for additional insight. The resulting chart not only serves as a powerful analytical tool for traders and investors but also contributes to a deeper understanding of the nuanced movements within the broader cryptocurrency market.
In summary, the "Crypto USD Liquidity" Pine Script indicator empowers users with a customizable and visually informative tool for analyzing and interpreting the complex dynamics of stablecoin liquidity, facilitating more informed decision-making in the realm of cryptocurrency trading and investment.
SMC Liquidity & Order Blocks🔹 1. Moving Averages for Trend Confirmation
Uses Exponential Moving Averages (EMA) to determine trend direction.
9-period EMA (blue) and 15-period EMA (red) are plotted.
🔹 2. Liquidity Zones (Swing Highs & Lows)
Identifies liquidity zones where price is likely to react.
Buy-Side Liquidity: Highest high over 20 periods (Green line).
Sell-Side Liquidity: Lowest low over 20 periods (Red line).
🔹 3. Order Block Detection
Detects bullish and bearish order blocks (key price zones of institutional activity).
Bullish Order Block (OB): Formed when the highest close over 5 bars exceeds the highest high.
Bearish Order Block (OB): Formed when the lowest close over 5 bars is lower than the lowest low.
Plotted using green (up-triangle) for bullish OB and red (down-triangle) for bearish OB.
🔹 4. Fair Value Gaps (FVG)
Detects price inefficiencies (gaps between candles).
FVG Up: When a candle's high is lower than a candle two bars ahead.
FVG Down: When a candle's low is higher than a candle two bars ahead.
Plotted using blue circles (FVG Up) and orange circles (FVG Down).
ICSM (Impulse-Correction & SCOB Mapper) [WinWorld]DESCRIPTION
ICSM (Impulse-Correction SCOB Mapper) is the indicator that analyzes the price movement and identifies valid impulses, corrections and SCOBs. It is a powerful tool that can be used with any type of technical analysis because it's flexible, informative, easy to use and it does substantially improve trader's awareness of the most liquid zones of interest.
SETTINGS
General | Visuals
Colour theme — defines the colour theme of the ICSM.
SCOB | Visuals
Show SCOB — enables/disables SCOB;
Mark SCOB with — represents a list of style options for SCOB representation;
SCOB colour — defines the colour of the SCOB;
ICM | Visuals
Show ICM lines — enables/disables ICM (Impulse-Correction Mapper) lines;
Show IC trend — enables/disables visualization of impulse-correction trend via coloured divider at the bottom of the chart;
Line colour — defines the colour of the ICM lines;
Line style — defines the style of the ICM lines;
Alerts
ICM — enables/disables alert for breaking ICM lines;
SCOB — enables/disables alert for SCOB creation;
ICM+SCOB — enables/disables alert for SCOB occurance at the end of the single impulse/correction, which grabs ICM line's liquidity.
ICM+SCOB (same candle) — enables/disables alert for SCOB occurance at the candle, which grabs ICM line's liquidity.
IMPORTANT CONCEPTS
In order to fully understand what ICSM can do, let's do a quick overview of the most important concepts that this indicator is built on.
By ICM we mean the liquidity grabbing of Impulse-Correction Mapper's lines (ICM lines; represented as dashed horizontal lines on the chart ). Saying shortly, liquidity grabs of ICM lines posses great opportunities for finding great entries.
SCOB (Single Candle Order Block) builds up by 3 simple rules:
Previous candle's liquidity is grabbed;
Current candle closes inside previous candle;
Imbalance occurs on the next candle.
SCOB is a quite useful zone of interest, from which the price usually reverses. You can also use SCOB as POI* on HTF** or as entry zone on LTF***.
* POI — Point Of Interest
* HTF — Higher TimeFrame
* LTF — Lower TimeFrame
"ICM+SCOB" is a short name that we use for event, at which price first grabs the liquidity from ICM line and then creates a SCOB at the same impulse/correction movement ( on the same ICM line, that does the liquidity grab ). Usually the SCOB that occurs after this event represents a highly liquid zone of interest , which should be considered when choosing entry level.
"ICM+SCOB (same candle)" is basically the same as "ICM+SCOB" event but with one major difference — the candle, which grabs the liquidity of ICM line, is also the candle at which the SCOB occurs, making such SCOB an even better zone of interest than a regular SCOB from ICM+SCOB event.
BIGGEST ADVANTAGES
ICSM precisely identifies impulses and corrections. Huge load of indicators on the TradingView does only show the simplest zones of interests, while ICSM uses our team's signature algorithms to precisely identify true impulses and corrections in the market, allowing traders to see both local and global price direction better and at the same time providing traders with the most liquid zones of interest;
ICSM shows points of interest and liquidity. The indicator identifies the nearest points of interest and zones, where the liquidity is concentrated, allowing you to find great entry and exit points for your trades;
ICSM has SCOB (Single Candle Order Block) detection function. ICM is packed with the extremely useful in SMC trading SCOB detetction feature, which allows you find even more solid points of interest;
ICSM has super minimalistic design, which contains only the things you really need. Your chart will not be overloaded with unnecessary information. You will only see clear points of interest, liquidity and price movement.
WHY SHOULD YOU USE IT?
As was said above, ICSM allows you to see the most profitable points and zones of interest, which professional SMC traders consider as one of the best in the market, because they are historically the areas from which the price bounces the most, allowing the smartest traders to get quick an clean profits with low drawdown.
In the ICSM indicator these zones are SCOB and ICM line liquidity grabs. By using these zones of interest to find entry points, you increase the chance to open a trade at the most lucrative price and reduce trading risks.
Considering what was said above, this indicator can help traders reduce drawdown risks and increase potential profits simply by showing the most liquid zones of interest, which are perfect for opening a trading position.
Here are some of the examples of how you leverage ICSM in your trading process:
Example of the short trade:
Price shows overall short trend. Trend liquidity is being formed.
Price grabs liduiqity from three ICM lines in a row and then creates a long SCOB at the end of 3rd liquidity grab.
SCOB, which occured at the end of ICM line, represents much stronger zone of interest than a regular SCOB. In this case it represents a zone, which we will use to find an entry.
The entry for the trade will be SCOB candle's low, stop-loss target should be put above SCOB candle's high. Our take-profit target is trend liquidity. See the screenshot above for better understanding.
▼ Now let's see the long trade example. ▼
Example of the long trade:
Price creates trend liquidity by showing equal highs ( EQH ).
Price grabs liduiqity from four ICM lines in a row and then creates a long SCOB at the end of 4th liquidity grab.
Again: SCOB, which occured at the end of ICM line, represents much stronger zone of interest than a regular SCOB. In this case it represents a zone, which we will use to find an entry.
The entry for the trade will be SCOB candle's high, stop-loss target should be put below SCOB candle's low. Our take-profit target is EQH. See the screenshot above for better understanding.
ALERTS
ICSM provides simple and easy alert customization, allwoing to choose only the alerts you want to receive. You can choose from the following alert options:
ICM — impulse or correction liquidity grab;
SCOB — SCOB is formed, wether or not the liquidity is grabbed from the impulse or correction;
SCOB+ICM — SCOB is formed after grabbing the liquidity of the ICM line;
SCOB+ICM (same candle) — SCOB is formed in the liquidity area of the impulse or correction.
HOW CAN I GET THE MOST OUT OF IT?
ICSM displays only the first liquidity of an impulse or correction, which matches the IDM (Inducement) in the Advanced SMC strategy . This strategy is completely covered in the World Class SMC indicator and is available for free for PDF in three parts.
You can also ICSM with any other strategy, because ICSM is a very flexible indicator and will help anyone improve their trading by making one aware of the high-quality liquidity on the chart.
Let's see how you can leverage ICSM with our World Class SMC indicator and other different strategies:
Example of the long & short trades with World Class SMC.
Long (1-3):
Price reached previous OB-EXT . This is the first sign for the potential price reversal;
ICM+SCOB happened after price reached OB-EXT;
After that, you can need to look for an entry on LTF. If you don't know how to do it, you can refer to our education materials.
Short (4-6):
Price reached OB-IDM , which is also a great sign for a potential upcoming price reversal;
ICM+SCOB occured after liquidity grab of the previous SCOB. This fact does strengthen the probability of the potential upcoming price reversal;
Now you need to switch to LTF and find an entry there.
Example of the short trade with simple Fibonacci retracement strategy.
Price grabs the liquidity of the ICM lines three times in a row, forming SCOB after the 3rd grab;
Price performs correctional move down without testing the SCOB, leaving no entry opportunity by our initial strategy, so we can add another strategy — Fibonacci retracement from 0.618 level — to our analysis in order to find an entry ;
We use Fibonacci grid with our initial strategy to find the best POI, that will align with the trend direction and will eventually become our entry point.
SUMMARY
ICSM is a unique indicator that indentifies zones and points of interests with high-quiality liquidity and can be both a stand-alone tool and can be integrated into any other strategy to increase the efficiency of analysis, accuracy of trading entries and reduce trading risks.
If you want to learn the SMC strategies that our team uses in our products, you can refer to our educational materials.
We hope that you will find a great use of ICSM and it will help you improve your perfomance as a trader. Best of luck, traders!
— with love, WinWorld Team
Liquidation Volume (Zeiierman)█ Overview
The Liquidation Volume (Zeiierman) indicator highlights real-time long and short liquidations across all timeframes on TradingView. The indicator assists traders in identifying potential liquidation points in the market based on volume and price movements. Liquidation, in this context, refers to the forced closure of a trader's position due to insufficient margin in their account to support open positions, often occurring during significant price movements.
█ How It Works
The indicator operates primarily through the computation of a MomentumAdjustedPrice function, which is applied to volume-weighted prices (open, high, low, close) adjusted for volatility.
█ How to Use
Identifying Support and Resistance Levels: Liquidation data can provide valuable insights into key market levels where significant trading activities occur. These levels often act as support or resistance in the price chart. Support levels are typically where an asset's price finds a floor, as buying interest is significant enough to outweigh selling pressure. Conversely, resistance levels are where an asset's price may find a ceiling, with selling interest outweighing buying pressure. By analyzing liquidation data, traders can identify these critical points.
Start of a New Trend:
The initiation of a new trend can often be identified by a significant shift in liquidation volumes near breakout levels.
Trend Continuations:
Trend continuations are periods where the current trend is sustained and further confirmed by liquidation patterns. For example, in an uptrend, continuous short liquidations might occur, suggesting that the trend is strong and likely to persist as bearish traders keep getting squeezed out. In a downtrend, continuous long liquidations can serve as confirmation that the trend is still in place. Recognizing these patterns in liquidation data can help traders to stay aligned with the prevailing trend and avoid premature exits or entries against the trend.
Trend Reversals: Patterns in liquidations can be crucial in signaling potential trend reversals. A sudden and significant change in liquidation volumes—like a spike in long liquidations during a downtrend or short liquidations during an uptrend—can indicate that the current trend is losing steam and a reversal may be imminent. This information can be particularly useful for traders looking to anticipate market turns and adjust their strategies accordingly.
Spot Potential Liquidation Points: By observing the liquidation candles and their colors, traders can identify where large liquidations are likely occurring, signaling potential market turning points.
Understand Market Sentiment: Changes in liquidation volumes can provide insights into bullish or bearish sentiment, helping traders gauge the market mood. By observing liquidation patterns and clusters, traders can get insights into prevailing market sentiments and emerging trends.
█ Settings
Liquidation Source: Allows selection between 'Price' and 'Volume' for liquidation analysis.
Volume Period: Determines the period over which volume is averaged.
Volatility Period: Sets the length for calculating standard deviation, influencing the volatility measure.
Candle Display Toggle: Enables or disables the display of liquidation candles on the chart.
Threshold: Sets the level at which liquidation bars are triggered.
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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!
MR Liq lvlHi Guys!
- This script show you liquidations levels with leverage of 100X, 50X, 25X & 10X (shorts & longs).
- This indicator "only" works for XBT on Bitmex.
- Other indicators only show the liquidations up to 25X .
- The idea of this indicator is to help the user to determine those levels where Bitmex hunt liquidity.
Best Regards.
Mr.amin
FxCanli RangeFxCanli Range is an indicator based on ICT Internal Range and External Range concept.
What is ICT Internal Range Liquidity?
The Fair Value Gap is marked as the ICT internal range liquidity.
ICT Fair Value Gap is marked as the liquidity because it is a formation of three candles leaving an area between high and low of 1st and 3rd candle where price do not overlap.
FxCanli Range Indicator draws all Internal Ranges above explaining the ICT internal range liquidity.
What is Imbalance (FVG)?
Fair Value Gaps are price jumps caused by imbalanced buying and selling pressures.
A bullish Fair Value Gap is created when there is a gap between the high of the first candle and the low of the third candle.
A bearish Fair Value Gap is created when there is a gap between the low of the first candle and the high of the third candle.
What is ICT External Range Liquidity?
The swing high and swing low of an ICT dealing range are termed as external range.
The high of an ICT dealing range is termed as “buy side liquidity” assuming the buy stops rest above the high of dealing range.
While the low of an ICT dealing range is known as “sell side liquidity” assuming the sell stops resting below the low of dealing range.
FxCanli Range Indicator draws all External Ranges above explaining the ICT external range liquidity
🔶 USAGE & EXAMPLES
As ICT said us, Price moves 2 side, Internal Liquidity or External Liquidity
External Range Liquidity to Internal Range Liquidity
When price reached to External Range, it will sweep the External Range Liquidity
at that time, we have to wait price to reverse and start to move to Internal range liquidity (FVG)
our strategy has to be like this; we have to open 2 time less lower time frame
if we are at 1 hour chart, we have to open 1Hour - 15 min - 5 min chart
and wait for Trend Reversal pattern at there
Internal Range Liquidity to External Range Liquidity
When price reached to Internal Range(FVG), it will fill the imbalance
at that time, we have to wait price to reverse and start to move to External Range Liquidity.
Again we have to decrease our time frame 2 times.
if we are at 1 hour chart, we have to open 1Hour -> 15 min -> 5 min chart
and wait for Trend Reversal pattern at there
🔶 SETTINGS
With the settings;
▪️ Fractal Properties;
it will show fractals or not, you will decide the period of fractals, Style, Color and also Size of the fractal
▪️ Trend Line Properties;
it will show trend or not, you will decide the color of the trend, line style, and line width.
▪️ External Range Properties;
it will show external range or not, Color of the level, line style, line witdh, show text of the external range, what will it write at the text, place/size/color of the text, show time frame, show price,
▪️ Internal Range Properties;
it will show internal range or not, Color of the level, line style, line witdh, show text of the external range, what will it write at the text, place/size/color of the text, show time frame, show price,
▪️ Alert Conditions
you will set alerts at this part
Alert or not, liquidity(External Range) alerts, FVG(Internal Range) alerts, FVG filled alert
Part 1
Part 2
Wish you great trades...
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.
24h volume by 100eyesIntroducing the 24h volume indicator on Tradingview!
DM me (Trading-Guru) here on Tradingview to get access to this indicator.
100eyes asked me to create a new Tradingview indicator that estimates the 24h volume of a pair. Works for all BTC/USDT/USD/ETH crypto pairs. You can choose to display the 24h volume in BTC or USD(T).
This indicator allows you to:
Check the 24h volume of a pair without having to check the website of the exchange
Quickly compare 24h volumes across pairs, e.g. ADABTC to ADAUSDT
Quickly compare 24h volumes of pairs across different exchanges
Volume is an important factor in crypto trading to estimate liquidity. Use this indicator to adjust your position size according to the volume of a pair.
Even on the website of an exchange, it's difficult to compare volume since for example volumes of USDT pairs are expressed in USDT, and volumes of BTC pairs are expressed in BTC. This indicator solves that problem by expressing everything in the same currency, and also directly on Tradingview!
F.A.Q.
Q: How do I get access to the indicator?
A: DM Trading-Guru on Tradingview.
Q: Why are there different values for different timeframes?
A: That is due to Tradingview limitations. The smaller the timeframe, the more accurate the displayed value. The timeframe you're looking at equals the maximum amount of lag.
Q: I'm on the Tradingview mobile app, why is the value is not displayed next to the indicator's name?
A: Click somewhere inside the chart. Then the indicator value will appear.
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.
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.
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.
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.
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.
Cryptolabs Global Liquidity Cycle Momentum IndicatorCryptolabs Global Liquidity Cycle Momentum Indicator (LMI-BTC)
This open-source indicator combines global central bank liquidity data with Bitcoin price movements to identify medium- to long-term market cycles and momentum phases. It is designed for traders who want to incorporate macroeconomic factors into their Bitcoin analysis.
How It Works
The script calculates a Liquidity Index using balance sheet data from four central banks (USA: ECONOMICS:USCBBS, Japan: FRED:JPNASSETS, China: ECONOMICS:CNCBBS, EU: FRED:ECBASSETSW), augmented by the Dollar Index (TVC:DXY) and Chinese 10-year bond yields (TVC:CN10Y). This index is:
- Logarithmically scaled (math.log) to better represent large values like central bank balances and Bitcoin prices.
- Normalized over a 50-period range to balance fluctuations between minimum and maximum values.
- Compared to prior-year values, with the number of bars dynamically adjusted based on the timeframe (e.g., 252 for 1D, 52 for 1W), to compute percentage changes.
The liquidity change is analyzed using a Chande Momentum Oscillator (CMO) (period: 24) to measure momentum trends. A Weighted Moving Average (WMA) (period: 10) acts as a signal line. The Bitcoin price is also plotted logarithmically to highlight parallels with liquidity cycles.
Usage
Traders can use the indicator to:
- Identify global liquidity cycles influencing Bitcoin price trends, such as expansive or restrictive monetary policies.
- Detect momentum phases: Values above 50 suggest overbought conditions, below -50 indicate oversold conditions.
- Anticipate trend reversals by observing CMO crossovers with the signal line.
It performs best on higher timeframes like daily (1D) or weekly (1W) charts. The visualization includes:
- CMO line (green > 50, red < -50, blue neutral), signal line (white), Bitcoin price (gray).
- Horizontal lines at 50, 0, and -50 for improved readability.
Originality
This indicator stands out from other momentum tools like RSI or basic price analysis due to:
- Unique Data Integration: Combines four central bank datasets, DXY, and CN10Y as macroeconomic proxies for Bitcoin.
- Dynamic Prior-Year Analysis: Calculates liquidity changes relative to historical values, adjustable by timeframe.
- Logarithmic Normalization: Enhances visibility of extreme values, critical for cryptocurrencies and macro data.
This combination offers a rare perspective on the interplay between global liquidity and Bitcoin, unavailable in other open-source scripts.
Settings
- CMO Period: Default 24, adjustable for faster/slower signals.
- Signal WMA: Default 10, for smoothing the CMO line.
- Normalization Window: Default 50 periods, customizable.
Users can modify these parameters in the Pine Editor to tailor the indicator to their strategy.
Note
This script is designed for medium- to long-term analysis, not scalping. For optimal results, combine it with additional analyses (e.g., on-chain data, support/resistance levels). It does not guarantee profits but supports informed decisions based on macroeconomic trends.
Data Sources
- Bitcoin: INDEX:BTCUSD
- Liquidity: ECONOMICS:USCBBS, FRED:JPNASSETS, ECONOMICS:CNCBBS, FRED:ECBASSETSW
- Additional: TVC:DXY, TVC:CN10Y
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.
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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.
