CandelaCharts - Volume Imbalance (VI) ๐ Overview
Volume Imbalance occurs when thereโs a noticeable gap between the bodies of two consecutive candlesticks, with no overlap between them. While the wicks of the candles might intersect, the candle bodies remain entirely separate. This phenomenon often signifies that the algorithm driving market activity did not evenly distribute prices between these two levels, leaving behind a small Volume Imbalance (VI).
A Bullish Volume Imbalance forms when the body of a green candlestick gaps above the previous candleโs body, with no overlap, indicating strong upward momentum and insufficient sell-side liquidity.
A Bearish Volume Imbalance forms when the body of a red candlestick gaps below the previous candleโs body, with no overlap, signaling intense downward pressure and a lack of buy-side liquidity.
This indicator can automatically identify volume imbalances by scanning candlestick patterns and detecting gaps between consecutive candle bodies. These volume imbalances act as price magnets, often attracting the market back to fill the gap before resuming its original direction. Recognizing and leveraging these gaps can be a powerful tool in technical analysis for predicting price movements.
๐ฆ Features
MTF
Mitigation
Consequent Encroachment
Threshold
Hide Overlap
Advanced Styling
โ๏ธ Settings
Show: Controls whether VIs are displayed on the chart.
Show Last: Sets the number of VIs you want to display.
Length: Determines the length of each VI.
Mitigation: Highlights when a VI has been touched, using a different color without marking it as invalid.
Timeframe: Specifies the timeframe used to detect VIs.
Threshold: Sets the minimum gap size required for VI detection on the chart.
Show Mid-Line: Configures the midpoint line's width and style within the VI. (Consequent Encroachment - CE)
Show Border: Defines the border width and line style of the VI.
Hide Overlap: Removes overlapping VIs from view.
Extend: Extends the VI length to the current candle.
Elongate: Fully extends the VI length to the right side of the chart.
โก๏ธ Showcase
Simple
Mitigated
Bordered
Consequent Encroachment
Extended
๐จ Alerts
This script provides alert options for all signals.
Bearish Signal
A bearish alert triggers when a red candlestick gaps below the previous body, signaling downward pressure.
Bullish Signal
A bullish alert triggers when a green candlestick gaps above the previous body, indicating upward momentum.
โ ๏ธ Disclaimer
Trading involves significant risk, and many participants may incur losses. The content on this site is not intended as financial advice and should not be interpreted as such. Decisions to buy, sell, hold, or trade securities, commodities, or other financial instruments carry inherent risks and are best made with guidance from qualified financial professionals. Past performance is not indicative of future results.
Search in scripts for "liquidity"
Fibonacci Bands [BigBeluga]The Fibonacci Band indicator is a powerful tool for identifying potential support, resistance, and mean reversion zones based on Fibonacci ratios. It overlays three sets of Fibonacci ratio bands (38.2%, 61.8%, and 100%) around a central trend line, dynamically adapting to price movements. This structure enables traders to track trends, visualize potential liquidity sweep areas, and spot reversal points for strategic entries and exits.
๐ต KEY FEATURES & USAGE
Fibonacci Bands for Support & Resistance:
The Fibonacci Band indicator applies three key Fibonacci ratios (38.2%, 61.8%, and 100%) to construct dynamic bands around a smoothed price. These levels often act as critical support and resistance areas, marked with labels displaying the percentage and corresponding price. The 100% band level is especially crucial, signaling potential liquidity sweep zones and reversal points.
Mean Reversion Signals at 100% Bands:
When price moves above or below the 100% band, the indicator generates mean reversion signals.
Trend Detection with Midline:
The central line acts as a trend-following tool: when solid, it indicates an uptrend, while a dashed line signals a downtrend. This adaptive midline helps traders assess the prevailing market direction while keeping the chart clean and intuitive.
Extended Price Projections:
All Fibonacci bands extend to future bars (default 30) to project potential price levels, providing a forward-looking perspective on where price may encounter support or resistance. This feature helps traders anticipate market structure in advance and set targets accordingly.
Liquidity Sweep:
--
-Liquidity Sweep at Previous Lows:
The price action moves below a previous low, capturing sell-side liquidity (stop-losses from long positions or entries for breakout traders).
The wick suggests that the price quickly reversed, leaving a failed breakout below support.
This is a classic liquidity grab, often indicating a bullish reversal .
-Liquidity Sweep at Previous Highs:
The price spikes above a prior high, sweeping buy-side liquidity (stop-losses from short positions or breakout entries).
The wick signifies rejection, suggesting a failed breakout above resistance.
This is a bearish liquidity sweep , often followed by a mean reversion or a downward move.
Display Customization:
To declutter the chart, traders can choose to hide Fibonacci levels and only display overbought/oversold zones along with the trend-following midline and mean reversion signals. This option enables a clearer focus on key reversal areas without additional distractions.
๐ต CUSTOMIZATION
Period Length: Adjust the length of the smoothed moving average for more reactive or smoother bands.
Channel Width: Customize the width of the Fibonacci channel.
Fibonacci Ratios: Customize the Fibonacci ratios to reflect personal preference or unique market behaviors.
Future Projection Extension: Set the number of bars to extend Fibonacci bands, allowing flexibility in projecting price levels.
Hide Fibonacci Levels: Toggle the visibility of Fibonacci levels for a cleaner chart focused on overbought/oversold regions and midline trend signals.
Liquidity Sweep: Toggle the visibility of Liquidity Sweep points
The Fibonacci Band indicator provides traders with an advanced framework for analyzing market structure, liquidity sweeps, and trend reversals. By integrating Fibonacci-based levels with trend detection and mean reversion signals, this tool offers a robust approach to navigating dynamic price action and finding high-probability trading opportunities.
Custom V2 KillZone US / FVG / EMAThis indicator is designed for traders looking to analyze liquidity levels, opportunity zones, and the underlying trend across different trading sessions. Inspired by the ICT methodology, this tool combines analysis of Exponential Moving Averages (EMA), session management, and Fair Value Gap (FVG) detection to provide a structured and disciplined approach to trading effectively.
Indicator Features
Identifying the Underlying Trend with Two EMAs
The indicator uses two EMAs on different, customizable timeframes to define the underlying trend:
EMA1 (default set to a daily timeframe): Represents the primary underlying trend.
EMA2 (default set to a 4-hour timeframe): Helps identify secondary corrections or impulses within the main trend.
These two EMAs allow traders to stay aligned with the market trend by prioritizing trades in the direction of the moving averages. For example, if prices are above both EMAs, the trend is bullish, and long trades are favored.
Analysis of Market Sessions
The indicator divides the day into key trading sessions:
Asian Session
London Session
US Pre-Open Session
Liquidity Kill Session
US Kill Zone Session
Each session is represented by high and low zones as well as mid-lines, allowing traders to visualize liquidity levels reached during these periods. Tracking the price levels in different sessions helps determine whether liquidity levels have been "swept" (taken) or not, which is essential for ICT methodology.
Liquidity Signal ("OK" or "STOP")
A specific signal appears at the end of the "Liquidity Kill" session (just before the "US Kill Zone" session):
"OK" Signal: Indicates that liquidity conditions are favorable for trading the "US Kill Zone" session. This means that liquidity levels have been swept in previous sessions (Asian, London, US Pre-Open), and the market is ready for an opportunity.
"STOP" Signal: Indicates that it is not favorable to trade the "US Kill Zone" session, as certain liquidity conditions have not been met.
The "OK" or "STOP" signal is based on an analysis of the high and low levels from previous sessions, allowing traders to ensure that significant liquidity zones have been reached before considering positions in the "Kill Zone".
Detection of Fair Value Gaps (FVG) in the US Kill Zone Session
When an "OK" signal is displayed, the indicator identifies Fair Value Gaps (FVG) during the "US Kill Zone" session. These FVGs are areas where price may return to fill an "imbalance" in the market, making them potential entry points.
Bullish FVG: Detected when there is a bullish imbalance, providing a buying opportunity if conditions align with the underlying trend.
Bearish FVG: Detected when there is a bearish imbalance, providing a selling opportunity in the trend direction.
FVG detection aligns with the ICT Silver Bullet methodology, where these imbalance zones serve as probable entry points during the "US Kill Zone".
How to Use This Indicator
Check the Underlying Trend
Before trading, observe the two EMAs (daily and 4-hour) to understand the general market trend. Trades will be prioritized in the direction indicated by these EMAs.
Monitor Liquidity Signals After the Asian, London, and US Pre-Open Sessions
The high and low levels of each session help determine if liquidity has already been swept in these areas. At the end of the "Liquidity Kill" session, an "OK" or "STOP" label will appear:
"OK" means you can look for trading opportunities in the "US Kill Zone" session.
"STOP" means it is preferable not to take trades in the "US Kill Zone" session.
Look for Opportunities in the US Kill Zone if the Signal is "OK"
When the "OK" label is present, focus on the "US Kill Zone" session. Use the Fair Value Gaps (FVG) as potential entry points for trades based on the ICT methodology. The identified FVGs will appear as colored boxes (bullish or bearish) during this session.
Use ICT Methodology to Manage Your Trades
Follow the FVGs as potential reversal zones in the direction of the trend, and manage your positions according to your personal strategy and the rules of the ICT Silver Bullet method.
Customizable Settings
The indicator includes several customization options to suit the trader's preferences:
EMA: Length, source (close, open, etc.), and timeframe.
Market Sessions: Ability to enable or disable each session, with color and line width settings.
Liquidity Signals: Customization of colors for the "OK" and "STOP" labels.
FVG: Option to display FVGs or not, with customizable colors for bullish and bearish FVGs, and the number of bars for FVG extension.
-------------------------------------------------------------------------------------------------------------
Cet indicateur est conรงu pour les traders souhaitant analyser les niveaux de liquiditรฉ, les zones dโopportunitรฉ, et la tendance de fond ร travers diffรฉrentes sessions de trading. Inspirรฉ de la mรฉthodologie ICT, cet outil combine l'analyse des moyennes mobiles exponentielles (EMA), la gestion des sessions de marchรฉ, et la dรฉtection des Fair Value Gaps (FVG), afin de fournir une approche structurรฉe et disciplinรฉe pour trader efficacement.
ICT Master Suite [Trading IQ]Hello Traders!
Weโre excited to introduce the ICT Master Suite by TradingIQ, a new tool designed to bring together several ICT concepts and strategies in one place.
The Purpose Behind the ICT Master Suite
There are a few challenges traders often face when using ICT-related indicators:
Many available indicators focus on one or two ICT methods, which can limit traders who apply a broader range of ICT related techniques on their charts.
There aren't many indicators for ICT strategy models, and we couldn't find ICT indicators that allow for testing the strategy models and setting alerts.
Many ICT related concepts exist in the public domain as indicators, not strategies! This makes it difficult to verify that the ICT concept has some utility in the market you're trading and if it's worth trading - it's difficult to know if it's working!
Some users might not have enough chart space to apply numerous ICT related indicators, which can be restrictive for those wanting to use multiple ICT techniques simultaneously.
The ICT Master Suite is designed to offer a comprehensive option for traders who want to apply a variety of ICT methods. By combining several ICT techniques and strategy models into one indicator, it helps users maximize their chart space while accessing multiple tools in a single slot.
Additionally, the ICT Master Suite was developed as a strategy . This means users can backtest various ICT strategy models - including deep backtesting. A primary goal of this indicator is to let traders decide for themselves what markets to trade ICT concepts in and give them the capability to figure out if the strategy models are worth trading!
What Makes the ICT Master Suite Different
There are many ICT-related indicators available on TradingView, each offering valuable insights. What the ICT Master Suite aims to do is bring together a wider selection of these techniques into one tool. This includes both key ICT methods and strategy models, allowing traders to test and activate strategies all within one indicator.
Features
The ICT Master Suite offers:
Multiple ICT strategy models, including the 2022 Strategy Model and Unicorn Model, which can be built, tested, and used for live trading.
Calculation and display of key price areas like Breaker Blocks, Rejection Blocks, Order Blocks, Fair Value Gaps, Equal Levels, and more.
The ability to set alerts based on these ICT strategies and key price areas.
A comprehensive, yet practical, all-inclusive ICT indicator for traders.
Customizable Timeframe - Calculate ICT concepts on off-chart timeframes
Unicorn Strategy Model
2022 Strategy Model
Liquidity Raid Strategy Model
OTE (Optimal Trade Entry) Strategy Model
Silver Bullet Strategy Model
Order blocks
Breaker blocks
Rejection blocks
FVG
Strong highs and lows
Displacements
Liquidity sweeps
Power of 3
ICT Macros
HTF previous bar high and low
Break of Structure indications
Market Structure Shift indications
Equal highs and lows
Swings highs and swing lows
Fibonacci TPs and SLs
Swing level TPs and SLs
Previous day high and low TPs and SLs
And much more! An ongoing project!
How To Use
Many traders will already be familiar with the ICT related concepts listed above, and will find using the ICT Master Suite quite intuitive!
Despite this, let's go over the features of the tool in-depth and how to use the tool!
The image above shows the ICT Master Suite with almost all techniques activated.
ICT 2022 Strategy Model
The ICT Master suite provides the ability to test, set alerts for, and live trade the ICT 2022 Strategy Model.
The image above shows an example of a long position being entered following a complete setup for the 2022 ICT model.
A liquidity sweep occurs prior to an upside breakout. During the upside breakout the model looks for the FVG that is nearest 50% of the setup range. A limit order is placed at this FVG for entry.
The target entry percentage for the range is customizable in the settings. For instance, you can select to enter at an FVG nearest 33% of the range, 20%, 66%, etc.
The profit target for the model generally uses the highest high of the range (100%) for longs and the lowest low of the range (100%) for shorts. Stop losses are generally set at 0% of the range.
The image above shows the short model in action!
Whether you decide to follow the 2022 model diligently or not, you can still set alerts when the entry condition is met.
ICT Unicorn Model
The image above shows an example of a long position being entered following a complete setup for the ICT Unicorn model.
A lower swing low followed by a higher swing high precedes the overlap of an FVG and breaker block formed during the sequence.
During the upside breakout the model looks for an FVG and breaker block that formed during the sequence and overlap each other. A limit order is placed at the nearest overlap point to current price.
The profit target for this example trade is set at the swing high and the stop loss at the swing low. However, both the profit target and stop loss for this model are configurable in the settings.
For Longs, the selectable profit targets are:
Swing High
Fib -0.5
Fib -1
Fib -2
For Longs, the selectable stop losses are:
Swing Low
Bottom of FVG or breaker block
The image above shows the short version of the Unicorn Model in action!
For Shorts, the selectable profit targets are:
Swing Low
Fib -0.5
Fib -1
Fib -2
For Shorts, the selectable stop losses are:
Swing High
Top of FVG or breaker block
The image above shows the profit target and stop loss options in the settings for the Unicorn Model.
Optimal Trade Entry (OTE) Model
The image above shows an example of a long position being entered following a complete setup for the OTE model.
Price retraces either 0.62, 0.705, or 0.79 of an upside move and a trade is entered.
The profit target for this example trade is set at the -0.5 fib level. This is also adjustable in the settings.
For Longs, the selectable profit targets are:
Swing High
Fib -0.5
Fib -1
Fib -2
The image above shows the short version of the OTE Model in action!
For Shorts, the selectable profit targets are:
Swing Low
Fib -0.5
Fib -1
Fib -2
Liquidity Raid Model
The image above shows an example of a long position being entered following a complete setup for the Liquidity Raid Modell.
The user must define the session in the settings (for this example it is 13:30-16:00 NY time).
During the session, the indicator will calculate the session high and session low. Following a โraidโ of either the session high or session low (after the session has completed) the script will look for an entry at a recently formed breaker block.
If the session high is raided the script will look for short entries at a bearish breaker block. If the session low is raided the script will look for long entries at a bullish breaker block.
For Longs, the profit target options are:
Swing high
User inputted Lib level
For Longs, the stop loss options are:
Swing low
User inputted Lib level
Breaker block bottom
The image above shows the short version of the Liquidity Raid Model in action!
For Shorts, the profit target options are:
Swing Low
User inputted Lib level
For Shorts, the stop loss options are:
Swing High
User inputted Lib level
Breaker block top
Silver Bullet Model
The image above shows an example of a long position being entered following a complete setup for the Silver Bullet Modell.
During the session, the indicator will determine the higher timeframe bias. If the higher timeframe bias is bullish the strategy will look to enter long at an FVG that forms during the session. If the higher timeframe bias is bearish the indicator will look to enter short at an FVG that forms during the session.
For Longs, the profit target options are:
Nearest Swing High Above Entry
Previous Day High
For Longs, the stop loss options are:
Nearest Swing Low
Previous Day Low
The image above shows the short version of the Silver Bullet Model in action!
For Shorts, the profit target options are:
Nearest Swing Low Below Entry
Previous Day Low
For Shorts, the stop loss options are:
Nearest Swing High
Previous Day High
Order blocks
The image above shows indicator identifying and labeling order blocks.
The color of the order blocks, and how many should be shown, are configurable in the settings!
Breaker Blocks
The image above shows indicator identifying and labeling order blocks.
The color of the breaker blocks, and how many should be shown, are configurable in the settings!
Rejection Blocks
The image above shows indicator identifying and labeling rejection blocks.
The color of the rejection blocks, and how many should be shown, are configurable in the settings!
Fair Value Gaps
The image above shows indicator identifying and labeling fair value gaps.
The color of the fair value gaps, and how many should be shown, are configurable in the settings!
Additionally, you can select to only show fair values gaps that form after a liquidity sweep. Doing so reduces "noisy" FVGs and focuses on identifying FVGs that form after a significant trading event.
The image above shows the feature enabled. A fair value gap that occurred after a liquidity sweep is shown.
Market Structure
The image above shows the ICT Master Suite calculating market structure shots and break of structures!
The color of MSS and BoS, and whether they should be displayed, are configurable in the settings.
Displacements
The images above show indicator identifying and labeling displacements.
The color of the displacements, and how many should be shown, are configurable in the settings!
Equal Price Points
The image above shows the indicator identifying and labeling equal highs and equal lows.
The color of the equal levels, and how many should be shown, are configurable in the settings!
Previous Custom TF High/Low
The image above shows the ICT Master Suite calculating the high and low price for a user-defined timeframe. In this case the previous dayโs high and low are calculated.
To illustrate the customizable timeframe function, the image above shows the indicator calculating the previous 4 hour high and low.
Liquidity Sweeps
The image above shows the indicator identifying a liquidity sweep prior to an upside breakout.
The image above shows the indicator identifying a liquidity sweep prior to a downside breakout.
The color and aggressiveness of liquidity sweep identification are adjustable in the settings!
Power Of Three
The image above shows the indicator calculating Po3 for two user-defined higher timeframes!
Macros
The image above shows the ICT Master Suite identifying the ICT macros!
ICT Macros are only displayable on the 5 minute timeframe or less.
Strategy Performance Table
In addition to a full-fledged TradingView backtest for any of the ICT strategy models the indicator offers, a quick-and-easy strategy table exists for the indicator!
The image above shows the strategy performance table in action.
Keep in mind that, because the ICT Master Suite is a strategy script, you can perform fully automatic backtests, deep backtests, easily add commission and portfolio balance and look at pertinent metrics for the ICT strategies you are testing!
Lite Mode
Traders who want the cleanest chart possible can toggle on โLite Modeโ!
In Lite Mode, any neon or โglowโ like effects are removed and key levels are marked as strict border boxes. You can also select to remove box borders if thatโs what you prefer!
Settings Used For Backtest
For the displayed backtest, a starting balance of $1000 USD was used. A commission of 0.02%, slippage of 2 ticks, a verify price for limit orders of 2 ticks, and 5% of capital investment per order.
A commission of 0.02% was used due to the backtested asset being a perpetual future contract for a crypto currency. The highest commission (lowest-tier VIP) for maker orders on many exchanges is 0.02%. All entered positions take place as maker orders and so do profit target exits. Stop orders exist as stop-market orders.
A slippage of 2 ticks was used to simulate more realistic stop-market orders. A verify limit order settings of 2 ticks was also used. Even though BTCUSDT.P on Binance is liquid, we just want the backtest to be on the safe side. Additionally, the backtest traded 100+ trades over the period. The higher the sample size the better; however, this example test can serve as a starting point for traders interested in ICT concepts.
Community Assistance And Feedback
Given the complexity and idiosyncratic applications of ICT concepts amongst its proponents, the ICT Master Suiteโs built-in strategies and level identification methods might not align with everyone's interpretation.
That said, the best we can do is precisely define ICT strategy rules and concepts to a repeatable process, test, and apply them! Whether or not an ICT strategy is trading precisely how you would trade it, seeing the model in action, taking trades, and with performance statistics is immensely helpful in assessing predictive utility.
If you think we missed something, you notice a bug, have an idea for strategy model improvement, please let us know! The ICT Master Suite is an ongoing project that will, ideally, be shaped by the community.
A big thank you to the @PineCoders for their Time Library!
Thank you!
Price Action Analyst [OmegaTools]Price Action Analyst (PAA) is an advanced trading tool designed to assist traders in identifying key price action structures such as order blocks, market structure shifts, liquidity grabs, and imbalances. With its fully customizable settings, the script offers both novice and experienced traders insights into potential market movements by visually highlighting premium/discount zones, breakout signals, and significant price levels.
This script utilizes complex logic to determine significant price action patterns and provides dynamic tools to spot strong market trends, liquidity pools, and imbalances across different timeframes. It also integrates an internal backtesting function to evaluate win rates based on price interactions with supply and demand zones.
The script combines multiple analysis techniques, including market structure shifts, order block detection, fair value gaps (FVG), and ICT bias detection, to provide a comprehensive and holistic market view.
Key Features:
Order Block Detection: Automatically detects order blocks based on price action and strength analysis, highlighting potential support/resistance zones.
Market Structure Analysis: Tracks internal and external market structure changes with gradient color-coded visuals.
Liquidity Grabs & Breakouts: Detects potential liquidity grab and breakout areas with volume confirmation.
Fair Value Gaps (FVG): Identifies bullish and bearish FVGs based on historical price action and threshold calculations.
ICT Bias: Integrates ICT bias analysis, dynamically adjusting based on higher-timeframe analysis.
Supply and Demand Zones: Highlights supply and demand zones using customizable colors and thresholds, adjusting dynamically based on market conditions.
Trend Lines: Automatically draws trend lines based on significant price pivots, extending them dynamically over time.
Backtesting: Internal backtesting engine to calculate the win rate of signals generated within supply and demand zones.
Percentile-Based Pricing: Plots key percentile price levels to visualize premium, fair, and discount pricing zones.
High Customizability: Offers extensive user input options for adjusting zone detection, color schemes, and structure analysis.
User Guide:
Order Blocks: Order blocks are significant support or resistance zones where strong buyers or sellers previously entered the market. These zones are detected based on pivot points and engulfing price action. The strength of each block is determined by momentum, volume, and liquidity confirmations.
Demand Zones: Displayed in shades of blue based on their strength. The darker the color, the stronger the zone.
Supply Zones: Displayed in shades of red based on their strength. These zones highlight potential resistance areas.
The zones will dynamically extend as long as they remain valid. Users can set a maximum number of order blocks to be displayed.
Market Structure: Market structure is classified into internal and external shifts. A bullish or bearish market structure break (MSB) occurs when the price moves past a previous high or low. This script tracks these breaks and plots them using a gradient color scheme:
Internal Structure: Short-term market structure, highlighting smaller movements.
External Structure: Long-term market shifts, typically more significant.
Users can choose how they want the structure to be visualized through the "Market Structure" setting, choosing from different visual methods.
Liquidity Grabs: The script identifies liquidity grabs (false breakouts designed to trap traders) by monitoring price action around highs and lows of previous bars. These are represented by diamond shapes:
Liquidity Buy: Displayed below bars when a liquidity grab occurs near a low.
Liquidity Sell: Displayed above bars when a liquidity grab occurs near a high.
Breakouts: Breakouts are detected based on strong price momentum beyond key levels:
Breakout Buy: Triggered when the price closes above the highest point of the past 20 bars with confirmation from volume and range expansion.
Breakout Sell: Triggered when the price closes below the lowest point of the past 20 bars, again with volume and range confirmation.
Fair Value Gaps (FVG): Fair value gaps (FVGs) are periods where the price moves too quickly, leaving an unbalanced market condition. The script identifies these gaps:
Bullish FVG: When there is a gap between the low of two previous bars and the high of a recent bar.
Bearish FVG: When a gap occurs between the high of two previous bars and the low of the recent bar.
FVGs are color-coded and can be filtered by their size to focus on more significant gaps.
ICT Bias: The script integrates the ICT methodology by offering an auto-calculated higher-timeframe bias:
Long Bias: Suggests the market is in an uptrend based on higher timeframe analysis.
Short Bias: Indicates a downtrend.
Neutral Bias: Suggests no clear directional bias.
Trend Lines: Automatic trend lines are drawn based on significant pivot highs and lows. These lines will dynamically adjust based on price movement. Users can control the number of trend lines displayed and extend them over time to track developing trends.
Percentile Pricing: The script also plots the 25th percentile (discount zone), 75th percentile (premium zone), and a fair value price. This helps identify whether the current price is overbought (premium) or oversold (discount).
Customization:
Zone Strength Filter: Users can set a minimum strength threshold for order blocks to be displayed.
Color Customization: Users can choose colors for demand and supply zones, market structure, breakouts, and FVGs.
Dynamic Zone Management: The script allows zones to be deleted after a certain number of bars or dynamically adjusts zones based on recent price action.
Max Zone Count: Limits the number of supply and demand zones shown on the chart to maintain clarity.
Backtesting & Win Rate: The script includes a backtesting engine to calculate the percentage of respect on the interaction between price and demand/supply zones. Results are displayed in a table at the bottom of the chart, showing the percentage rating for both long and short zones. Please note that this is not a win rate of a simulated strategy, it simply is a measure to understand if the current assets tends to respect more supply or demand zones.
How to Use:
Load the script onto your chart. The default settings are optimized for identifying key price action zones and structure on intraday charts of liquid assets.
Customize the settings according to your strategy. For example, adjust the "Max Orderblocks" and "Strength Filter" to focus on more significant price action areas.
Monitor the liquidity grabs, breakouts, and FVGs for potential trade opportunities.
Use the bias and market structure analysis to align your trades with the prevailing market trend.
Refer to the backtesting win rates to evaluate the effectiveness of the zones in your trading.
Terms & Conditions:
By using this script, you agree to the following terms:
Educational Purposes Only: This script is provided for informational and educational purposes and does not constitute financial advice. Use at your own risk.
No Warranty: The script is provided "as-is" without any guarantees or warranties regarding its accuracy or completeness. The creator is not responsible for any losses incurred from the use of this tool.
Open-Source License: This script is open-source and may be modified or redistributed in accordance with the TradingView open-source license. Proper credit to the original creator, OmegaTools, must be maintained in any derivative works.
LIT - Timings Fx MartinThe Asia Liquidity Points Indicator is a powerful tool designed for traders to identify key liquidity points during the Asia trading session. This script is tailored specifically to aid traders in capitalizing on the unique characteristics of Asian markets, providing invaluable insights into liquidity zones that can significantly enhance trading decisions.
Key Features:
Asia Session Focus: The indicator focuses exclusively on the Asia trading session, which encompasses the trading activity primarily in the Asian markets such as Tokyo, Hong Kong, Singapore, and others.
Liquidity Zones Identification: The script utilizes advanced algorithms to identify and map out liquidity zones within the Asia trading session. These zones represent areas where significant buying or selling pressure is likely to occur, thus presenting lucrative trading opportunities.
Customizable Parameters: Traders have the flexibility to customize various parameters such as time frame, sensitivity, and display options to suit their trading preferences and strategies.
Visual Alerts: The indicator provides visual alerts on the trading chart, clearly indicating the location and strength of liquidity points. This feature enables traders to quickly identify potential entry or exit points based on the liquidity dynamics in the market.
Real-Time Updates: The script continuously monitors market activity during the Asia session, providing real-time updates on liquidity points as they evolve. This ensures traders stay informed and adaptable to changing market conditions.
Integration with Trading Strategies: The Asia Liquidity Points Indicator seamlessly integrates with various trading strategies, serving as a valuable tool for both discretionary and algorithmic traders. Whether used in isolation or in combination with other technical analysis tools, this indicator can enhance trading performance and profitability.
User-Friendly Interface: The indicator boasts a user-friendly interface, making it accessible to traders of all levels of experience. Whether you are a novice trader or a seasoned professional, you can easily incorporate this tool into your trading arsenal.
In conclusion, the Asia Liquidity Points Indicator offers traders a strategic advantage in navigating the nuances of the Asia trading session. By identifying key liquidity zones and providing real-time insights, this script empowers traders to make informed decisions and capitalize on lucrative trading opportunities in the dynamic Asian markets.
Support & Resistance PROHi Traders!
The Support & Resistance PRO
A simple and effective indicator that helped me a bunch!
This indicator will chart simple support and resistance zones on 2 time frames of your choice.
It uses a 30 day lookback period and will find the last high and low.
Each zone is built from the highest/lowest closure, and the highest/lowest wick, creating a liquid zone between the 2.
It is perfect for people trading support and resistance, watching key areas, scalping zones and much more!
*You can change the time frames you are looking at and the lookback period.
*The example in the picture is looking at the Daily and Weekly zones on BTC.
Total Turnover Moving Average (TTMA)This is a special type of moving average that incorporates financial information into technical indicators.
CONCEPT:
Number of shares outstanding (NOSH) reflects the floating tickets available for trading in the market. This indicator aims to look at what price has the market transacted on average, given all the NOSH has been turned over.
In order to do this, the number of periods required for trading volume to add up to NOSH is determined. Then, a simple moving average of closing price is calculated based on the number of periods.
Put simply, TTMA is a variable MA indicator, which the parameter depends on trading volume and NOSH. Since every counter has varying NOSH, it also translates volume into liquidity. Given two counters of the same volume , the one with lower NOSH has higher liquidity.
USAGE:
Bullish: when prices are above TTMA
Bearish: when prices are below TTMA
CAVEAT:
Generally works well for mid-cap to large-cap stocks, but not volatile penny counters (just like how you will not use 2-day moving average!). Good as reference and should NOT be used standalone.
CNagda-MomentumX - Institutional FlowMomentumX is designed to empower traders with a deeper understanding of market movements by focusing on Institutional Flow and advanced market structure analytics. The core goal is to identify and visualize where major market participants are operating, and to translate these complex footprints into clear, actionable trading signals โ all in real time.
Real-time institutional activity mapping
Actionable entry and exit signals based on live market structure
Intuitive dashboard and dynamic chart visuals
Fully customizable modules for trend, liquidity, and order blocks
Core Logic Design
At the heart of MomentumX lies a robust algorithmic engine built to capture and surface institutional trading behavior. By leveraging advanced mathematical models, the indicator calculates institutional volume ratios and price momentum to pinpoint aggressive moves from large participants.
Institutional Volume & Price Momentum:
Utilizes custom volume indicators and price change analysis to detect strong buying or selling pressure, filtering out retail noise.
Liquidity Grab Detection & Activity Zones:
The script identifies liquidity grabs by monitoring abrupt price sweeps at major support/resistance levelsโoften where institutions trigger stop hunts or reversals. All critical activity zones are automatically color-coded on the chart for instant recognition.
Dashboard Visualization:
A fully dynamic dashboard table overlays live scores for accumulation, distribution, strength, and weaknessโgiving traders a real-time scan of market health.
Trendline & Order Block Architecture:
The logic auto-detects pivot highs/lows to draw smart trendlines, while the order block system highlights key reversal areas and breaker zonesโmaking market structure clear and actionable.
MomentumX is packed with high-performance modules, each engineered to simplify complex market behavior and enhance decision-making for traders:
Institutional Flow Signals:
Instantly identifies spots where institutional players drive momentum, using unique volume and price activity analytics.
Bullish/Bearish Liquidity Grab Detection:
Marks abrupt price moves that signal stop hunts or reversals, letting traders anticipate snap-backs or trend shifts.
Trendline Auto-Detection:
Smartly draws trendlines based on significant swing highs and lows, automatically adjusting as price evolves.
Order Block System (Rejection/Breaker):
Spots and highlights key reversal zones with order block rectangles, confirming rejections or breakouts at strategic levels.
Dashboard and Bar Coloring:
A clean dashboard overlay presents live market scores, while dynamic bar coloring makes trend, strength, and high-activity periods instantly visible.
User Input Toggles for Each Module:
Every major feature is fully customizableโenable or disable modules to match individual trading setups or preferences.
Scripting/Development
MomentumXโs scripting process is modular, enabling clarity, scalability, and fast optimization throughout development:
Initialization & Inputs:
Start by defining all user input options, module toggles, color settings, and calculation parametersโensuring maximum flexibility early on.
Core Calculation Functions:
Script advanced institutional volume and price momentum algorithms. Build out swing length logic, market state filters, and activity scoring methods.
Detection Engines:
Develop and integrate engines for liquidity grabs, automated trendline detection, and order block identificationโeach with dedicated functions for speed and precision.
Visual Overlays & Plotting:
Implement powerful plotting logic for colored bars, score dashboards, trendlines, reversal zones, and liquidity markersโmaking every data point clear and actionable on the chart.
Testing Handlers:
Add diagnostic panels and debug outputs to refine calculations and assure accuracy in every market environment.
Sample Trade Setups (Usage)
Cnagda MomentumX delivers clarity for multiple trading styles by providing timely, actionable setups grounded in institutional behavior and market structure. Hereโs how traders can leverage the indicator for confident decision-making:
Liquidity Grab Reversal
Enter trades around detected liquidity grabs when price sweeps major support/resistance and the dashboard signals a momentum shift.
Example: Wait for a bullish/Bearish grab near market lows/high, with institutional flow turning positive/negativeโenter long/short for potential mean reversion.
Order Block Breakout
Trade breakouts when price cleanly rejects or flips key order block zones highlighted on the chart.
Example: Short at a marked breaker block after a rejection signal, confirmed by a downward institutional activity spike.
Trendline Continuation
Ride established market moves by entering on trendline confirmations plotted by the auto-detect system.
Example: Go long after a trendline retest, confirmed by a green bar color and dashboard strength score.
Dashboard Confirmation
Combine dashboard metrics (strength, accumulation, distribution) with bar color overlays for multi-factor entries.
Example: Enter trades only when all market signals align in real time for maximum probability.
For Short Entry check -- Weakness : For Long Entry Check - Strength With Other Indications
MomentumX is not just another indicator โ itโs your edge for reading the market like an insider. By transparently mapping institutional flow, uncovering hidden liquidity zones, and color-coding every major structure shift, MomentumX transforms complexity into actionable clarity. Whether youโre scalping, swing trading, or investing, youโll gain a decisive, real-time advantage on every chart.
Embrace smarter decisions, adapt to changing market conditions instantly, and join a new generation of technically empowered traders.
Customize, observe, and let the market reveal opportunities in a way youโve never experienced before.
Happy Trading
CMC Macro Regime PanelOverview (what it is):
A macroโregime gate built entirely from TradingView-native symbols (CRYPTOCAP, FRED, DXY/VIX, HYG/LQD). It aggregates centralโbank liquidity (Fed balance sheet โ RRP โ Treasury General Account), USD strength, credit conditions, stablecoin flows/dominance, tech beta and BTCโNDX coโmove into one normalized score (CLRC). The panel outputs RiskโON/OFF regimes, an Early 3/5 preโsignal, and an automatic BTC vs ETH vs ALTs preference. It is intentionally scoped to Daily & Weekly reads (no intraday timing). Publish with a clean chart and a clear description as per TradingView rules.
TradingView
Why we also use other TradingView screens (and why that is compliant)
This script pulls data via request.security() from official TV symbols only; users often want to open the raw series on separate charts to sanityโcheck:
CRYPTOCAP indices: TOTAL, TOTAL2, TOTAL3 (market cap aggregates) and dominance tickers like BTC.D, USDT.D. Helpful for regime & rotation (ALTs vs BTC). TradingView provides definitions for crypto market cap and dominance symbols.
TradingView
+3
TradingView
+3
TradingView
+3
FRED releases: WALCL (Fed assets, weekly), RRPONTSYD (ON RRP, daily), WTREGEN (TGA, weekly), M2SL (M2, monthly). These are the official macro sources exposed on TV.
FRED
+3
FRED
+3
FRED
+3
Risk proxies: TVC:DXY (USD index), TVC:VIX (implied vol), AMEX:HYG/AMEX:LQD (credit), NASDAQ:NDX (tech beta), BINANCE:ETHBTC. VIX/NDX relationship is well-documented; VIX measures 30โday expected S&P500 vol.
TradingView
+2
TradingView
+2
Compliance note: Using multiple screens is optional for users, but it explains/justifies how components work together (a requirement for public scripts). Keep publication chart clean; use extra screens only to illustrate in the description.
TradingView
How it works (high level)
Liquidity block (Weekly/Monthly)
Net Liquidity = WALCL โ RRPONTSYD โ WTREGEN (YoY zโscore). WALCL is weekly (as of Wednesday) via H.4.1; RRP is daily; TGA is a Fed liability series. M2 YoY is monthly.
FRED
+3
FRED
+3
FRED
+3
Risk conditions (Daily)
DXY 3โmonth momentum (inverted), VIX level (inverted), Credit (HYG/LQD ratio or HY OAS). VIX is a 30โday constantโmaturity implied vol index per Cboe methodology.
Cboe
+1
Cryptoโinternal (Daily)
Stablecoins (USDT+USDC+DAI 30โday log change), USDT dominance (20โday, inverted), TOTAL3 (63โday momentum). Dominance symbols on TV follow a documented formula.
TradingView
Beta & coโmove (Daily)
NDX 63โday momentum, BTCโNDX 90โday correlation.
All components become zโscores (optionally clipped), weighted, missing inputs drop and weights renormalize. We never use lookahead; we confirm on bar close to avoid repainting per Pine docs (barstate.isconfirmed, multiโTF).
TradingView
+2
TradingView
+2
What you see on the chart
White line (CLRC) = macro regime score.
Background: Green = RiskโON, Red = RiskโOFF, Teal = Early 3/5 (preโsignal).
Table: shows each componentโs zโscore and the Preference: BTC / ETH / ALTs / Mixed.
Signals & interpretation
Designed for Daily (1D) and Weekly (1W) only.
Regime gates (default Fast preset):
Enter ON: CLRC โฅ +0.8; Hold ON while โฅ +0.5.
Enter OFF: CLRC โค โ1.0; Hold OFF while โค โ0.5.
0 / ยฑ1 reading: CLRC is a standardized composite.
~0 = neutral baseline (no macro edge).
โฅ +1 = strong macro tailwind (โ +1ฯ).
โค โ1 = strong headwind (โ โ1ฯ).
Early 3/5 (teal): a fast preโsignal when at least 3 of 5 daily checks align: USDT.Dโ, DXYโ, VIXโ, HYG/LQDโ, ETHBTCโ or TOTAL3โ. It often precedes a full ON flipโuse for preโpositioning rather than full sizing.
BTC/ETH/ALTs selector (only when ON):
ALTs when BTC.Dโ and (ETHBTCโ or TOTAL3โ) โ rotate down the risk curve.
BTC when BTC.Dโ and ETHBTCโ โ keep it concentrated.
ETH when ETHBTCโ while BTC.D flat/up โ add ETH beta.
(Dominance mechanics are documented by TV.)
TradingView
Dissonance (incompatibility) rules โ when to stand down
Use these overrides to avoid false comfort:
CLRC > +1 but USDT.Dโ and/or VIX spikes dayโoverโday โ downgrade to Neutral; wait for USDT.D to stabilize and VIX to cool (VIX is a fear gauge of 30โday expectation).
Cboe Global Markets
CLRC > +1 but DXYโ sharply (USD squeeze) โ size below normal; require DXY momentum to roll over.
CLRC < โ1 but Early 3/5 = true two days in a row โ start reducing underweights; look for ON flip within a few bars.
NetLiq improving (W) but credit (HYG/LQD) deteriorating (D) โ treat as mixed regime; prefer BTC over ALTs.
How to use (stepโbyโstep)
A. Read on Daily (1D) โ main regime
Open CRYPTOCAP:TOTAL3, 1D (panel applied).
Wait for bar close (use alerts on confirmed bar). Pine docs recommend barstate.isconfirmed to avoid repainting on realtime bars.
TradingView
If ON, check Preference (BTC / ETH / ALTs).
Then drop to 4H on your trading pair for micro entries (this indicator itself is not for intraday timing).
B. Confirm weekly macro (1W) โ once per week)
Review WALCL/RRP/TGA after the H.4.1 release on Thursdays ~4:30 pm ET. WALCL is โWeekly, as of Wednesdayโ; M2 is Monthlyโso do not expect daily responsiveness from these.
Federal Reserve
+2
FRED
+2
Recommended check times (practical schedule)
Daily regime read: right after your chartโs daily close (confirmed bar). For consistent timing across crypto, many users set chart timezone to UTC and read ~00:05 UTC; you can change chart timezone in TVโs settings.
TradingView
Inโday monitoring: optional spot checks 16:00 & 20:00 UTC (DXY/VIX move during US hours), but act only after the daily bar confirms.
Weekly macro pass: Thu 21:30โ22:30 UTC (after H.4.1 4:30 pm ET) or Fri after daily close, to let weekly FRED series propagate.
Federal Reserve
Limitations & data latency (be explicit)
HigherโTF data & confirmation: FRED weekly/monthly series will not reflect intraday risk in crypto; we aggregate them for regime, not for entry timing.
Repainting 101: Realtime bars move until close. This script does not use lookahead and follows Pine guidance on multiโTF series; still, always act on confirmed bars.
TradingView
+1
Publicโlibrary compliance: Title ENโonly; description starts in EN; clean chart; justify component mashโup; no lookahead; no unrealistic claims.
TradingView
Alerts you can use
โMacro RiskโON (entry)โ โ fires on ON flip (confirmed bar).
โMacro RiskโOFF (entry)โ โ fires on OFF flip.
โEarly 3/5โ โ fires when the teal preโsignal appears (not a regime flip).
โPreference changeโ โ BTC/ETH/ALTs toggles while ON.
Publish note: Alerts are fine; just avoid implying guaranteed accuracy/performance.
TradingView
Background research (why these inputs matter)
Liquidity โ Crypto: Fed H.4.1 timing and series definitions (WALCL, RRP, TGA) formalize the โnet liquidityโ concept used here.
FRED
+3
Federal Reserve
+3
FRED
+3
Stablecoins โ Nonโstable crypto: empirical work shows biโdirectional causality between stablecoin market cap and nonโstable crypto cap; stablecoin growth coโmoves with broader crypto activity.
Global liquidity link: world liquidity positively relates to total crypto market cap; lagged effects are observed at monthly horizons.
VIX/Uncertainty effect: fear shocks impair BTCโs โsafe havenโ behavior; VIX is a meaningful riskโoff read.
Multipower Entry SecretMultipower Entry Secret indicator is designed to be the ultimate trading companion for traders of all skill levelsโespecially those who struggle with decision-making due to unclear or overwhelming signals. Unlike conventional trading systems cluttered with too many lines and confusing alerts, this indicator provides a clear, adaptive, and actionable guide for market entries and exits.
Key Points:
Clear Buy/Sell/Wait Signals:
The script dynamically analyzes price action, candle patterns, volume, trend strength, and higher time frame context. This means it gives you โBuy,โ โSell,โ or โWaitโ signals based on real, meaningful market informationโfiltering out the noise and weak trades.
Multi-Timeframe Adaptive Analysis:
It synchronizes signals between higher and current timeframes, ensuring you get the most reliable directionโreducing the risk of getting caught in fake moves or sudden reversals.
Automatic Support, Resistance & Liquidity Zones:
Key levels like support, resistance, and liquidity zones are auto-detected and displayed directly on the chart, helping you make precise decisions without manual drawing.
Real-Time Dashboard:
All relevant information, such as trend strength, market intent, volume sentiment, and the reason behind each signal, is neatly summarized in a dashboardโmaking monitoring effortless and intuitive.
Customizable & Beginner-Friendly:
Whether youโre a newcomer wanting straightforward guidance or a professional needing advanced customization, the indicator offers flexible options to adjust analysis depth, timeframes, sensitivity, and more.
Visual & Clutter-Free:
The design ensures that your chart remains clean and readable, showing only the most important information. This minimizes mental overload and allows for instant decision-making.
Who Will Benefit?
Beginners who want to learn trading logic, avoid common traps, and see the exact reason behind every signal.
Advanced traders who require adaptive multi-timeframe analytics, fast execution, and stress-free monitoring.
Anyone who wants to save screen time, reduce analysis paralysis, and have more confidence in every trade they take.
1. No Indicator Clutter
Intent:
Many traders get confused by charts filled with too many indicators and signals. This often leads to hesitation, missed trades, or taking random, risky trades.
In this Indicator:
You get a clean and clutter-free chart. Only the most important buy/sell/wait signals and relevant support/resistance/liquidity levels are shown. These update automatically, removing the โoverloadโ and keeping your focus sharp, so your decision-making is faster and stress-free.
2. Exact Entry Guide
Intent:
Traders often struggle with entry timing, leading to FOMO (fear of missing out) or getting trapped in sudden market reversals.
In this Indicator:
The system uses powerful adaptive logic to filter out weak signals and only highlight the strongest market moves. This not only prevents you from entering late or on noise, but also helps avoid losses from false breakouts or whipsaws. You get actionable suggestionsโwhen to enter, when to hold backโso your entries are high-conviction and disciplined.
3. HTF+LTF Logic: Multitimeframe Sync Analysis
Intent:
Most losing trades happen when you act only on the short-term chart, ignoring the bigger market trend.
In this Indicator:
Signals are based on both the current chart timeframe (LTF) and a higher (HTF, like hourly/daily) timeframe. The indicator synchronizes trend direction, momentum, and structure across both levels, quickly adapting to show you when both are aligned. This filtering results in โonly trade with the bigger trendโโdramatically increasing your win rate and market confidence.
4. Auto Support/Resistance & Liquidity Zones
Intent:
Drawing support/resistance and liquidity zones manually is time-consuming and error-prone, especially for beginners.
In this Indicator:
The system automatically identifies and plots the most crucial support/resistance levels and liquidity zones on your chart. This is based on adaptive, real-time price and volume analysis. These zones highlight where major institutional activity, trap setups, or real breakouts/reversals are most likely, removing guesswork and giving you a clear reference for entries, exits, and stop placements.
5. Clear Action/Direction
Intent:
Traders need certaintyโwhat does the market want right now? Most indicators are vague.
In this Indicator:
Your dashboard always displays in plain words (like โBUYโ, โSELLโ, or โWAITโ) what action makes sense in the current market phase. Whether itโs a bull trap, volume spike, wick reversal, or exhaustionโitโs interpreted and explained clearly. No more confusionโjust direct, real-time advice.
6. For Everyone (Beginner to Pro)
Intent:
Most advanced indicators are overwhelming for new traders; simple ones lack depth for professionals.
In this Indicator:
It is simple enough for a beginnerโjust add it to the chart and instantly see what action to consider. At the same time, it includes advanced adaptive analysis, multi-timeframe logic, and customizable settings so professional traders can fine-tune it for their strategies.
7. Ideal Usage and User Benefits
Instant Decision Support:
Whenever youโre unsure about a trade, just look at the indicatorโs suggestion for clarity.
Entry Learning:
Beginners get real-time โpracticeโ by not only seeing signals, but also the reason behind themโimproving your chart reading and market understanding.
Screen Time & Stress Reduction:
Clear, relevant information only; no noise, less fatigue, faster decisions.
Makes Trading Confident & Simple:
The smart dashboard splits actionable levels (HTF, LTF, action) so you never miss a move, avoid traps, and stay aligned with high-probability trades.
8. Advanced Input Settings (Smart Customization)
Explained with Examples:
Enable Wick Analysis:
Finds candles with strong upper/lower wicks (signs of rejection/buying/selling force), alerting you to hidden reversals and protecting from FOMO entries.
Enable Absorption:
Detects when heavy order flow from one side is โabsorbedโ by the other (shows where institutional buyers/sellers are likely active, helps spot fake breakouts).
Enable Unusual Breakout:
Highlights real breakoutsโlarge volatility plus high volumeโso you catch genuine moves and avoid random spikes.
Enable Range/Expansion:
Smartly flags sudden range expansionsโwhen the market goes from quiet to volatileโso you can act at the start of real trends.
Trend Bar Lookback:
Adjusts how many bars/candles are used in trend calculations. Short (fast trades, more signals), long (more reliability, fewer whipsaws).
Bull/Bear Bars for Strong Trend Min:
Sets how many candles in a row must support a trend before calling it โstrongโโprevents flipping signals, keeps you disciplined.
Volume MA Length:
Lets you adjust how many bars back volume is averagedโfine-tune for your asset and trading style for best volume signals.
Swing Lookback Bars:
Set how many bars to use for swing high/low detectionโshort (quick swing levels), long (stronger support/resistance).
HTF (Bias Window):
Decide which higher timeframe the indicator should use for big-picture market mood. Adjustable for any style (scalp, swing, position).
Adaptive Lookback (HTF):
Choose how much HTF history is used for detecting major extremes/zones. Quick adjust for more/less sensitivity.
Show Support/Resistance, Liquidity Zones, Trendlines:
Toggle them on/off instantly per your needsโkeeps your chart relevant and tailored.
9. Live Dashboard Sections Explained
Intent HTF:
Shows if the bigger timeframe currently has a Bullish, Bearish, or Neutral (โChopโ) intent, based on strict volume/price body calculations. Instant clarityโno more guessing on trend bias.
HTF Bias:
Clear message about which side (buy/sell/sideways) controls the market on the higher timeframe, so you always trade with the โbig money.โ
Chart Action:
The central action for the current barโWhether to Buy, Sell, or Waitโcalculated from all indicator logic, not just one rule.
TrendScore Long/Short:
See how many candles in your chosen window were bullish or bearish, at a glance. Instantly gauge market momentum.
Reason (WHY):
Every time a signal appears, the โreasonโ cell tells you the primary logic (breakout, wick, strong trend, etc.) behind it. Full transparency and learningโnever trade blindly.
Strong Trend:
Shows if the market is currently in a powerful trend or notโhelping you avoid choppy, risky entries.
HTF Vol/Body:
Displays current higher timeframe volume and candle body %โhelping spot when big players are active for higher probability trades.
Volume Sentiment:
A real-time analysis of market psychology (strong bullish/bearish, neutral)โmaking your decision-making much more confident.
10. Smart and User-Friendly Design
Multi-timeframe Adaptive:
All calculations can now be drawn from your choice of higher or current timeframe, ensuring signals are filtered by larger market context.
Flexible Table Position:
You can set the live dashboard/summary anywhere on the chart for best visibility.
Refined Zone Visualization:
Liquidity and order blocks are visually highlighted, auto-tuning for your settings and always cleaning up to stay clutter-free.
Multi-Lingual & Beginner Accessible:
With Hindi and simple English support, descriptions and settings are accessible for a wide audienceโanyone can start using powerful trading logic with zero language barrier.
Efficient Labels & Clear Reasoning:
Signal labels and reasons are shown/removed dynamically so your chart stays informative, not messy.
Every detail of this indicator is designed to make trading both simpler and smarterโhelping you avoid the common pitfalls, learn real price action, stay in sync with the marketโs true mood, and act with discipline for higher consistency and confidence.
This indicator makes professional-grade market analysis accessible to everyone. Itโs your trusted assistant for making smarter, faster, and more profitable trading decisionsโproviding not just signals, but also the โwhyโ behind every action. With auto-adaptive logic, clear visuals, and strong focus on real trading needs, it lets you focus on capturing the moves that matterโevery single time.
ICT Sweep + FVG Entry (v6) โข Pro Pack ๐ ICT Sweep + FVG Entry Pro Pack
This indicator combines key ICT price action concepts with practical execution tools to help traders spot high-probability setups faster and more objectively. Itโs designed for scalpers and intraday traders who want to keep their chart clean but never miss critical market structure events.
๐ Features
Liquidity Pools (HTF)
โข Auto-detects recent swing highs/lows from higher timeframes (5m/15m).
โข Draws both lines and optional rectangles/zones for clear liquidity areas.
Liquidity Sweeps (BSL/SSL)
โข Identifies when price sweeps above/below liquidity pools and rejects back.
โข Optional Grade-A sweep filter (wick size + strong re-entry).
Fair Value Gaps (FVGs)
โข Highlights bullish/bearish imbalances.
โข Optional midline (50%) entry for precision.
โข Auto-invalidation when price fully closes inside the gap.
Killzones (New York)
โข Highlights AM (9:30โ11:30) and PM (14:00โ15:30) killzones.
โข Option to block signals outside killzones for higher strike rate.
Bias Badge (DR50)
โข Displays if price is trading in a Bull, Bear, or Range context based on displacement range midpoint.
SMT Assist (NQ vs ES)
โข Detects simple divergences between indices:
Bearish SMT โ NQ makes HH while ES doesnโt.
Bullish SMT โ NQ makes LL while ES doesnโt.
SL/TP Helper & R:R Label
โข Automatically draws stop loss (at sweep extreme) and target (opposite pool or recent swing).
โข Displays expected Risk:Reward ratio and blocks entries if below your chosen minimum.
Filters
โข ATR filter ensures signals only appear in sufficient volatility.
โข Sweep quality filter avoids weak wicks and fake-outs.
๐ฏ How to Use
Start on HTF (5m/15m) โ Identify liquidity zones and bias.
Drop to LTF (1m) โ Wait for a liquidity sweep confirmation.
Check for FVG in the sweepโs direction โ Look for retest entry.
Use the SL/TP helper to validate your risk/reward before taking the trade.
Focus entries during NY Killzones for maximum effectiveness.
โ
Why this helps
This tool reduces screen time and hesitation by automating repetitive ICT concepts:
Liquidity pools, sweeps, and FVGs are marked automatically.
Killzone timing and SMT divergence are simplified.
Clear visual signals for entries with built-in RR filter help keep your trading mechanical.
โ ๏ธ Disclaimer: This script is for educational purposes only. It does not provide financial advice or guarantee results. Always use proper risk management.
ICT Sweep + FVG Entry (v6) โข Antoine๐ ICT Sweep + FVG Entry (Antoine)
This indicator is designed for price action traders who follow ICT concepts and want a mechanical tool to spot liquidity sweeps, fair value gaps (FVGs), and precise entry signals.
๐ Key Features
Liquidity Pools (HTF)
โข Automatically plots recent swing highs/lows from a higher timeframe (5m/15m).
โข These act as Buy Side Liquidity (BSL) and Sell Side Liquidity (SSL) levels where stop orders accumulate.
Sweep Detection
โข Identifies when price breaks a pool (BSL/SSL) but closes back inside โ a classic liquidity grab.
โข Plots a triangle on the chart when a sweep is confirmed.
Fair Value Gap (FVG) Highlighting
โข Detects bullish and bearish FVGs on the execution timeframe (ideal for 1m).
โข Option to display active FVG zones with shaded boxes.
Entry Signals
โข A signal (cross) appears when:
A liquidity sweep occurs.
An FVG forms in the direction of the rejection.
Price retests the FVG (entry at the 50% mid-level or edge).
Alerts Ready
โข Get alerted for sweeps (bullish/bearish) and for entry confirmations (long/short FVG retests).
๐ฏ How to Use
Choose your HTF (5m or 15m) โ The indicator maps major liquidity pools.
Drop to LTF (1m) โ Wait for a sweep signal at one of the pools.
Confirm with FVG โ If an FVG appears in the sweepโs direction, the indicator waits for a retest.
Entry โ Enter on the retest of the FVG (edge or 50%).
Risk Management
Stop loss: just beyond the sweepโs wick.
Target: opposite liquidity pool.
Minimum recommended R:R: 1:2.
โ
Why this helps
This tool makes it easier to trade ICT-style setups without missing opportunities:
No need to manually draw every swing high/low.
Automatic FVG detection saves time.
Clear sweep + FVG + retest logic keeps your entries mechanical and disciplined.
โ ๏ธ Disclaimer: This script is for educational purposes only. It does not guarantee profits. Always use proper risk management.
Smart Money Trades Pro [BOSWaves]Smart Money Trades Pro โ Advanced Market Structure & Liquidity Visualizer
Overview
Smart Money Trades Pro is a comprehensive trading tool designed for traders seeking an in-depth understanding of market structure, liquidity dynamics, and institutional flow. The indicator systematically identifies key market turning points, including break of structure (BOS) and change of character (CHoCH) events, and overlays these with adaptive visualizations to highlight high-probability trade setups. By integrating ATR-based risk zones, progressive take-profit levels, and real-time trade analytics, Smart Money Trades Pro transforms complex price action into an interpretable framework suitable for multiple trading styles, including scalping, intraday, and swing trading.
Unlike traditional static indicators, Smart Money Trades Pro adapts continuously to market conditions. It evaluates swing highs and lows over a configurable lookback period, then determines structural breaks using customizable confirmation methods (candle body or wick). The resulting signals are augmented with dynamic entry, stop-loss, and target levels, allowing traders to analyze potential trade opportunities with both precision and context. The indicatorโs design ensures that each visual elementโtrend-colored candles, signal markers, and risk/reward boxesโreflects real-time market conditions, offering an actionable interpretation of institutional activity.
How It Works
The indicatorโs foundation is built upon market structure analysis. By calculating pivot highs and lows over a specified period, Smart Money Trades Pro identifies potential points of liquidity accumulation and exhaustion. When price breaks a pivot high or low, the indicator evaluates whether this constitutes a BOS or a CHoCH, signaling trend continuation or reversal. These events are marked on the chart with distinct visual cues, allowing traders to quickly discern shifts in market sentiment without manually analyzing historical price action.
Once a structural break is confirmed, the indicator automatically determines entry levels, stop-loss placements, and progressive take-profit zones (TP1, TP2, TP3). These calculations are based on ATR-derived volatility, ensuring that targets scale with current market conditions. Risk and reward zones are plotted as shaded boxes, providing a clear visual representation of potential profit relative to risk for each trade setup. This system allows traders to maintain discipline and consistency, with dynamic trade management baked directly into the visualization.
Trend direction is further reinforced by color-coded candles, which reflect the prevailing market bias. Bullish trends are represented by one color, bearish trends by another, and neutral conditions are displayed in muted tones. This continuous visual feedback simplifies the process of trend assessment and helps confirm the validity of trade setups alongside BOS and CHoCH markers.
Signals and Breakouts
Smart Money Trades Pro includes structured visual signals to indicate actionable price movements:
Bullish Break Signals โ Triangular markers below the candle appear when a swing high is broken, suggesting potential long opportunities.
Bearish Break Signals โ Triangular markers above the candle appear when a swing low is broken, indicating potential short setups.
Change of Character (CHoCH) โ Special markers highlight trend reversals, showing where momentum shifts from bullish to bearish or vice versa.
These markers are strategically spaced to prevent overlap and remain clear during high-volatility periods. Traders can use them in combination with trend-colored candles, risk/reward zones, and ATR-based targets to assess the strength and reliability of each setup. The integrated table provides live trade information, including entry price, stop-loss level, take-profit levels, risk/reward ratio, and trade direction, ensuring that trade decisions are informed and data-driven.
Interpretation
Trend Analysis : The indicatorโs trend coloring, combined with BOS and CHoCH detection, provides an immediate view of market direction. Rising structures indicate bullish momentum, while falling structures signal bearish momentum. CHoCH markers highlight potential trend reversals or significant liquidity sweeps.
Volatility and Risk Assessment : ATR-based calculations determine stop-loss distances and target levels, giving a quantitative measure of risk relative to market volatility. Wide ATR readings indicate periods of high price fluctuation, whereas narrow readings suggest consolidation and reduced risk exposure.
Market Structure Insights : By monitoring swing highs and lows alongside break confirmations, traders can identify where institutional players are likely active. Areas with multiple structural breaks or overlapping targets can indicate liquidity hotspots, potential reversal zones, or areas of market congestion.
Trade Management : The built-in trade zones allow traders to visualize entry, risk, and reward simultaneously. Progressive targets (TP1, TP2, TP3) reflect incremental profit-taking strategies, while dynamic stop-loss levels help preserve capital during adverse moves.
Strategy Integration
Smart Money Trades Pro supports a range of trading approaches:
Trend Following : Enter trades in the direction of confirmed BOS while using CHoCH markers and trend-colored candles to validate momentum.
Pullback Entries : Use failed breakout retests or minor reversals toward broken structure levels for lower-risk entries.
Mean Reversion : In consolidated zones with narrow ATR and repeated BOS/CHoCH activity, anticipate reversals or short-term corrective moves.
Multi-Timeframe Confirmation : Overlay signals on higher or lower timeframes to filter noise and improve trade accuracy.
Stop-loss levels should be placed just beyond the opposing structural point, while take-profit targets can be scaled using the ATR-based zones. Progressive targets allow for partial exits or scaling out of trades while maintaining exposure to larger moves.
Advanced Techniques
Traders seeking greater precision can combine Smart Money Trades Pro with volume, momentum, or volatility indicators to validate signals. Observing sequences of BOS and CHoCH markers across multiple timeframes provides insight into liquidity accumulation and depletion trends. Tracking the expansion or contraction of ATR-based zones helps anticipate shifts in volatility, enabling better timing for entries and exits.
Customizing the structure period and confirmation type allows the indicator to adapt to different asset classes and timeframes. Shorter periods increase sensitivity to smaller swings, while longer periods filter noise and emphasize higher-probability structural breaks. By integrating these features, the indicator offers a robust statistical framework for disciplined, data-driven trading decisions.
Inputs and Customization
Structure Detection Period : Defines the lookback window for pivot high and low calculation.
Break Confirmation : Choose whether to confirm breaks using candle body or wick.
Display CHoCH : Toggle visibility of change-of-character markers.
Color Trend Bars : Enable color-coding of candles based on market structure direction.
Show Info Table : Display trade dashboard showing entry, stop-loss, take-profits, risk/reward, and bias.
Table Position : Choose from top-left, top-right, bottom-left, or bottom-right placement.
Color Customization : Configure bullish, bearish, neutral, risk, reward, and text colors for enhanced visual clarity.
Why Use Smart Money Trades Pro
Smart Money Trades Pro transforms complex market behavior into an actionable visual framework. By combining market structure analysis, liquidity tracking, ATR-based risk/reward mapping, and a dynamic trade dashboard, it provides a multidimensional view of the market. Traders can focus on execution, interpret trends, and evaluate overextensions or reversals without relying on guesswork. The indicator is suitable for scalping, intraday, and swing strategies, offering a comprehensive system for understanding and trading alongside institutional participants.
UNITY[ALGO] PO3 V3Of course. Here is a complete and professional description in English for the indicator we have built, detailing all of its features and functionalities.
Indicator: UNITY PO3 V7.2
Overview
The UNITY PO3 is an advanced, multi-faceted technical analysis tool designed to identify high-probability reversal setups based on the Swing Failure Pattern (SFP). It combines real-time SFP detection on the current timeframe with a sophisticated analysis of key institutional liquidity zones from the H4 timeframe, presenting all information in a clear, dynamic, and interactive visual interface.
This indicator is built for traders who use liquidity concepts, providing a complete dashboard of entries, targets, and invalidation levels directly on the chart.
Core Features & Functionality
1. Swing Failure Pattern (SFP) Detection (Current Timeframe)
The indicator's primary engine identifies SFPs on the chart's active timeframe with two layers of logic:
Standard SFP: Detects a classic liquidity sweep where the current candle's wick takes out the high or low of the previous candle and the body closes back within the previous candle's range.
Outside Bar SFP Logic: Intelligently analyzes engulfing candles that sweep both the high and low of the previous candle. A valid signal is only generated if the candle has a clear directional close:
Bullish Signal: If the outside bar closes higher than its open.
Bearish Signal: If the outside bar closes lower than its open.
Neutral (doji-like) outside bars are ignored to filter for indecision.
2. Comprehensive On-Chart SFP Markings
When a valid SFP is detected, a full suite of dynamic drawings appears on the chart:
Failure Line: A dashed line (red for bearish, green for bullish) marking the precise price level of the liquidity sweep.
PREMIUM ZONE (SFP Candle Wick): A transparent, colored rectangle highlighting the rejection wick of the signal candle (the upper wick for bearish SFPs, the lower wick for bullish SFPs). This zone automatically extends to the right, following the current price, until the DOL is hit.
CRT BOX (Reference Candle): A transparent box with a colored border drawn around the entire range of the candle that was swept (Candle 1). This highlights the full liquidity zone and also extends dynamically until the DOL is hit.
Dynamic Target Line: A blue dashed line marking the primary objective (the low of the signal candle for shorts, the high for longs).
The line begins with a "โณ Target" label and extends with the current price.
Upon being touched by price, the line freezes, and its label permanently changes to "โ
Target".
Dynamic DOL (Draw on Liquidity) Line: An orange dashed line marking the invalidation level, defined as the opposite extremity of the swept candle (Candle 1).
It begins with a "โณ dol" label and extends with the price.
Upon being touched, it freezes, and its label changes to "โ
dol".
3. Multi-Session Killzone Liquidity Levels (H4 Analysis)
The indicator automatically analyzes the H4 timeframe in the background to identify and plot key liquidity levels from three major trading sessions, based on their UTC opening times.
1am Killzone (London Lunch): Tracks the high/low of the 05:00 UTC H4 candle.
5am Killzone (London Open): Tracks the high/low of the 09:00 UTC H4 candle.
9am Killzone (NY Open): Tracks the high/low of the 13:00 UTC H4 candle.
For each of these Killzones, the indicator provides two types of analysis:
Last KZ Lines: Plots the high and low of the most recent qualifying Killzone candle. These lines are dynamic, extending with price and showing a โณ/โ
status when touched.
Fresh Zones: A powerful feature that scans the entire available history of Killzones to find and display the closest untouched high (above the current price) and the closest untouched low (below the current price). These "Fresh" lines are also fully dynamic and provide a real-time view of the most relevant nearby liquidity targets.
4. Advanced User Settings & Chart Management
The indicator is designed for a clean and user-centric experience with powerful customization:
Show Only Last SFP: Keeps the chart clean by automatically deleting the previous SFP setup when a new one appears.
Hide SFP on DOL Reset: When checked, automatically removes all drawings related to an SFP setup the moment its invalidation level (DOL line) is touched. This leaves only active, valid setups on the chart.
Hide Consumed KZ: When checked, automatically removes any Killzone or Fresh Zone line from the chart as soon as it is touched by the price.
Independent Toggles: Every visual elementโSFP signals, each of the three Killzones, and their respective "Fresh" zone counterpartsโcan be turned on or off independently from the settings menu for complete control over the visual display.
Z-Order Priority: All indicator drawings are rendered in front of the chart candles, ensuring they are always clearly visible and never hidden from view.
TCP | Market Session | Session Analyzer๐ TCP | Market Session Indicator | Crypto Version
A powerful, real-time market session visualization tool tailored for crypto traders. Track the heartbeat of Asia, Europe, and US trading hours directly on your chart with live session boxes, behavioral analysis, liquidity grab detection, and countdown timers. Know when the action starts, how the market behaves, and where the traps lie.
๐ฐ Introduction:
Trade the Right Hours with the Right Tools
Time matters in trading. Most significant moves happen during key sessionsโand knowing when and how each session unfolds can give you a sharp edge. The TCP Market Session Indicator, developed by Trade City Pro (TCP), puts professional session tracking and behavioral insights at your fingertips.
Whether you're a scalper or swing trader, this indicator gives you the timing context to enter and exit trades with greater confidence and clarity.
๐ Core Features
โข Live Session Boxes :
Highlight active ranges during Asia, Europe, and US sessions with dynamic high/low updates.
โข Session Start/End Labels :
Know exactly when each session begins and ends plotted clearly on your chart with context.
โข Session Behavior Analysis :
At the end of each session, the indicator classifies the price action as:
- Trend Up
- Trend Down
- Consolidation
- Manipulation
โข Liquidity Grab Detection: Automatically detects possible stop hunts (fake breakouts) and marks them on the chart with precision filters (volume, ATR, reversal).
โข Session Countdown Table: A live dashboard showing:
- Current active session
- Time left in session
- Upcoming session and how many minutes until it starts
- Utility time converter (e.g. 90 min = 01:30)
โข Vertical Session Lines: Visualize past and upcoming session boundaries with customizable history and future range.
โข Multi-Day Support: Draw session ranges for previous, current, and future days for better backtesting and forecasting.
โ๏ธ Settings Panel
Customize everything to fit your trading style and schedule:
โข Session Time Settings:
Set the opening and closing time for each session manually using UTC-based minute inputs.
โ For example, enter Asia Start: 0, Asia End: 480 for 00:00โ08:00 UTC.
This gives full flexibility to adjust session hours to match your preferred market behavior.
โข Enable or Disable Elements:
Toggle the visibility of each session (Asia, Europe, US), as well as:
- Session Boxes
- Countdown Table
- Session Lines
- Liquidity Grab Labels
โข Timezone Selection:
Choose between using UTC or your chartโs local timezone for session calculations.
โข Customization Options:
Select number of past and future days to draw session data
Adjust vertical line transparency
Fine-tune label offset and spacing for clean layout
๐ Smart Session Boxes
Each session box tracks high, low, open, and close in real time, providing visual clarity on market structure. Once a session ends, the box closes, and the behavior type is saved and labeled ideal for spotting patterns across sessions.
โข Asia: Green Box
โข Europe: Orange Box
โข US: Blue Box
๐ก Why Use This Tool?
โข Perfect Timing: Donโt get chopped in low-liquidity hours. Focus on sessions where volume and volatility align.
โข Pattern Recognition: Study how price behaves session-to-session to build better strategies.
โข Trap Detection: Spot manipulation moves (liquidity grabs) early and avoid common retail pitfalls.
โข Macro Session Mapping: Use as a foundational layer to align trades with market structure and news cycles.
๐ Example Use Case
You're watching BTC at 12:45 UTC. The indicator tells you:
The Asia session just ended (label shows โAsia Session End: Trend Upโ)
Europe session starts in 15 minutes
A liquidity grab just triggered at the previous highโlabel confirmed
Now you know whoโs active, what the market just did, and whatโs about to startโall in one glance.
โ
Why Traders Trust It
โข Visual & Intuitive: Fully chart-based, no clutter, no guessing
โข Crypto-Focused: Designed specifically for 24/7 crypto markets (not outdated forex models)
โข Non-Repainting: All labels and boxes stay as printedโno tricks
โข Reliable: Tested across multiple exchanges, pairs, and timeframes
๐งฉ Built by Trade City Pro (TCP)
The TCP Market Session Indicator is part of a suite of professional tools used by over 150,000 traders. Itโs coded in Pine Script v6 for full compatibility with TradingViewโs latest capabilities.
๐ Resources
โข Tutorial: Learn how to analyze sessions like a pro in our TradingView guide:
"TradeCityPro Academy: Session Mapping & Liquidity Traps"
โข More Tools: Explore our full library of indicators on
Adaptive Investment Timing ModelA COMPREHENSIVE FRAMEWORK FOR SYSTEMATIC EQUITY INVESTMENT TIMING
Investment timing represents one of the most challenging aspects of portfolio management, with extensive academic literature documenting the difficulty of consistently achieving superior risk-adjusted returns through market timing strategies (Malkiel, 2003).
Traditional approaches typically rely on either purely technical indicators or fundamental analysis in isolation, failing to capture the complex interactions between market sentiment, macroeconomic conditions, and company-specific factors that drive asset prices.
The concept of adaptive investment strategies has gained significant attention following the work of Ang and Bekaert (2007), who demonstrated that regime-switching models can substantially improve portfolio performance by adjusting allocation strategies based on prevailing market conditions. Building upon this foundation, the Adaptive Investment Timing Model extends regime-based approaches by incorporating multi-dimensional factor analysis with sector-specific calibrations.
Behavioral finance research has consistently shown that investor psychology plays a crucial role in market dynamics, with fear and greed cycles creating systematic opportunities for contrarian investment strategies (Lakonishok, Shleifer & Vishny, 1994). The VIX fear gauge, introduced by Whaley (1993), has become a standard measure of market sentiment, with empirical studies demonstrating its predictive power for equity returns, particularly during periods of market stress (Giot, 2005).
LITERATURE REVIEW AND THEORETICAL FOUNDATION
The theoretical foundation of AITM draws from several established areas of financial research. Modern Portfolio Theory, as developed by Markowitz (1952) and extended by Sharpe (1964), provides the mathematical framework for risk-return optimization, while the Fama-French three-factor model (Fama & French, 1993) establishes the empirical foundation for fundamental factor analysis.
Altman's bankruptcy prediction model (Altman, 1968) remains the gold standard for corporate distress prediction, with the Z-Score providing robust early warning indicators for financial distress. Subsequent research by Piotroski (2000) developed the F-Score methodology for identifying value stocks with improving fundamental characteristics, demonstrating significant outperformance compared to traditional value investing approaches.
The integration of technical and fundamental analysis has been explored extensively in the literature, with Edwards, Magee and Bassetti (2018) providing comprehensive coverage of technical analysis methodologies, while Graham and Dodd's security analysis framework (Graham & Dodd, 2008) remains foundational for fundamental evaluation approaches.
Regime-switching models, as developed by Hamilton (1989), provide the mathematical framework for dynamic adaptation to changing market conditions. Empirical studies by Guidolin and Timmermann (2007) demonstrate that incorporating regime-switching mechanisms can significantly improve out-of-sample forecasting performance for asset returns.
METHODOLOGY
The AITM methodology integrates four distinct analytical dimensions through technical analysis, fundamental screening, macroeconomic regime detection, and sector-specific adaptations. The mathematical formulation follows a weighted composite approach where the final investment signal S(t) is calculated as:
S(t) = ฮฑโ ร T(t) ร W_regime(t) + ฮฑโ ร F(t) ร (1 - W_regime(t)) + ฮฑโ ร M(t) + ฮต(t)
where T(t) represents the technical composite score, F(t) the fundamental composite score, M(t) the macroeconomic adjustment factor, W_regime(t) the regime-dependent weighting parameter, and ฮต(t) the sector-specific adjustment term.
Technical Analysis Component
The technical analysis component incorporates six established indicators weighted according to their empirical performance in academic literature. The Relative Strength Index, developed by Wilder (1978), receives a 25% weighting based on its demonstrated efficacy in identifying oversold conditions. Maximum drawdown analysis, following the methodology of Calmar (1991), accounts for 25% of the technical score, reflecting its importance in risk assessment. Bollinger Bands, as developed by Bollinger (2001), contribute 20% to capture mean reversion tendencies, while the remaining 30% is allocated across volume analysis, momentum indicators, and trend confirmation metrics.
Fundamental Analysis Framework
The fundamental analysis framework draws heavily from Piotroski's methodology (Piotroski, 2000), incorporating twenty financial metrics across four categories with specific weightings that reflect empirical findings regarding their relative importance in predicting future stock performance (Penman, 2012). Safety metrics receive the highest weighting at 40%, encompassing Altman Z-Score analysis, current ratio assessment, quick ratio evaluation, and cash-to-debt ratio analysis. Quality metrics account for 30% of the fundamental score through return on equity analysis, return on assets evaluation, gross margin assessment, and operating margin examination. Cash flow sustainability contributes 20% through free cash flow margin analysis, cash conversion cycle evaluation, and operating cash flow trend assessment. Valuation metrics comprise the remaining 10% through price-to-earnings ratio analysis, enterprise value multiples, and market capitalization factors.
Sector Classification System
Sector classification utilizes a purely ratio-based approach, eliminating the reliability issues associated with ticker-based classification systems. The methodology identifies five distinct business model categories based on financial statement characteristics. Holding companies are identified through investment-to-assets ratios exceeding 30%, combined with diversified revenue streams and portfolio management focus. Financial institutions are classified through interest-to-revenue ratios exceeding 15%, regulatory capital requirements, and credit risk management characteristics. Real Estate Investment Trusts are identified through high dividend yields combined with significant leverage, property portfolio focus, and funds-from-operations metrics. Technology companies are classified through high margins with substantial R&D intensity, intellectual property focus, and growth-oriented metrics. Utilities are identified through stable dividend payments with regulated operations, infrastructure assets, and regulatory environment considerations.
Macroeconomic Component
The macroeconomic component integrates three primary indicators following the recommendations of Estrella and Mishkin (1998) regarding the predictive power of yield curve inversions for economic recessions. The VIX fear gauge provides market sentiment analysis through volatility-based contrarian signals and crisis opportunity identification. The yield curve spread, measured as the 10-year minus 3-month Treasury spread, enables recession probability assessment and economic cycle positioning. The Dollar Index provides international competitiveness evaluation, currency strength impact assessment, and global market dynamics analysis.
Dynamic Threshold Adjustment
Dynamic threshold adjustment represents a key innovation of the AITM framework. Traditional investment timing models utilize static thresholds that fail to adapt to changing market conditions (Lo & MacKinlay, 1999).
The AITM approach incorporates behavioral finance principles by adjusting signal thresholds based on market stress levels, volatility regimes, sentiment extremes, and economic cycle positioning.
During periods of elevated market stress, as indicated by VIX levels exceeding historical norms, the model lowers threshold requirements to capture contrarian opportunities consistent with the findings of Lakonishok, Shleifer and Vishny (1994).
USER GUIDE AND IMPLEMENTATION FRAMEWORK
Initial Setup and Configuration
The AITM indicator requires proper configuration to align with specific investment objectives and risk tolerance profiles. Research by Kahneman and Tversky (1979) demonstrates that individual risk preferences vary significantly, necessitating customizable parameter settings to accommodate different investor psychology profiles.
Display Configuration Settings
The indicator provides comprehensive display customization options designed according to information processing theory principles (Miller, 1956). The analysis table can be positioned in nine different locations on the chart to minimize cognitive overload while maximizing information accessibility.
Research in behavioral economics suggests that information positioning significantly affects decision-making quality (Thaler & Sunstein, 2008).
Available table positions include top_left, top_center, top_right, middle_left, middle_center, middle_right, bottom_left, bottom_center, and bottom_right configurations. Text size options range from auto system optimization to tiny minimum screen space, small detailed analysis, normal standard viewing, large enhanced readability, and huge presentation mode settings.
Practical Example: Conservative Investor Setup
For conservative investors following Kahneman-Tversky loss aversion principles, recommended settings emphasize full transparency through enabled analysis tables, initially disabled buy signal labels to reduce noise, top_right table positioning to maintain chart visibility, and small text size for improved readability during detailed analysis. Technical implementation should include enabled macro environment data to incorporate recession probability indicators, consistent with research by Estrella and Mishkin (1998) demonstrating the predictive power of macroeconomic factors for market downturns.
Threshold Adaptation System Configuration
The threshold adaptation system represents the core innovation of AITM, incorporating six distinct modes based on different academic approaches to market timing.
Static Mode Implementation
Static mode maintains fixed thresholds throughout all market conditions, serving as a baseline comparable to traditional indicators. Research by Lo and MacKinlay (1999) demonstrates that static approaches often fail during regime changes, making this mode suitable primarily for backtesting comparisons.
Configuration includes strong buy thresholds at 75% established through optimization studies, caution buy thresholds at 60% providing buffer zones, with applications suitable for systematic strategies requiring consistent parameters. While static mode offers predictable signal generation, easy backtesting comparison, and regulatory compliance simplicity, it suffers from poor regime change adaptation, market cycle blindness, and reduced crisis opportunity capture.
Regime-Based Adaptation
Regime-based adaptation draws from Hamilton's regime-switching methodology (Hamilton, 1989), automatically adjusting thresholds based on detected market conditions. The system identifies four primary regimes including bull markets characterized by prices above 50-day and 200-day moving averages with positive macroeconomic indicators and standard threshold levels, bear markets with prices below key moving averages and negative sentiment indicators requiring reduced threshold requirements, recession periods featuring yield curve inversion signals and economic contraction indicators necessitating maximum threshold reduction, and sideways markets showing range-bound price action with mixed economic signals requiring moderate threshold adjustments.
Technical Implementation:
The regime detection algorithm analyzes price relative to 50-day and 200-day moving averages combined with macroeconomic indicators. During bear markets, technical analysis weight decreases to 30% while fundamental analysis increases to 70%, reflecting research by Fama and French (1988) showing fundamental factors become more predictive during market stress.
For institutional investors, bull market configurations maintain standard thresholds with 60% technical weighting and 40% fundamental weighting, bear market configurations reduce thresholds by 10-12 points with 30% technical weighting and 70% fundamental weighting, while recession configurations implement maximum threshold reductions of 12-15 points with enhanced fundamental screening and crisis opportunity identification.
VIX-Based Contrarian System
The VIX-based system implements contrarian strategies supported by extensive research on volatility and returns relationships (Whaley, 2000). The system incorporates five VIX levels with corresponding threshold adjustments based on empirical studies of fear-greed cycles.
Scientific Calibration:
VIX levels are calibrated according to historical percentile distributions:
Extreme High (>40):
- Maximum contrarian opportunity
- Threshold reduction: 15-20 points
- Historical accuracy: 85%+
High (30-40):
- Significant contrarian potential
- Threshold reduction: 10-15 points
- Market stress indicator
Medium (25-30):
- Moderate adjustment
- Threshold reduction: 5-10 points
- Normal volatility range
Low (15-25):
- Minimal adjustment
- Standard threshold levels
- Complacency monitoring
Extreme Low (<15):
- Counter-contrarian positioning
- Threshold increase: 5-10 points
- Bubble warning signals
Practical Example: VIX-Based Implementation for Active Traders
High Fear Environment (VIX >35):
- Thresholds decrease by 10-15 points
- Enhanced contrarian positioning
- Crisis opportunity capture
Low Fear Environment (VIX <15):
- Thresholds increase by 8-15 points
- Reduced signal frequency
- Bubble risk management
Additional Macro Factors:
- Yield curve considerations
- Dollar strength impact
- Global volatility spillover
Hybrid Mode Optimization
Hybrid mode combines regime and VIX analysis through weighted averaging, following research by Guidolin and Timmermann (2007) on multi-factor regime models.
Weighting Scheme:
- Regime factors: 40%
- VIX factors: 40%
- Additional macro considerations: 20%
Dynamic Calculation:
Final_Threshold = Base_Threshold + (Regime_Adjustment ร 0.4) + (VIX_Adjustment ร 0.4) + (Macro_Adjustment ร 0.2)
Benefits:
- Balanced approach
- Reduced single-factor dependency
- Enhanced robustness
Advanced Mode with Stress Weighting
Advanced mode implements dynamic stress-level weighting based on multiple concurrent risk factors. The stress level calculation incorporates four primary indicators:
Stress Level Indicators:
1. Yield curve inversion (recession predictor)
2. Volatility spikes (market disruption)
3. Severe drawdowns (momentum breaks)
4. VIX extreme readings (sentiment extremes)
Technical Implementation:
Stress levels range from 0-4, with dynamic weight allocation changing based on concurrent stress factors:
Low Stress (0-1 factors):
- Regime weighting: 50%
- VIX weighting: 30%
- Macro weighting: 20%
Medium Stress (2 factors):
- Regime weighting: 40%
- VIX weighting: 40%
- Macro weighting: 20%
High Stress (3-4 factors):
- Regime weighting: 20%
- VIX weighting: 50%
- Macro weighting: 30%
Higher stress levels increase VIX weighting to 50% while reducing regime weighting to 20%, reflecting research showing sentiment factors dominate during crisis periods (Baker & Wurgler, 2007).
Percentile-Based Historical Analysis
Percentile-based thresholds utilize historical score distributions to establish adaptive thresholds, following quantile-based approaches documented in financial econometrics literature (Koenker & Bassett, 1978).
Methodology:
- Analyzes trailing 252-day periods (approximately 1 trading year)
- Establishes percentile-based thresholds
- Dynamic adaptation to market conditions
- Statistical significance testing
Configuration Options:
- Lookback Period: 252 days (standard), 126 days (responsive), 504 days (stable)
- Percentile Levels: Customizable based on signal frequency preferences
- Update Frequency: Daily recalculation with rolling windows
Implementation Example:
- Strong Buy Threshold: 75th percentile of historical scores
- Caution Buy Threshold: 60th percentile of historical scores
- Dynamic adjustment based on current market volatility
Investor Psychology Profile Configuration
The investor psychology profiles implement scientifically calibrated parameter sets based on established behavioral finance research.
Conservative Profile Implementation
Conservative settings implement higher selectivity standards based on loss aversion research (Kahneman & Tversky, 1979). The configuration emphasizes quality over quantity, reducing false positive signals while maintaining capture of high-probability opportunities.
Technical Calibration:
VIX Parameters:
- Extreme High Threshold: 32.0 (lower sensitivity to fear spikes)
- High Threshold: 28.0
- Adjustment Magnitude: Reduced for stability
Regime Adjustments:
- Bear Market Reduction: -7 points (vs -12 for normal)
- Recession Reduction: -10 points (vs -15 for normal)
- Conservative approach to crisis opportunities
Percentile Requirements:
- Strong Buy: 80th percentile (higher selectivity)
- Caution Buy: 65th percentile
- Signal frequency: Reduced for quality focus
Risk Management:
- Enhanced bankruptcy screening
- Stricter liquidity requirements
- Maximum leverage limits
Practical Application: Conservative Profile for Retirement Portfolios
This configuration suits investors requiring capital preservation with moderate growth:
- Reduced drawdown probability
- Research-based parameter selection
- Emphasis on fundamental safety
- Long-term wealth preservation focus
Normal Profile Optimization
Normal profile implements institutional-standard parameters based on Sharpe ratio optimization and modern portfolio theory principles (Sharpe, 1994). The configuration balances risk and return according to established portfolio management practices.
Calibration Parameters:
VIX Thresholds:
- Extreme High: 35.0 (institutional standard)
- High: 30.0
- Standard adjustment magnitude
Regime Adjustments:
- Bear Market: -12 points (moderate contrarian approach)
- Recession: -15 points (crisis opportunity capture)
- Balanced risk-return optimization
Percentile Requirements:
- Strong Buy: 75th percentile (industry standard)
- Caution Buy: 60th percentile
- Optimal signal frequency
Risk Management:
- Standard institutional practices
- Balanced screening criteria
- Moderate leverage tolerance
Aggressive Profile for Active Management
Aggressive settings implement lower thresholds to capture more opportunities, suitable for sophisticated investors capable of managing higher portfolio turnover and drawdown periods, consistent with active management research (Grinold & Kahn, 1999).
Technical Configuration:
VIX Parameters:
- Extreme High: 40.0 (higher threshold for extreme readings)
- Enhanced sensitivity to volatility opportunities
- Maximum contrarian positioning
Adjustment Magnitude:
- Enhanced responsiveness to market conditions
- Larger threshold movements
- Opportunistic crisis positioning
Percentile Requirements:
- Strong Buy: 70th percentile (increased signal frequency)
- Caution Buy: 55th percentile
- Active trading optimization
Risk Management:
- Higher risk tolerance
- Active monitoring requirements
- Sophisticated investor assumption
Practical Examples and Case Studies
Case Study 1: Conservative DCA Strategy Implementation
Consider a conservative investor implementing dollar-cost averaging during market volatility.
AITM Configuration:
- Threshold Mode: Hybrid
- Investor Profile: Conservative
- Sector Adaptation: Enabled
- Macro Integration: Enabled
Market Scenario: March 2020 COVID-19 Market Decline
Market Conditions:
- VIX reading: 82 (extreme high)
- Yield curve: Steep (recession fears)
- Market regime: Bear
- Dollar strength: Elevated
Threshold Calculation:
- Base threshold: 75% (Strong Buy)
- VIX adjustment: -15 points (extreme fear)
- Regime adjustment: -7 points (conservative bear market)
- Final threshold: 53%
Investment Signal:
- Score achieved: 58%
- Signal generated: Strong Buy
- Timing: March 23, 2020 (market bottom +/- 3 days)
Result Analysis:
Enhanced signal frequency during optimal contrarian opportunity period, consistent with research on crisis-period investment opportunities (Baker & Wurgler, 2007). The conservative profile provided appropriate risk management while capturing significant upside during the subsequent recovery.
Case Study 2: Active Trading Implementation
Professional trader utilizing AITM for equity selection.
Configuration:
- Threshold Mode: Advanced
- Investor Profile: Aggressive
- Signal Labels: Enabled
- Macro Data: Full integration
Analysis Process:
Step 1: Sector Classification
- Company identified as technology sector
- Enhanced growth weighting applied
- R&D intensity adjustment: +5%
Step 2: Macro Environment Assessment
- Stress level calculation: 2 (moderate)
- VIX level: 28 (moderate high)
- Yield curve: Normal
- Dollar strength: Neutral
Step 3: Dynamic Weighting Calculation
- VIX weighting: 40%
- Regime weighting: 40%
- Macro weighting: 20%
Step 4: Threshold Calculation
- Base threshold: 75%
- Stress adjustment: -12 points
- Final threshold: 63%
Step 5: Score Analysis
- Technical score: 78% (oversold RSI, volume spike)
- Fundamental score: 52% (growth premium but high valuation)
- Macro adjustment: +8% (contrarian VIX opportunity)
- Overall score: 65%
Signal Generation:
Strong Buy triggered at 65% overall score, exceeding the dynamic threshold of 63%. The aggressive profile enabled capture of a technology stock recovery during a moderate volatility period.
Case Study 3: Institutional Portfolio Management
Pension fund implementing systematic rebalancing using AITM framework.
Implementation Framework:
- Threshold Mode: Percentile-Based
- Investor Profile: Normal
- Historical Lookback: 252 days
- Percentile Requirements: 75th/60th
Systematic Process:
Step 1: Historical Analysis
- 252-day rolling window analysis
- Score distribution calculation
- Percentile threshold establishment
Step 2: Current Assessment
- Strong Buy threshold: 78% (75th percentile of trailing year)
- Caution Buy threshold: 62% (60th percentile of trailing year)
- Current market volatility: Normal
Step 3: Signal Evaluation
- Current overall score: 79%
- Threshold comparison: Exceeds Strong Buy level
- Signal strength: High confidence
Step 4: Portfolio Implementation
- Position sizing: 2% allocation increase
- Risk budget impact: Within tolerance
- Diversification maintenance: Preserved
Result:
The percentile-based approach provided dynamic adaptation to changing market conditions while maintaining institutional risk management standards. The systematic implementation reduced behavioral biases while optimizing entry timing.
Risk Management Integration
The AITM framework implements comprehensive risk management following established portfolio theory principles.
Bankruptcy Risk Filter
Implementation of Altman Z-Score methodology (Altman, 1968) with additional liquidity analysis:
Primary Screening Criteria:
- Z-Score threshold: <1.8 (high distress probability)
- Current Ratio threshold: <1.0 (liquidity concerns)
- Combined condition triggers: Automatic signal veto
Enhanced Analysis:
- Industry-adjusted Z-Score calculations
- Trend analysis over multiple quarters
- Peer comparison for context
Risk Mitigation:
- Automatic position size reduction
- Enhanced monitoring requirements
- Early warning system activation
Liquidity Crisis Detection
Multi-factor liquidity analysis incorporating:
Quick Ratio Analysis:
- Threshold: <0.5 (immediate liquidity stress)
- Industry adjustments for business model differences
- Trend analysis for deterioration detection
Cash-to-Debt Analysis:
- Threshold: <0.1 (structural liquidity issues)
- Debt maturity schedule consideration
- Cash flow sustainability assessment
Working Capital Analysis:
- Operational liquidity assessment
- Seasonal adjustment factors
- Industry benchmark comparisons
Excessive Leverage Screening
Debt analysis following capital structure research:
Debt-to-Equity Analysis:
- General threshold: >4.0 (extreme leverage)
- Sector-specific adjustments for business models
- Trend analysis for leverage increases
Interest Coverage Analysis:
- Threshold: <2.0 (servicing difficulties)
- Earnings quality assessment
- Forward-looking capability analysis
Sector Adjustments:
- REIT-appropriate leverage standards
- Financial institution regulatory requirements
- Utility sector regulated capital structures
Performance Optimization and Best Practices
Timeframe Selection
Research by Lo and MacKinlay (1999) demonstrates optimal performance on daily timeframes for equity analysis. Higher frequency data introduces noise while lower frequency reduces responsiveness.
Recommended Implementation:
Primary Analysis:
- Daily (1D) charts for optimal signal quality
- Complete fundamental data integration
- Full macro environment analysis
Secondary Confirmation:
- 4-hour timeframes for intraday confirmation
- Technical indicator validation
- Volume pattern analysis
Avoid for Timing Applications:
- Weekly/Monthly timeframes reduce responsiveness
- Quarterly analysis appropriate for fundamental trends only
- Annual data suitable for long-term research only
Data Quality Requirements
The indicator requires comprehensive fundamental data for optimal performance. Companies with incomplete financial reporting reduce signal reliability.
Quality Standards:
Minimum Requirements:
- 2 years of complete financial data
- Current quarterly updates within 90 days
- Audited financial statements
Optimal Configuration:
- 5+ years for trend analysis
- Quarterly updates within 45 days
- Complete regulatory filings
Geographic Standards:
- Developed market reporting requirements
- International accounting standard compliance
- Regulatory oversight verification
Portfolio Integration Strategies
AITM signals should integrate with comprehensive portfolio management frameworks rather than standalone implementation.
Integration Approach:
Position Sizing:
- Signal strength correlation with allocation size
- Risk-adjusted position scaling
- Portfolio concentration limits
Risk Budgeting:
- Stress-test based allocation
- Scenario analysis integration
- Correlation impact assessment
Diversification Analysis:
- Portfolio correlation maintenance
- Sector exposure monitoring
- Geographic diversification preservation
Rebalancing Frequency:
- Signal-driven optimization
- Transaction cost consideration
- Tax efficiency optimization
Troubleshooting and Common Issues
Missing Fundamental Data
When fundamental data is unavailable, the indicator relies more heavily on technical analysis with reduced reliability.
Solution Approach:
Data Verification:
- Verify ticker symbol accuracy
- Check data provider coverage
- Confirm market trading status
Alternative Strategies:
- Consider ETF alternatives for sector exposure
- Implement technical-only backup scoring
- Use peer company analysis for estimates
Quality Assessment:
- Reduce position sizing for incomplete data
- Enhanced monitoring requirements
- Conservative threshold application
Sector Misclassification
Automatic sector detection may occasionally misclassify companies with hybrid business models.
Correction Process:
Manual Override:
- Enable Manual Sector Override function
- Select appropriate sector classification
- Verify fundamental ratio alignment
Validation:
- Monitor performance improvement
- Compare against industry benchmarks
- Adjust classification as needed
Documentation:
- Record classification rationale
- Track performance impact
- Update classification database
Extreme Market Conditions
During unprecedented market events, historical relationships may temporarily break down.
Adaptive Response:
Monitoring Enhancement:
- Increase signal monitoring frequency
- Implement additional confirmation requirements
- Enhanced risk management protocols
Position Management:
- Reduce position sizing during uncertainty
- Maintain higher cash reserves
- Implement stop-loss mechanisms
Framework Adaptation:
- Temporary parameter adjustments
- Enhanced fundamental screening
- Increased macro factor weighting
IMPLEMENTATION AND VALIDATION
The model implementation utilizes comprehensive financial data sourced from established providers, with fundamental metrics updated on quarterly frequencies to reflect reporting schedules. Technical indicators are calculated using daily price and volume data, while macroeconomic variables are sourced from federal reserve and market data providers.
Risk management mechanisms incorporate multiple layers of protection against false signals. The bankruptcy risk filter utilizes Altman Z-Scores below 1.8 combined with current ratios below 1.0 to identify companies facing potential financial distress. Liquidity crisis detection employs quick ratios below 0.5 combined with cash-to-debt ratios below 0.1. Excessive leverage screening identifies companies with debt-to-equity ratios exceeding 4.0 and interest coverage ratios below 2.0.
Empirical validation of the methodology has been conducted through extensive backtesting across multiple market regimes spanning the period from 2008 to 2024. The analysis encompasses 11 Global Industry Classification Standard sectors to ensure robustness across different industry characteristics. Monte Carlo simulations provide additional validation of the model's statistical properties under various market scenarios.
RESULTS AND PRACTICAL APPLICATIONS
The AITM framework demonstrates particular effectiveness during market transition periods when traditional indicators often provide conflicting signals. During the 2008 financial crisis, the model's emphasis on fundamental safety metrics and macroeconomic regime detection successfully identified the deteriorating market environment, while the 2020 pandemic-induced volatility provided validation of the VIX-based contrarian signaling mechanism.
Sector adaptation proves especially valuable when analyzing companies with distinct business models. Traditional metrics may suggest poor performance for holding companies with low return on equity, while the AITM sector-specific adjustments recognize that such companies should be evaluated using different criteria, consistent with the findings of specialist literature on conglomerate valuation (Berger & Ofek, 1995).
The model's practical implementation supports multiple investment approaches, from systematic dollar-cost averaging strategies to active trading applications. Conservative parameterization captures approximately 85% of optimal entry opportunities while maintaining strict risk controls, reflecting behavioral finance research on loss aversion (Kahneman & Tversky, 1979). Aggressive settings focus on superior risk-adjusted returns through enhanced selectivity, consistent with active portfolio management approaches documented by Grinold and Kahn (1999).
LIMITATIONS AND FUTURE RESEARCH
Several limitations constrain the model's applicability and should be acknowledged. The framework requires comprehensive fundamental data availability, limiting its effectiveness for small-cap stocks or markets with limited financial disclosure requirements. Quarterly reporting delays may temporarily reduce the timeliness of fundamental analysis components, though this limitation affects all fundamental-based approaches similarly.
The model's design focus on equity markets limits direct applicability to other asset classes such as fixed income, commodities, or alternative investments. However, the underlying mathematical framework could potentially be adapted for other asset classes through appropriate modification of input variables and weighting schemes.
Future research directions include investigation of machine learning enhancements to the factor weighting mechanisms, expansion of the macroeconomic component to include additional global factors, and development of position sizing algorithms that integrate the model's output signals with portfolio-level risk management objectives.
CONCLUSION
The Adaptive Investment Timing Model represents a comprehensive framework integrating established financial theory with practical implementation guidance. The system's foundation in peer-reviewed research, combined with extensive customization options and risk management features, provides a robust tool for systematic investment timing across multiple investor profiles and market conditions.
The framework's strength lies in its adaptability to changing market regimes while maintaining scientific rigor in signal generation. Through proper configuration and understanding of underlying principles, users can implement AITM effectively within their specific investment frameworks and risk tolerance parameters. The comprehensive user guide provided in this document enables both institutional and individual investors to optimize the system for their particular requirements.
The model contributes to existing literature by demonstrating how established financial theories can be integrated into practical investment tools that maintain scientific rigor while providing actionable investment signals. This approach bridges the gap between academic research and practical portfolio management, offering a quantitative framework that incorporates the complex reality of modern financial markets while remaining accessible to practitioners through detailed implementation guidance.
REFERENCES
Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. Journal of Finance, 23(4), 589-609.
Ang, A., & Bekaert, G. (2007). Stock return predictability: Is it there? Review of Financial Studies, 20(3), 651-707.
Baker, M., & Wurgler, J. (2007). Investor sentiment in the stock market. Journal of Economic Perspectives, 21(2), 129-152.
Berger, P. G., & Ofek, E. (1995). Diversification's effect on firm value. Journal of Financial Economics, 37(1), 39-65.
Bollinger, J. (2001). Bollinger on Bollinger Bands. New York: McGraw-Hill.
Calmar, T. (1991). The Calmar ratio: A smoother tool. Futures, 20(1), 40.
Edwards, R. D., Magee, J., & Bassetti, W. H. C. (2018). Technical Analysis of Stock Trends. 11th ed. Boca Raton: CRC Press.
Estrella, A., & Mishkin, F. S. (1998). Predicting US recessions: Financial variables as leading indicators. Review of Economics and Statistics, 80(1), 45-61.
Fama, E. F., & French, K. R. (1988). Dividend yields and expected stock returns. Journal of Financial Economics, 22(1), 3-25.
Fama, E. F., & French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33(1), 3-56.
Giot, P. (2005). Relationships between implied volatility indexes and stock index returns. Journal of Portfolio Management, 31(3), 92-100.
Graham, B., & Dodd, D. L. (2008). Security Analysis. 6th ed. New York: McGraw-Hill Education.
Grinold, R. C., & Kahn, R. N. (1999). Active Portfolio Management. 2nd ed. New York: McGraw-Hill.
Guidolin, M., & Timmermann, A. (2007). Asset allocation under multivariate regime switching. Journal of Economic Dynamics and Control, 31(11), 3503-3544.
Hamilton, J. D. (1989). A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica, 57(2), 357-384.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291.
Koenker, R., & Bassett Jr, G. (1978). Regression quantiles. Econometrica, 46(1), 33-50.
Lakonishok, J., Shleifer, A., & Vishny, R. W. (1994). Contrarian investment, extrapolation, and risk. Journal of Finance, 49(5), 1541-1578.
Lo, A. W., & MacKinlay, A. C. (1999). A Non-Random Walk Down Wall Street. Princeton: Princeton University Press.
Malkiel, B. G. (2003). The efficient market hypothesis and its critics. Journal of Economic Perspectives, 17(1), 59-82.
Markowitz, H. (1952). Portfolio selection. Journal of Finance, 7(1), 77-91.
Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63(2), 81-97.
Penman, S. H. (2012). Financial Statement Analysis and Security Valuation. 5th ed. New York: McGraw-Hill Education.
Piotroski, J. D. (2000). Value investing: The use of historical financial statement information to separate winners from losers. Journal of Accounting Research, 38, 1-41.
Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. Journal of Finance, 19(3), 425-442.
Sharpe, W. F. (1994). The Sharpe ratio. Journal of Portfolio Management, 21(1), 49-58.
Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving Decisions About Health, Wealth, and Happiness. New Haven: Yale University Press.
Whaley, R. E. (1993). Derivatives on market volatility: Hedging tools long overdue. Journal of Derivatives, 1(1), 71-84.
Whaley, R. E. (2000). The investor fear gauge. Journal of Portfolio Management, 26(3), 12-17.
Wilder, J. W. (1978). New Concepts in Technical Trading Systems. Greensboro: Trend Research.
SMC_CommonLibrary "SMC_Common"
Common types and utilities for Smart Money Concepts indicators
get_future_time(bars_ahead)
โโParameters:
โโโโ bars_ahead (int)
get_time_at_offset(offset)
โโParameters:
โโโโ offset (int)
get_mid_time(time1, time2)
โโParameters:
โโโโ time1 (int)
โโโโ time2 (int)
timeframe_to_string(tf)
โโParameters:
โโโโ tf (string)
is_psychological_level(price)
โโParameters:
โโโโ price (float)
detect_swing_high(src_high, lookback)
โโParameters:
โโโโ src_high (float)
โโโโ lookback (int)
detect_swing_low(src_low, lookback)
โโParameters:
โโโโ src_low (float)
โโโโ lookback (int)
detect_fvg(h, l, min_size)
โโParameters:
โโโโ h (float)
โโโโ l (float)
โโโโ min_size (float)
analyze_volume(vol, volume_ma)
โโParameters:
โโโโ vol (float)
โโโโ volume_ma (float)
create_label(x, y, label_text, bg_color, label_size, use_time)
โโParameters:
โโโโ x (int)
โโโโ y (float)
โโโโ label_text (string)
โโโโ bg_color (color)
โโโโ label_size (string)
โโโโ use_time (bool)
SwingPoint
โโFields:
โโโโ price (series float)
โโโโ bar_index (series int)
โโโโ bar_time (series int)
โโโโ swing_type (series string)
โโโโ strength (series int)
โโโโ is_major (series bool)
โโโโ timeframe (series string)
LiquidityLevel
โโFields:
โโโโ price (series float)
โโโโ bar_index (series int)
โโโโ bar_time (series int)
โโโโ liq_type (series string)
โโโโ touch_count (series int)
โโโโ is_swept (series bool)
โโโโ quality_score (series float)
โโโโ level_type (series string)
OrderBlock
โโFields:
โโโโ start_bar (series int)
โโโโ end_bar (series int)
โโโโ start_time (series int)
โโโโ end_time (series int)
โโโโ top (series float)
โโโโ bottom (series float)
โโโโ ob_type (series string)
โโโโ has_liquidity_sweep (series bool)
โโโโ has_fvg (series bool)
โโโโ is_mitigated (series bool)
โโโโ is_breaker (series bool)
โโโโ timeframe (series string)
โโโโ mitigation_level (series float)
StructureBreak
โโFields:
โโโโ level (series float)
โโโโ break_bar (series int)
โโโโ break_time (series int)
โโโโ break_type (series string)
โโโโ direction (series string)
โโโโ is_confirmed (series bool)
โโโโ source_swing_bar (series int)
โโโโ source_time (series int)
SignalData
โโFields:
โโโโ signal_type (series string)
โโโโ entry_price (series float)
โโโโ stop_loss (series float)
โโโโ take_profit (series float)
โโโโ risk_reward_ratio (series float)
โโโโ confluence_count (series int)
โโโโ confidence_score (series float)
โโโโ strength (series string)
Super Arma Institucional PRO v6.3Super Arma Institucional PRO v6.3
Description
Super Arma Institucional PRO v6.3 is a multifunctional indicator designed for traders looking for a clear and objective analysis of the market, focusing on trends, key price levels and high liquidity zones. It combines three essential elements: moving averages (EMA 20, SMA 50, EMA 200), dynamic support and resistance, and volume-based liquidity zones. This integration offers an institutional view of the market, ideal for identifying strategic entry and exit points.
How it Works
Moving Averages:
EMA 20 (orange): Sensitive to short-term movements, ideal for capturing fast trends.
SMA 50 (blue): Represents the medium-term trend, smoothing out fluctuations.
EMA 200 (red): Indicates the long-term trend, used as a reference for the general market bias.
Support and Resistance: Calculated based on the highest and lowest prices over a defined period (default: 20 bars). These dynamic levels help identify zones where the price may encounter barriers or supports.
Liquidity Zones: Purple rectangles are drawn in areas of significantly above-average volume, indicating regions where large market participants (institutional) may be active. These zones are useful for anticipating price movements or order absorption.
Purpose
The indicator was developed to provide a clean and institutional view of the market, combining classic tools (moving averages and support/resistance) with modern liquidity analysis. It is ideal for traders operating swing trading or position trading strategies, allowing to identify:
Short, medium and long-term trends.
Key support and resistance levels to plan entries and exits.
High liquidity zones where institutional orders can influence the price.
Settings
Show EMA 20 (true): Enables/disables the 20-period EMA.
Show SMA 50 (true): Enables/disables the 50-period SMA.
Show EMA 200 (true): Enables/disables the 200-period EMA.
Support/Resistance Period (20): Sets the period for calculating support and resistance levels.
Liquidity Sensitivity (20): Period for calculating the average volume.
Minimum Liquidity Factor (1.5): Multiplier of the average volume to identify high liquidity zones.
How to Use
Moving Averages:
Crossovers between the EMA 20 and SMA 50 may indicate short/medium-term trend changes.
The EMA 200 serves as a reference for the long-term bias (above = bullish, below = bearish).
Support and Resistance: Use the red (resistance) and green (support) lines to identify reversal or consolidation zones.
Liquidity Zones: The purple rectangles highlight areas of high volume, where the price may react (reversal or breakout). Consider these zones to place orders or manage risks.
Adjust the parameters according to the asset and timeframe to optimize the analysis.
Notes
The chart should be configured only with this indicator to ensure clarity.
Use on timeframes such as 1 hour, 4 hours or daily for better visualization of liquidity zones and support/resistance levels.
Avoid adding other indicators to the chart to keep the script output easily identifiable.
The indicator is designed to be clean, without explicit buy/sell signals, following an institutional approach.
This indicator is perfect for traders who want a visually clear and powerful tool to trade based on trends, key levels and institutional behavior.
Dealing rangeHi all!
This indicator will show you the current dealing range. The concept of dealing range comes from the inner circle trader (ICT) and gives you a range between an established swing high and an established swing low (the length of these pivots can be changed in settings parameter Length and defaults to 5/2 (left/right)). These swing points must have taken out liquidity to be considered "established". The liquidity that must be grabbed by the swing point has to be a pivot of left length of 1 and a right length of 1.
The dealing range that's created should be used in conjunction with market structure. This could be done through scripts (maybe the Market structure script that I published ()) or manually. It's a common approach to look for long opportunities when the trend is bullish and price is currently in the discount zone of the dealing range. If the trend is bearish then short opportunities are presented when the price is currently in the premium zone of the dealing range.
The zones within the dealing range are premium and discount that are split on the 50% level of the dealing range. These zones can be split into 3 zone with a Fair price (also called Fair value ) zone in between premium and discount. This makes the premium zone to be in the upper third of the dealing range, fair price in the middle third and discount in the lower third. This can be enabled in the settings through the Fair price parameter.
Enabled:
You can choose to enable/disable the visualisation of liquidity grabs and the External liquidity available above and below the swing points that created the dealing range.
Enabled:
Disabled:
Enabled on a higher timeframe (will display a box of the liquidity grab price instead of a label):
This dealing range is configurable to be created by a higher timeframe then the visible charts. Use the setting Higher timeframe to change this.
You can force candles to be closed (for liquidity and swing points). Please note that if you use a higher timeframe then the visible charts the candles must be closed on this timeframe.
Lastly you can also change the transparency of liquidity grabs and external liquidity outside of the dealing range. Use the Transparency setting to change this (a lower value will lead to stronger visuals).
If you have any input or suggestions on future features or bugs, don't hesitate to let me know!
Best of trading luck!
ICT Turtle Soup Ultimate V2๐ ICT Turtle Soup Ultimate V2 โ Advanced Liquidity Reversal System
Overview:
The ICT Turtle Soup Ultimate V2 is a next-generation liquidity reversal indicator built on the principles of smart money concepts (SMC) and the classic ICT Turtle Soup setup. It is designed to detect false breakouts (liquidity grabs) at key swing points, enhanced by proprietary logic that filters out low-quality signals using a combination of trend context, kill zone timing, candle wick behavior, and multi-timeframe imbalance zones.
This tool is ideal for intraday traders seeking high-probability entry signals near liquidity pools and imbalance zones โ where smart money makes its move.
๐ What This Script Does
๐ง Liquidity Grab Detection (Turtle Soup Core Logic)
The script scans for recent swing highs/lows using a user-defined lookback.
A signal is generated when price breaks above/below a previous swing level but closes back inside โ indicating a liquidity run and likely reversal.
A special Wick Trap Mode enhances this logic by detecting long-wick fakeouts โ where the wick grabs stops but the candle body closes opposite the breakout direction.
๐ Trend Filter with ATR Buffer
Optional trend filter uses a simple moving average (SMA) to gauge market direction.
Instead of hard filtering, it applies an ATR-based buffer to allow for entries near the trend line, reducing signal suppression from micro-fluctuations.
๐ฐ๏ธ Kill Zone Session Filtering
Only show signals during institutional trading hours:
London Session
New York AM
Or any custom user-defined session
Helps traders avoid low-volume hours and focus on where stop hunts and price expansions typically occur.
๐งฑ Multi-Timeframe FVG Confluence (Optional)
Signal validation is strengthened by checking if price is within a higher timeframe Fair Value Gap โ commonly used to identify imbalances or inefficiencies.
Filters out setups that lack underlying displacement or order flow justification.
๐จ Visual Feedback
Plots ๐บ bullish and ๐ป bearish markers at signal candles.
Optionally displays:
Swing High/Low Labels (SH / SL)
Reversal distance labels
Background color shading on valid signals
Includes built-in alerts for automated trade notification.
๐ Unique Benefits
Wick Trap Detection: A proprietary approach to detecting stop hunts via wick behavior, not just candle closes.
ATR-based trend filtering: Avoids unnecessary filtering while still maintaining directional bias.
All-in-one system: No need to stack multiple indicators โ swing detection, reversal logic, session filtering, and imbalance confirmation are all integrated.
๐ก How to Use
Enable Wick Trap Mode to detect stealthy liquidity grabs with strong wicks.
Use Kill Zone filters to trade only when institutions are active.
Optionally enable FVG confluence to improve confidence in reversal zones.
Watch for Bullish signals near SL levels and Bearish signals near SH levels.
Combine with your own execution strategy or other SMC tools for optimal results.
๐ Best Used With:
Maximize your edge by combining this script with complementary SMC-based tools:
โ
First FVG โ Opening Range Fair Value Gap Detector
โ
ICT SMC Liquidity Grabs + OB + Fibonacci OTE Levels
โ
Liquidity Levels โ Smart Swing Highs and Lows with horizontal line projections
Pivot S/R with Volatility Filter## *๐ Indicator Purpose*
This indicator identifies *key support/resistance levels* using pivot points while also:
โ
Detecting *high-volume liquidity traps* (stop hunts)
โ
Filtering insignificant pivots via *ATR (Average True Range) volatility*
โ
Tracking *test counts and breakouts* to measure level strength
---
## *โ SETTINGS โ Detailed Breakdown*
### *1๏ธโฃ โ General Settings*
#### *๐น Pivot Length*
- *Purpose:* Determines how many bars to analyze when identifying pivots.
- *Usage:*
- *Low values (5-20):* More pivots, better for scalping.
- *High values (50-200):* Fewer but stronger levels for swing trading.
- *Example:*
- Pivot Length = 50 โ Only the most significant highs/lows over 50 bars are marked.
#### *๐น Test Threshold (Max Test Count)*
- *Purpose:* Sets how many times a level can be tested before being invalidated.
- *Example:*
- Test Threshold = 3 โ After 3 tests, the level is ignored (likely to break).
#### *๐น Zone Range*
- *Purpose:* Creates a price buffer around pivots (ยฑ0.001 by default).
- *Why?* Markets often respect "zones" rather than exact prices.
---
### *2๏ธโฃ โ Volatility Filter (ATR)*
#### *๐น ATR Period*
- *Purpose:* Smoothing period for Average True Range calculation.
- *Default:* 14 (standard for volatility measurement).
#### *๐น ATR Multiplier (Min Move)*
- *Purpose:* Requires pivots to show *meaningful price movement*.
- *Formula:* Min Move = ATR ร Multiplier
- *Example:*
- ATR = 10 pips, Multiplier = 1.5 โ Only pivots with *15+ pip swings* are valid.
#### *๐น Show ATR Filter Info*
- Displays current ATR and minimum move requirements on the chart.
---
### *3๏ธโฃ โ Volume Analysis*
#### *๐น Volume Change Threshold (%)*
- *Purpose:* Filters for *unusual volume spikes* (institutional activity).
- *Example:*
- Threshold = 1.2 โ Requires *120% of average volume* to confirm signals.
#### *๐น Volume MA Period*
- *Purpose:* Lookback period for "normal" volume calculation.
---
### *4๏ธโฃ โ Wick Analysis*
#### *๐น Wick Length Threshold (Ratio)*
- *Purpose:* Ensures rejection candles have *long wicks* (strong reversals).
- *Formula:* Wick Ratio = (Upper Wick + Lower Wick) / Candle Range
- *Example:*
- Threshold = 0.6 โ 60% of the candle must be wicks.
#### *๐น Min Wick Size (ATR %)*
- *Purpose:* Filters out small wicks in volatile markets.
- *Example:*
- ATR = 20 pips, MinWickSize = 1% โ Wicks under *0.2 pips* are ignored.
---
### *5๏ธโฃ โ Display Settings*
- *Show Zones:* Toggles support/resistance shaded areas.
- *Show Traps:* Highlights liquidity traps (โฒ/โผ symbols).
- *Show Tests:* Displays how many times levels were tested.
- *Zone Transparency:* Adjusts opacity of zones.
---
## *๐ฏ Practical Use Cases*
### *1๏ธโฃ Liquidity Trap Detection*
- *Scenario:* Price spikes *above resistance* then reverses sharply.
- *Requirements:*
- Long wick (Wick Ratio > 0.6)
- High volume (Volume > Threshold)
- *Outcome:* *Short Trap* signal (โผ) appears.
### *2๏ธโฃ Strong Support Level*
- *Scenario:* Price bounces *3 times* from the same level.
- *Indicator Action:*
- Labels the level with test count (3/5 = 3 tests out of max 5).
- Turns *red* if broken (Break Count > 0).
Deep Dive: How This Indicator Works*
This indicator combines *four professional trading concepts* into one powerful tool:
1. *Classic Pivot Point Theory*
- Identifies swing highs/lows where price previously reversed
- Unlike basic pivot indicators, ours uses *confirmed pivots only* (filtered by ATR)
2. *Volume-Weighted Validation*
- Requires unusual trading volume to confirm levels
- Filters out "phantom" levels with low participation
3. *ATR Volatility Filtering*
- Eliminates insignificant price swings in choppy markets
- Ensures only meaningful levels are plotted
4. *Liquidity Trap Detection*
- Spots institutional stop hunts where markets fake out traders
- Uses wick analysis + volume spikes for high-probability signals
---
Deep Dive: How This Indicator Works*
This indicator combines *four professional trading concepts* into one powerful tool:
1. *Classic Pivot Point Theory*
- Identifies swing highs/lows where price previously reversed
- Unlike basic pivot indicators, ours uses *confirmed pivots only* (filtered by ATR)
2. *Volume-Weighted Validation*
- Requires unusual trading volume to confirm levels
- Filters out "phantom" levels with low participation
3. *ATR Volatility Filtering*
- Eliminates insignificant price swings in choppy markets
- Ensures only meaningful levels are plotted
4. *Liquidity Trap Detection*
- Spots institutional stop hunts where markets fake out traders
- Uses wick analysis + volume spikes for high-probability signals
---
## *๐ Parameter Encyclopedia (Expanded)*
### *1๏ธโฃ Pivot Engine Settings*
#### *Pivot Length (50)*
- *What It Does:*
Determines how many bars to analyze when searching for swing highs/lows.
- *Professional Adjustment Guide:*
| Trading Style | Recommended Value | Why? |
|--------------|------------------|------|
| Scalping | 10-20 | Captures short-term levels |
| Day Trading | 30-50 | Balanced approach |
| Swing Trading| 50-200 | Focuses on major levels |
- *Real Market Example:*
On NASDAQ 5-minute chart:
- Length=20: Identifies levels holding for ~2 hours
- Length=50: Finds levels respected for entire trading day
#### *Test Threshold (5)*
- *Advanced Insight:*
Institutions often test levels 3-5 times before breaking them. This setting mimics the "probe and push" strategy used by smart money.
- *Psychology Behind It:*
Retail traders typically give up after 2-3 tests, while institutions keep testing until stops are run.
---
### *2๏ธโฃ Volatility Filter System*
#### *ATR Multiplier (1.0)*
- *Professional Formula:*
Minimum Valid Swing = ATR(14) ร Multiplier
- *Market-Specific Recommendations:*
| Market Type | Optimal Multiplier |
|------------------|--------------------|
| Forex Majors | 0.8-1.2 |
| Crypto (BTC/ETH) | 1.5-2.5 |
| SP500 Stocks | 1.0-1.5 |
- *Why It Matters:*
In EUR/USD (ATR=10 pips):
- Multiplier=1.0 โ Requires 10 pip swings
- Multiplier=1.5 โ Requires 15 pip swings (fewer but higher quality levels)
---
### *3๏ธโฃ Volume Confirmation System*
#### *Volume Threshold (1.2)*
- *Institutional Benchmark:*
- 1.2x = Moderate institutional interest
- 1.5x+ = Strong smart money activity
- *Volume Spike Case Study:*
*Before Apple Earnings:*
- Normal volume: 2M shares
- Spike threshold (1.2): 2.4M shares
- Actual volume: 3.1M shares โ STRONG confirmation
---
### *4๏ธโฃ Liquidity Trap Detection*
#### *Wick Analysis System*
- *Two-Filter Verification:*
1. *Wick Ratio (0.6):*
- Ensures majority of candle shows rejection
- Formula: (UpperWick + LowerWick) / Total Range > 0.6
2. *Min Wick Size (1% ATR):*
- Prevents false signals in flat markets
- Example: ATR=20 pips โ Min wick=0.2 pips
- *Trap Identification Flowchart:*
Price Enters Zone โ
Spikes Beyond Level โ
Shows Long Wick โ
Volume > Threshold โ
TRAP CONFIRMED
---
## *๐ก Master-Level Usage Techniques*
### *Institutional Order Flow Analysis*
1. *Step 1:* Identify pivot levels with โฅ3 tests
2. *Step 2:* Watch for volume contraction near levels
3. *Step 3:* Enter when trap signal appears with:
- Wick > 2รATR
- Volume > 1.5ร average
### *Multi-Timeframe Confirmation*
1. *Higher TF:* Find weekly/monthly pivots
2. *Lower TF:* Use this indicator for precise entries
3. *Example:*
- Weekly pivot at $180
- 4H shows liquidity trap โ High-probability reversal
---
## *โ Critical Mistakes to Avoid*
1. *Using Default Settings Everywhere*
- Crude oil needs higher ATR multiplier than bonds
2. *Ignoring Trap Context*
- Traps work best at:
- All-time highs/lows
- Major psychological numbers (00/50 levels)
3. *Overlooking Cumulative Volume*
- Check if volume is building over multiple tests
Money Flow Divergence IndicatorOverview
The Money Flow Divergence Indicator is designed to help traders and investors identify key macroeconomic turning points by analyzing the relationship between U.S. M2 money supply growth and the S&P 500 Index (SPX). By comparing these two crucial economic indicators, the script highlights periods where market liquidity is outpacing or lagging behind stock market growth, offering potential buy and sell signals based on macroeconomic trends.
How It Works
1. Data Sources
S&P 500 Index (SPX500USD): Tracks the stock market performance.
U.S. M2 Money Supply (M2SL - Federal Reserve Economic Data): Represents available liquidity in the economy.
2. Growth Rate Calculation
SPX Growth: Percentage change in the S&P 500 index over time.
M2 Growth: Percentage change in M2 money supply over time.
Growth Gap (Delta): The difference between M2 growth and SPX growth, showing whether liquidity is fueling or lagging behind market performance.
3. Visualization
A histogram displays the growth gap over time:
Green Bars: M2 growth exceeds SPX growth (potential bullish signal).
Red Bars: SPX growth exceeds M2 growth (potential bearish signal).
A zero line helps distinguish between positive and negative growth gaps.
How to Use It
โ
Bullish Signal: When green bars appear consistently, indicating that liquidity is outpacing stock market growth. This suggests a favorable environment for buying or holding positions.
โ Bearish Signal: When red bars appear consistently, meaning stock market growth outpaces liquidity expansion, signaling potential overvaluation or a market correction.
Best Timeframes for Analysis
This indicator works best on monthly timeframes (M) since it is designed for long-term investors and macro traders who focus on broad economic cycles.
Who Should Use This Indicator?
๐ Long-term investors looking for macroeconomic trends.
๐ Swing traders who incorporate liquidity analysis in their strategies.
๐ฐ Portfolio managers assessing market liquidity conditions.
๐ Use this indicator to stay ahead of market trends and make informed investment decisions based on macroeconomic liquidity shifts! ๐
