IQ Liquidation Heatmap [TradingIQ]Introducing "IQ Liquidation Heatmap".
IQ Liquidation Heatmap is a proprietary indicator designed to identify and display price zones where large numbers of crypto position liquidations are likely to occur. It presents both current liquidation zones—areas where a cascade of liquidations would be triggered if the price is reached—and historical liquidation zones, where such events have taken place before.
Why Liquidations and Liquidation Cascades Are Important
Liquidation cascades are important because they can lead to rapid and significant price moves in the market. When many traders have set stop-loss orders or are highly leveraged at similar price levels, a move that hits these zones can force a large number of positions to close at once. This mass closing of positions not only accelerates the price movement but can also trigger further liquidations in a self-reinforcing loop.
Understanding where these cascades occur helps traders recognize potential support and resistance levels. It also provides insights into where market participants are most vulnerable, allowing for better risk management and more informed trading decisions. In short, liquidation cascades highlight key areas of market stress that can lead to increased volatility and opportunities for those prepared to act.
In short, if a lot of short positions are liquidated simultaneously, an upside liquidation cascade can occur. During an upside liquidation cascade, price will increase intensely to the upside with high volatility.
If a lot of long positions are liquidated simultaneously, a downside liquidation cascade can occur. During a downside liquidation cascade, price will decrease intensely to the downside with high volatility.
Knowing where these liquidation cascades can occur is invaluable information for crypto traders.
What IQ Liquidation Heatmap Does
IQ Liquidation Heatmap visually maps price levels that have seen or may see liquidation cascades. In plain terms, it shows you where many stop-losses or leveraged positions have been triggered in the past and where similar events can occur in the future. By highlighting these zones, the indicator helps you understand areas of market stress that could lead to rapid price movements.
The image above shows a historical liquidation cascade occurring. Clustered bubbles show large amounts of liquidations occurring - the more bubbles and the brighter they are, the stronger the liquidation cascade. During a liquidation cascade, there is a higher chance that a strong downtrend or uptrend will continue.
Current Liquidation Levels
The image above explains current liquidation levels.
Current liquidations levels are price areas where a large number of positions will be liquidated. If a liquidation level is above the current price, then it is considered a price zone where shorts will be liquidated. If a liquidation level is below the current price, then it is considered a price zone where longs will be liquidated.
In this image, bright green levels represent price areas where the highest amount of positions will be liquidated, while dark purple levels represent price areas where the lowest amount of positions will be liquidated.
An active (current) liquidation level will extend to the right beyond the current price because they have not yet been hit.
When strong liquidation levels (green - bright green) are hit and are above price, it is expected that an upside liquidation cascade will occur. When strong liquidations are hit and are below price, it is expected that a downside liquidation cascade will occur.
Historical Liquidation Levels
The image above explains historical liquidation levels.
Historical liquidation levels stop at the bar where they are hit, so you can see how price responded to hitting a key liquidation level.
In this image, bright green levels represent price areas where the highest amount of positions will be liquidated, while dark purple levels represent price areas where the lowest amount of positions will be liquidated.
If price moves up into a liquidation level, then shorts are being liquidated. If price moves down into a liquidation level, then longs are being liquidated. In the image, we can see that when bright green liquidation levels were hit - a liquidation cascade occurred. During this cascade, price continued to move strongly to the downside with high volatility.
During the uptrend after the downtrend, we can see some bright green liquidation levels were also hit - causing an upside liquidation cascade that resulted in strong, volatile upside price moves.
Gradient Bar
The image above explains the liquidations gradient bar.
The bar located on the right of your chart shows what colors correspond to low, medium, and high liquidation levels.
In this image, bright green means the liquidation level is strong, while dark purple means the liquidation level is weak. By extension, we would expect liquidation cascades or strong price moves to more likely occur when a cluster of bright green liquidation zones are hit. Additionally, we would expect a small reaction (or no reaction at all) when dark purple liquidation zones are hit.
Colors are customizable.
Liquidation Cluster Bar
The image above explains the liquidation cluster bar.
The liquidation cluster bar aggregates liquidation zones and shows the approximate price areas where the highest number of liquidation points are located.
In this image, the green portion of the bar represents where the largest number of traders will be liquidated in aggregate. While the purple portions of the bar shows where the smallest number of traders will be liquidated in aggregate.
This bar is useful for clustering liquidations zones across larger price areas to see where the highest number of traders are likely to be liquidated.
Concept Behind IQ Liquidation Heatmap
The basic idea is simple: in crypto markets, when price reaches certain levels, many traders’ positions can be liquidated at once, causing sharp moves in price. These zones are not random. They are built on historical price data and statistical analysis of past liquidation events. IQ Liquidation Heatmap captures this information and presents it in an easy-to-read format.
Key points include:
Current Liquidation Zones: These are the areas where, if the price moves into them, a high number of liquidations could occur.
Historical Liquidation Zones: These show where liquidation cascades have happened in the past, offering context on how the market has behaved under stress.
Key Features of IQ Liquidation Heatmap
Real-Time and Historical Data:
The indicator combines current market conditions with historical liquidation events. It updates dynamically to reflect real-time data while also showing past liquidation zones.
Visual Heatmap:
The display uses color gradients to represent the intensity of liquidation activity. Brighter or more intense colors indicate zones with a higher likelihood of triggering liquidations, while darker colors represent areas with lower activity.
User-Friendly Interface:
IQ Liquidation Heatmap is designed to be simple and straightforward. The visual output clearly marks the price levels of interest, making it easy for traders to see where liquidations might occur.
Proprietary Calculation:
The data behind the indicator is calculated using proprietary methods that consider historical price action, statistical ranges, and liquidity distribution. This means the indicator adapts to the specific characteristics of different crypto assets and timeframes.
Dynamic Updates:
The indicator recalculates its output in real time as new price data comes in. This ensures that the displayed liquidation zones are always current and reflect the latest market conditions.
How IQ Liquidation Heatmap Works
Data Collection:
IQ Liquidation Heatmap gathers historical price data as well as data on liquidation events. This data is used to identify key price ranges and levels where liquidations have previously occurred.
Statistical Analysis:
The indicator applies statistical methods—such as calculating medians and percentiles—to determine the significance of each price range. This analysis helps to rank the importance of various liquidation zones.
Liquidity Clustering:
Areas with a high concentration of liquidations are identified by examining how many positions or stop orders are clustered at specific price levels. These clusters are then represented on the chart using a heatmap style.
Visual Mapping:
The calculated data is overlaid onto the trading chart. Graphical elements like lines, boxes, or filled regions mark the identified liquidation zones. Color gradients help to differentiate between zones with high versus low liquidation risk.
Real-Time Recalculation:
As new price data becomes available, IQ Liquidation Heatmap continuously updates its analysis. This ensures that the indicator remains relevant throughout the trading session and can quickly adjust if market conditions change.
Using IQ Liquidation Heatmap
Traders can use IQ Liquidation Heatmap as an additional tool to support their trading decisions. Here are some practical applications:
Trade Entry And Exit Planning:
The visual cues provided by the indicator can serve as reference points for planning entries and exits. When the price nears a zone known for triggering liquidations, traders can adjust their strategies accordingly.
Risk Management:
By identifying key liquidation zones, traders can better manage risk. Knowing where a liquidation cascade is likely to occur helps in setting more effective stop-loss orders and managing overall exposure.
Market Structure Analysis:
The historical data offered by IQ Liquidation Heatmap gives insight into how the market has reacted in the past during periods of stress. This historical perspective can help in understanding broader market trends and potential future movements.
Summary
IQ Liquidation Heatmap is a straightforward indicator that provides clear visual information about price levels where liquidation cascades have occurred or are likely to occur. By merging historical data with real-time updates and proprietary liquidity analysis, it offers traders a neutral and data-driven way to understand areas of potential market stress for entries and exits. The indicator is simple to use and does not require complex adjustments, making it suitable for traders looking for clear visual cues in the crypto market.
By incorporating IQ Liquidation Heatmap into your analysis toolkit, you can gain a better understanding of key price zones, support effective risk management, and identify liquidation cascades before they occur and potentially identify breakouts before they occur.
Statistics
15% Below Daily LowESPP discount pricing (15%) - Line chart that follows the daily low of the chart to show what price you could buy a company stock with the typical discount of 15%.
Global M2 Money SupplyAn indicator looking at the total money, of the largest economies, in circulation. I like to use it to analyze the lag between Bitcoin and liquidity. I think 109 days or a 16 week delay is the most accurate lag when contrasting both charts together (you can manually change the offset in the indicator's settings).
Round Numbers Round Numbers – A Visual Guide to Key Psychological Price Levels
The Round Numbers indicator highlights key psychological price levels, specifically 500s and 1000s, which frequently act as support and resistance zones. This tool automatically detects and plots horizontal lines at these critical price points, helping traders analyze market structure with clarity.
Features:
Plots horizontal lines at every 500 & 1000 price level (e.g., $20,500, $21,000, $21,500).
Customizable settings:
Line color, style (solid, dashed, dotted).
Font type selection (Comic Sans, Century Gothic, Sans, Serif, Mono).
Text color customization.
Formatted price labels with currency symbols (e.g., $20,500).
Adjustable line length – Choose how many candles back the lines extend (1-500 bars).
No background on price labels – Clean, non-intrusive design.
How It Helps Traders:
Support & Resistance Trading – Round numbers often act as reversal or breakout zones.
Scalping & Day Trading – Quickly identify psychological price barriers in fast-moving markets.
Swing Trading & Long-Term Analysis – Spot major price clusters where buyers and sellers react.
This indicator is suitable for Forex, Stocks, Crypto, and Futures traders who rely on psychological price levels for precision trading.
David Capital | Power Of 3## David Capital | Power Of 3
*A Dynamic Structure-Based Indicator for Smart Market Manipulation Recognition*
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### 📌 What it does
This indicator implements a dynamic interpretation of the Power Of 3 (PO3) methodology. Unlike generic PO3 indicators, this version constructs consolidation zones based on mathematical structure, and detects precise manipulation setups with built-in confirmations.
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### ⚙️ How it works
- The indicator identifies consolidation zones using dynamic candle analysis (at least 5 inside bars).
- After a breakout (manipulation) from the zone, it looks for a confirmation candle that:
- Sweeps the high/low of the breakout candle (wick only),
- Closes back within the zone,
- Closes in the opposite direction (color flip).
- When all conditions are met, a signal is triggered (LONG or SHORT).
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### 🧠 Why it's different
Most indicators leave discretion to the trader. This tool builds **a mechanical execution system** based on 3 years of backtesting logic and dynamic structure recognition. It filters out noise and only highlights statistically meaningful opportunities.
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### 🎯 Entry Logic
- Entry signals appear as labels on the chart (LONG / SHORT).
- Alerts are sent at the close of confirmation candles.
- Entry type can be set to "Aggressive" or "Passive" (future expansion).
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### ✅ Usage Notes
- Best used on 5M/15M charts for precision.
- Does not repaint.
- No other indicators are required.
- Script is closed-source due to proprietary structure and logic.
avgPrice - Accum./Dist.I would explain the understanding of " FREQUENCY " and how it is built and realized in this indicator: " avgPrice - Accum./Dist " and " avgPrice - VF20 ".
Let's look at the explanation:
BASIC KNOWLEDGE ON FREQUENCY
FOR TRADERS
If you are a Trader, then read this article. This article means a lot to you, and will change many things about your life in the trading world.
The knowledge in this article is very secret, the main key to success for traders You would not found it anywhere, search all youtube shows, articles on websites, you would not found it. It even takes a very long time for you to realize it, most are not aware and do not know it. You would only know if you are told.
First of all, about "frequency"
Frequency is a unit in a single buy and sell transaction. In one time, for example in one minute, the number of times each transaction occurs is different. This difference will be closely related to the level of liquidity and volatility. We can see that the frequency is divided into three, 1) low frequency, 2) medium frequency, and 3) high frequency.
In one trading day, the market is open for 4 hours, or for 245 minutes. If we look at the IDX:ADRO stock on March 5, 2022, the frequency is 50,339, and if divided by 245 minutes, then every minute there are 205 frequencies. If reduced again in seconds, it means that every second there are 3.5 frequencies or if rounded up, there are 3 buy and sell transactions every second. While the IDX:KREN stock on March 5, 2022, the frequency is 3,552, and if divided by 245 minutes, then every minute there are 14.5 frequencies. If reduced again in seconds, it means that every 4 seconds there is 1 frequency. This shows that the IDX:ADRO stock has a high frequency, while the IDX:KREN stock has a low frequency.
So the higher the frequency, the lower the risk. Because it will avoid sudden price drops. Because in high frequency, Buyer or Seller find it difficult to go to many ticks, because it has only gone down 1 tick, there are already many other Buyers and Sellers blocking it. Therefore, the higher the frequency, the more liquid a stock is, and the lower the volatility. Conversely, the lower the frequency, the less liquid a stock is and the higher the volatility.
We know that stocks with low frequency, less liquid, and high volatility are high risk stocks , less safe for your capital. Conversely, stocks with high frequency, more liquid, and low volatility are low risk stocks , very safe for your capital.
Because in high frequency stocks, when you have a stoploss target, when the price drops to your stoploss target price position, you can exit quickly. Unlike low frequency stocks, when you have a stoploss target, once it drops it can immediately fall 5% - 10% down, if you don't have time to cutloss, your capital can immediately bleed in one hit.
VOLUME & FREQUENCY
Generally, the ratio of the volume is the same as the frequency. However, if the volume is greater than the frequency, it means that each transaction of buying and selling uses big money. The use of big money in transactions is a sign that the transaction is carried out by a big player/big fund. Conversely, if the volume is smaller than the frequency, it means that each transaction of buying and selling uses small money. The use of small money in transactions is a sign that the transaction is carried out by a small player/retailer.
It can be interpreted that volume> frequency = accumulation and volume < frequency = distribution. So if volume> frequency indicates that the price in the future is highly likely to increase. Conversely, if volume < frequency indicates that the price in the future is highly likely to decrease.
To make it easier to measure the risk ratio of volume divided by frequency, we can use the symbol V/F. The smaller the V/F means " distribution ", and the larger the V/F means " accumulation ". See the my own indicator namely: Louded Candle
After basic knowledge about frequency and its relationship to volume, we call it VF , which is volume divided by frequency. See the my own indicator namely: avgPrice - VF20
And this indicator you see is called " avgPrice - Accum./ Dist. " The point is to find out the accumulation area and distribution area . As mentioned in the description above, that volume > frequency = accumulation and volume < frequency = distribution. This indicator is built on the basis of this understanding.
If you want to discuss further, please just chat me, I would always be happy to reply. For the sake of knowledge and for everyone to be able to generate consistent profits in the trading world
Enjoy, hopefully useful.
Ratio S/RRatio S/R - Intraday Support & Resistance Levels
Introduction
This script identifies key intraday support and resistance (S/R) levels where price tends to reverse frequently. It is designed specifically for intraday trading and aims to help traders find high-probability reversal zones.
The logic behind the script revolves around logarithmic returns, historical volatility, and ratio-based price levels. The script dynamically calculates price ranges using standard deviation-based volatility and applies preset ratio levels to determine potential support and resistance zones.
How It Works
Dynamic Range Calculation
The script calculates the price range based on the previous day’s logarithmic return volatility.
The range is then used to project different levels of price movement.
Reference Price
You can choose whether the reference price is from today’s open or yesterday’s close (oporcl setting).
This helps adapt the levels based on market behavior.
Ratio-Based Levels
The script applies specific ratios to the calculated range:
0.0833 (Minor Reversal Zone)
0.25 & 0.38 (Primary Reversal Zones)
0.62 & 0.75 (Significant Reversal Zones)
1.0 & 1.25 (Extreme Reversal Zones)
These levels act as potential support and resistance points.
Disclaimer: This is just for educational purpose . Trading is risky activity and how you use this tool is your own responsibility. The publisher of this tool does not make any claims.
Entry Price Ranges with Winrate and Average ProfitOnce you have registered the analyzed win rate and average return rate, they will be displayed on the chart.
You can visually grasp the poor performance of a trade depending on the price range you enter.
Intended for use with VIX.
Market Conditions with RSI v6Market Conditions with RSI Indicator
This indicator combines price action, volume, and RSI (Relative Strength Index) to identify market conditions and generate trading signals.
What It Does
The indicator classifies market conditions into four categories:
1.Strong Bullish: When price is rising, volume is up, and the volume-based "open interest" is increasing
2.Weak Bullish: When price is rising, but volume is down, and the volume-based "open interest" is decreasing
3.Weak Bearish: When price is declining, volume is up, and the volume-based "open interest" is increasing
4.Strong Bearish: When price is declining, volume is down, and the volume-based "open interest" is decreasing
These market conditions are then combined with RSI readings to generate buy and sell signals.
## How to Use It
1. Add the indicator to your TradingView chart
2. The indicator will display below your price chart (since it's not an overlay)
3. Look for buy signals (green triangles at the bottom) and sell signals (red triangles at the top)
4. Use the color-coded background to quickly identify the current market condition
5. Check the information table in the top-right corner for detailed metrics
What It Shows
1. RSI Line: The blue line showing the Relative Strength Index value
2. Background Color:
- Green = Strong Bullish
- Light Green = Weak Bullish
- Orange = Weak Bearish
- Red = Strong Bearish
3. Buy Signals (green triangles) appear when:
- Strong Bullish condition with RSI below 50 (catching momentum early)
- Weak Bearish condition with RSI below 30 (oversold opportunity)
4. Sell Signals (red triangles) appear when:
- Strong Bearish condition with RSI above 50 (catching downward momentum)
- Weak Bullish condition with RSI above 70 (overbought opportunity)
5. Information Table showing:
- Current market condition
- RSI value
- Price direction (rising/declining)
- Volume status (up/down)
- Volume-based "open interest" proxy (up/down)
Customization Options
You can adjust:
- RSI Length (default: 14)
- RSI Overbought Level (default: 70)
- RSI Oversold Level (default: 30)
- Volume Moving Average Length (default: 20)
- "Open Interest" Moving Average Length (default: 20)
Open Price on Selected TimeframeIndicator Name: Open Price on Selected Timeframe
Short Title: Open Price mtf
Type: Technical Indicator
Description:
Open Price on Selected Timeframe is an indicator that displays the Open price of a specific timeframe on your chart, with the ability to dynamically change the color of the open price line based on the change between the current candle's open and the previous candle's open.
Selectable Timeframes: You can choose the timeframe you wish to monitor the Open price of candles, ranging from M1, M5, M15, H1, H4 to D1, and more.
Dynamic Color Change: The Open price line changes to green when the open price of the current candle is higher than the open price of the previous candle, and to red when the open price of the current candle is lower than the open price of the previous candle. This helps users quickly identify trends and market changes.
Features:
Easy Timeframe Selection: Instead of editing the code, users can select the desired timeframe from the TradingView interface via a dropdown.
Dynamic Color Change: The color of the Open price line changes automatically based on whether the open price of the current candle is higher or lower than the previous candle.
Easily Track Open Price Levels: The indicator plots a horizontal line at the Open price of the selected timeframe, making it easy for users to track this important price level.
How to Use:
Select the Timeframe: Users can choose the timeframe they want to track the Open price of the candles.
Interpret the Color Signal: When the open price of the current candle is higher than the open price of the previous candle, the Open price line is colored green, signaling an uptrend. When the open price of the current candle is lower than the open price of the previous candle, the Open price line turns red, signaling a downtrend.
Observe the Open Price Levels: The indicator will draw a horizontal line at the Open price level of the selected timeframe, allowing users to easily monitor this important price.
Benefits:
Enhanced Technical Analysis: The indicator allows you to quickly identify trends and market changes, making it easier to make trading decisions.
User-Friendly: No need to modify the code; simply select your preferred timeframe to start using the indicator.
Disclaimer:
This indicator is not a complete trading signal. It only provides information about the Open price and related trends. Users should combine it with other technical analysis tools to make more informed trading decisions.
Summary:
Open Price on Selected Timeframe is a simple yet powerful indicator that helps you track the Open price on various timeframes with the ability to change colors dynamically, providing a visual representation of the market's trend.
Multi-Signal Trading Indicator (MSTI)Multi-Signal Trading Indicator (MSTI)
Overview
The Multi-Signal Trading Indicator (MSTI) is a comprehensive technical analysis tool that combines eight powerful indicators into a single, unified system. Designed to identify high-probability trading opportunities, MSTI generates precise buy and sell signals by analyzing multiple market factors simultaneously. The indicator excels at detecting potential reversals and trend continuations while filtering out market noise.
Key Features
8 Core Technical Components
MACD: Identifies momentum changes and potential trend reversals
RSI: Detects overbought and oversold conditionsн
Bollinger Bands: Analyzes price volatility and extreme conditions
Stochastic Oscillator: Identifies potential turning points in price
Moving Averages: Confirms trend direction using dual SMAs
Volume Analysis: Validates price movements with volume confirmation
Fibonacci Levels: Identifies key support/resistance areas
Divergence Detection: Spots divergences between price and momentum
Advanced Predictive Capabilities
Volume Surge Detection: Identifies significant volume increases that often precede major price movements
Enhanced Divergence Analysis: Detects both regular and hidden divergences for early reversal signals
Support/Resistance Tests: Identifies successful tests of key support/resistance zones
Momentum Change Detection: Spots early shifts in price momentum using Rate of Change
Order Flow Analysis: Tracks buying/selling pressure through On-Balance Volume
Signal Quality Management
Adjustable Signal Thresholds: Customize the number of conditions required for signal generation
Multiple Quality Levels: Choose between Normal, High, and Maximum quality settings
Strength Measurement: Displays signal strength as a percentage for better decision-making
Repeat Signal Prevention: Eliminates duplicate signals to reduce noise
Visual Features
Clear Chart Markers: Buy/sell signals displayed directly on price chart
Comprehensive Info Panel: Shows status of all components and overall signal information
Customizable Colors: Adjust visual elements to match your chart theme
Practical Applications
For Day Traders
Identify short-term reversal points with high accuracy
Validate entries with multiple confirmations
Filter out false signals during choppy market conditions
For Swing Traders
Spot early trend changes before they become obvious
Enter positions with higher confidence and precision
Hold positions through noise by following true trend signals
For Position Traders
Identify major trend reversals with multiple confirmations
Filter out minor retracements from significant trend changes
Time entries and exits with greater precision
Customization Options
MSTI is highly customizable with over 30 adjustable parameters allowing you to:
Fine-tune each technical component
Adjust signal quality and filtering
Enable/disable specific components
Customize visual appearance
Usage Tips
Start with the Normal quality setting to understand signal frequency
Progress to High or Maximum settings for fewer but higher quality signals
Adjust minimum conditions based on market volatility
Enable trend filter in trending markets for better signal accuracy
Enable volatility filter to avoid signals during low-volatility periods
The Multi-Signal Trading Indicator is a powerful tool for traders of all experience levels, combining the strength of multiple technical indicators to provide clear, actionable trading signals.
Frequency Analyzer by Dean EarwickerThis indicator is called a frequency analyzer to detect whale activity. It works to detect exploding candles, before they explode.
Black–Scholes model - Options premium calculatorBlack-Scholes Options Pricing Calculator in Pine Script Introduction
The Black-Scholes model is one of the most widely used mathematical models for pricing options. It provides a theoretical estimate of the price of European-style options based on factors such as the underlying asset price, strike price, time to expiration, volatility, risk-free rate, and option type.
This Pine Script implementation of the Black-Scholes options pricing model enables traders to calculate call and put option prices directly within TradingView, helping them assess potential trades more efficiently.
What Does This Script Do?
This script allows traders to input essential option parameters and instantly calculate both call and put option prices using the Black-Scholes formula. It provides:
• A user-friendly interface for inputting option parameters.
• Automatic computation of option prices.
• Real-time updates as market data changes.
Key Features:
• Uses the Black-Scholes formula to compute European call and put option prices.
• User-defined inputs for stock price, strike price, time to expiration, volatility, and risk-free rate.
• Displays calculated option prices on the TradingView chart.
Understanding the Black-Scholes Formula:
The Black-Scholes model is given by the following equations:
C=S0N(d1)−Xe−rtN(d2)C = S_0 N(d_1) - Xe^{-rt} N(d_2) P=Xe−rtN(−d2)−S0N(−d1)P = Xe^{-rt} N(-d_2) - S_0 N(-d_1)
Where:
• CC = Call option price
• PP = Put option price
• S0S_0 = Current stock price
• XX = Strike price
• rr = Risk-free interest rate
• tt = Time to expiration (in years)
• σ\sigma = Volatility of the stock (annualized)
• N(x)N(x) = Cumulative standard normal distribution
• d1d_1 and d2d_2 are given by:
d1=ln(S0/X)+(r+σ2/2)tσtd_1 = \frac{ \ln(S_0/X) + (r + \sigma^2/2)t }{ \sigma \sqrt{t} } d2=d1−σtd_2 = d_1 - \sigma \sqrt{t}
This script implements these calculations efficiently in Pine Script to help traders quickly determine fair values for options based on current market conditions.
Example Calculation:
(The following example values were true at the time of publishing this script. Option prices fluctuate constantly, so actual values may vary.)
• Underlying asset price (NIFTY): 23,519.35
• ATM Call Strike Price: 23,500
• ATM Put Strike Price: 23,550
• IV (Implied Volatility) for Call Option: 8.1%
• IV (Implied Volatility) for Put Option: 10.1%
• Expiry Date: April 3, 2025
Using the Black-Scholes model, the calculated theoretical prices are:
• Theoretical ATM CE price: ₹129
• Theoretical ATM PE price: ₹118
For comparison, the actual option prices from the option chain table at the time of writing were:
• Actual ATM CE price: ₹139.70
• Actual ATM PE price: ₹120.30
As we can see, there is a larger difference between the theoretical price and actual market price for the ATM Call option compared to the ATM Put option.
If you're an experienced trader, you likely know how to use this kind of information to identify potential market inefficiencies or trading opportunities.
How to Use This Script:
1. Add the script to your TradingView chart.
2. Input the necessary parameters such as stock price, strike price, volatility, risk-free rate, and time to expiration.
3. View the calculated call and put option prices directly on the chart.
This Black-Scholes options pricing calculator provides a convenient way to compute theoretical option prices within TradingView. It helps traders analyse whether an option is fairly priced based on market conditions.
While the Black-Scholes model has its limitations (e.g., it does not account for early exercise of American options or dividend payments), it remains a powerful tool for European-style options pricing and a foundational concept in financial markets.
A handy little tool! Unfortunately, this script requires manual data entry since automatic data capture is currently not possible. If this ever becomes feasible in the future, an updated version will be released.
Try it out and let me know your feedback!
Disclaimer:
Please note that this is only for study/educational purpose and is just one of the many tools a trader may use.
Use it at your own risk.
Regards!
SPY Frequent Trading Strategythis is my SPY long term trading strategy:
entry if all conditions are met:
5 day rs is below 30
5 day rsi reading is down for the third day in a row
5 day rsi was below 60 three trading days ago
the close is higher than the 200 day moving average
exit when the 5 day rsi is above 50
I want to convert it into a strategy that trades more frequently, so adjust the rules so that it willl be taking multiple trades a week. and build it in pine script
Candle Height & Trend Probability DashboardDescription and Guide
Description:
This Pine Script for TradingView displays a dashboard that calculates the probability of price increases or decreases based on past price movements. It analyzes the last 30 candles (by default) and shows the probabilities for different timeframes (from 1 minute to 1 week). Additionally, it checks volatility using the ATR indicator.
Script Features:
Calculates probabilities of an upward (Up %) or downward (Down %) price move based on past candles.
Displays a dashboard showing probabilities for multiple timeframes.
Color-coded probability display:
Green if the upward probability exceeds a set threshold.
Red if the downward probability exceeds the threshold.
Yellow if neither threshold is exceeded.
Considers volatility using the ATR indicator.
Triggers alerts when probabilities exceed specific values.
How to Use:
Insert the script into TradingView: Copy and paste the script into the Pine Script editor.
Adjust parameters:
lookback: Number of past candles used for calculation (default: 30).
alertThresholdUp & alertThresholdDown: Thresholds for probabilities (default: 51%).
volatilityLength & volatilityThreshold: ATR volatility settings.
dashboardPosition: Choose where the dashboard appears on the chart.
Enable visualization: The dashboard will be displayed over the chart.
Set alerts: The script triggers notifications when probabilities exceed set thresholds.
Strategy Stats [presentTrading]Hello! it's another weekend. This tool is a strategy performance analysis tool. Looking at the TradingView community, it seems few creators focus on this aspect. I've intentionally created a shared version. Welcome to share your idea or question on this.
█ Introduction and How it is Different
Strategy Stats is a comprehensive performance analytics framework designed specifically for trading strategies. Unlike standard strategy backtesting tools that simply show cumulative profits, this analytics suite provides real-time, multi-timeframe statistical analysis of your trading performance.
Multi-timeframe analysis: Automatically tracks performance metrics across the most recent time periods (last 7 days, 30 days, 90 days, 1 year, and 4 years)
Advanced statistical measures: Goes beyond basic metrics to include Information Coefficient (IC) and Sortino Ratio
Real-time feedback: Updates performance statistics with each new trade
Visual analytics: Color-coded performance table provides instant visual feedback on strategy health
Integrated risk management: Implements sophisticated take profit mechanisms with 3-step ATR and percentage-based exits
BTCUSD Performance
The table in the upper right corner is a comprehensive performance dashboard showing trading strategy statistics.
Note: While this presentation uses Vegas SuperTrend as the underlying strategy, this is merely an example. The Stats framework can be applied to any trading strategy. The Vegas SuperTrend implementation is included solely to demonstrate how the analytics module integrates with a trading strategy.
⚠️ Timeframe Limitations
Important: TradingView's backtesting engine has a maximum storage limit of 10,000 bars. When using this strategy stats framework on smaller timeframes such as 1-hour or 2-hour charts, you may encounter errors if your backtesting period is too long.
Recommended Timeframe Usage:
Ideal for: 4H, 6H, 8H, Daily charts and above
May cause errors on: 1H, 2H charts spanning multiple years
Not recommended for: Timeframes below 1H with long history
█ Strategy, How it Works: Detailed Explanation
The Strategy Stats framework consists of three primary components: statistical data collection, performance analysis, and visualization.
🔶 Statistical Data Collection
The system maintains several critical data arrays:
equityHistory: Tracks equity curve over time
tradeHistory: Records profit/loss of each trade
predictionSignals: Stores trade direction signals (1 for long, -1 for short)
actualReturns: Records corresponding actual returns from each trade
For each closed trade, the system captures:
float tradePnL = strategy.closedtrades.profit(tradeIndex)
float tradeReturn = strategy.closedtrades.profit_percent(tradeIndex)
int tradeType = entryPrice < exitPrice ? 1 : -1 // Direction
🔶 Performance Metrics Calculation
The framework calculates several key performance metrics:
Information Coefficient (IC):
The correlation between prediction signals and actual returns, measuring forecast skill.
IC = Correlation(predictionSignals, actualReturns)
Where Correlation is the Pearson correlation coefficient:
Correlation(X,Y) = (nΣXY - ΣXY) / √
Sortino Ratio:
Measures risk-adjusted return focusing only on downside risk:
Sortino = (Avg_Return - Risk_Free_Rate) / Downside_Deviation
Where Downside Deviation is:
Downside_Deviation = √
R_i represents individual returns, T is the target return (typically the risk-free rate), and n is the number of observations.
Maximum Drawdown:
Tracks the largest percentage drop from peak to trough:
DD = (Peak_Equity - Trough_Equity) / Peak_Equity * 100
🔶 Time Period Calculation
The system automatically determines the appropriate number of bars to analyze for each timeframe based on the current chart timeframe:
bars_7d = math.max(1, math.round(7 * barsPerDay))
bars_30d = math.max(1, math.round(30 * barsPerDay))
bars_90d = math.max(1, math.round(90 * barsPerDay))
bars_365d = math.max(1, math.round(365 * barsPerDay))
bars_4y = math.max(1, math.round(365 * 4 * barsPerDay))
Where barsPerDay is calculated based on the chart timeframe:
barsPerDay = timeframe.isintraday ?
24 * 60 / math.max(1, (timeframe.in_seconds() / 60)) :
timeframe.isdaily ? 1 :
timeframe.isweekly ? 1/7 :
timeframe.ismonthly ? 1/30 : 0.01
🔶 Visual Representation
The system presents performance data in a color-coded table with intuitive visual indicators:
Green: Excellent performance
Lime: Good performance
Gray: Neutral performance
Orange: Mediocre performance
Red: Poor performance
█ Trade Direction
The Strategy Stats framework supports three trading directions:
Long Only: Only takes long positions when entry conditions are met
Short Only: Only takes short positions when entry conditions are met
Both: Takes both long and short positions depending on market conditions
█ Usage
To effectively use the Strategy Stats framework:
Apply to existing strategies: Add the performance tracking code to any strategy to gain advanced analytics
Monitor multiple timeframes: Use the multi-timeframe analysis to identify performance trends
Evaluate strategy health: Review IC and Sortino ratios to assess predictive power and risk-adjusted returns
Optimize parameters: Use performance data to refine strategy parameters
Compare strategies: Apply the framework to multiple strategies to identify the most effective approach
For best results, allow the strategy to generate sufficient trade history for meaningful statistical analysis (at least 20-30 trades).
█ Default Settings
The default settings have been carefully calibrated for cryptocurrency markets:
Performance Tracking:
Time periods: 7D, 30D, 90D, 1Y, 4Y
Statistical measures: Return, Win%, MaxDD, IC, Sortino Ratio
IC color thresholds: >0.3 (green), >0.1 (lime), <-0.1 (orange), <-0.3 (red)
Sortino color thresholds: >1.0 (green), >0.5 (lime), <0 (red)
Multi-Step Take Profit:
ATR multipliers: 2.618, 5.0, 10.0
Percentage levels: 3%, 8%, 17%
Short multiplier: 1.5x (makes short take profits more aggressive)
Stop loss: 20%
Spent Output Profit Ratio (SOPR) Z-Score | [DeV]SOPR Z-Score
The Spent Output Profit Ratio (SOPR) is an advanced on-chain metric designed to provide deep insights into Bitcoin market dynamics by measuring the ratio between the combined USD value of all Bitcoin outputs spent on a given day and their combined USD value at the time of creation (typically, their purchase price). As a member of the Realized Profit/Loss family of metrics, SOPR offers a window into aggregate seller behavior, effectively representing the USD amount received by sellers divided by the USD amount they originally paid. This indicator enhances this metric by normalizing it into a Z-Score, enabling a statistically robust analysis of market sentiment relative to historical trends, augmented by a suite of customizable features for precision and visualization.
SOPR Settings -
Lookback Length (Default: 150 days): Determines the historical window for calculating the Z-Score’s mean and standard deviation. A longer lookback captures broader market cycles, providing a stable baseline for identifying extreme deviations, which is particularly valuable for long-term strategic analysis.
Smoothing Period (Default: 100 days): Applies an EMA to the raw SOPR, balancing responsiveness to recent changes with noise reduction. This extended smoothing period ensures the indicator focuses on sustained shifts in seller behavior, ideal for institutional-grade trend analysis.
Moving Average Settings -
MA Lookback Length (Default: 90 days): Sets the period for the Z-Score’s moving average, offering a shorter-term trend signal relative to the 150-day Z-Score lookback. This contrast enhances the ability to detect momentum shifts within the broader context.
MA Type (Default: EMA): Provides six moving average types, from the simple SMA to the volume-weighted VWMA. The default EMA strikes an optimal balance between smoothness and responsiveness, while alternatives like HMA (Hull) or VWMA (volume-weighted) allow for specialized applications, such as emphasizing recent price action or incorporating volume dynamics.
Display Settings -
Show Moving Average (Default: True): Toggles the visibility of the Z-Score MA plot, enabling users to focus solely on the raw Z-Score when preferred.
Show Background Colors (Default: True): Activates dynamic background shading, enhancing visual interpretation of market regimes.
Background Color Source (Default: SOPR): Allows users to tie the background color to either the SOPR Z-Score’s midline (reflecting adjustedZScore > 0) or the MA’s trend direction (zScoreMA > zScoreMA ). This dual-source option provides flexibility to align the visual context with the primary analytical focus.
Analytical Applications -
Bear Market Resistance: When the Z-Score approaches or exceeds zero (raw SOPR near 1), it often signals resistance as sellers rush to exit at break-even, a pattern historically observed during downtrends. A rising Z-Score MA crossing zero can confirm this pressure.
Bull Market Support: Conversely, a Z-Score dropping below zero in uptrends indicates reluctance to sell at a loss, forming support as sell pressure diminishes. The MA’s bullish coloring reinforces confirmation of renewed buying interest.
Extreme Deviations: Values significantly above or below zero highlight overbought or oversold conditions, respectively, offering opportunities for contrarian positioning when paired with other on-chain or price-based metrics.
Econometrica by [SS]This is Econometrica, an indicator that aims to bridge a big gap between the resources available for analysis of fundamental data and its impact on tickers and price action.
I have noticed a general dearth of available indicators that offer insight into how fundamentals impact a ticker and provide guidance on how they these economic factors influence ticker behaviour.
Enter Econometrica. Econometrica is a math based indicator that aims to co-integrate and model indicator price action in relation to critical economic metrics.
Econometrica supports the following US based economic data:
CPI
Non-Farm Payroll
Core Inflation
US Money Supply
US Central Bank Balance Sheet
GDP
PCE
Let's go over the functions of Econometrica.
Creating a Regression Cointegrated Model
The first thing Econometrica does is creates a co-integrated regression, as you see in the main chart, predicting ticker value ranges from fundamental economic data.
You can visualize this in the main chart above, but here are some other examples:
SPY vs Core Inflation:
BA vs PCE:
QQQ vs US Balance Sheet:
The band represents the anticipated range the ticker should theoretically fall in based on the underlying economic value. The indicator will breakdown the relationship between the economic indicator and the ticker more precisely. In the images above, you can see how there are some metrics provided, including Stationairty, lagged correlation, Integrated Correlation and R2. Let's discuss these very briefly:
Stationarity: checks to ensure that the relationship between the economic indicator and ticker is stationary. Stationary data is important for making unbiased inferences and projections, so having data that is stationary is valuable.
Lagged Correlation: This is a very interesting metric. Lagged correlation means whether there is a delay in the economic indicator and the response of the ticker. Typically, you will observed a lagged correlation between an economic indicator and price of a ticker, as it can take some time for economic changes to reach the market. This lagged correlation will provide you with how long it takes for the economic indicator to catch up with the ticker in months.
Integrated Correlation: This metric tells you how good of a fit the regression bands are in relation to the ticker price. A higher correlation, means the model is better at consistent and accurate information about the anticipated range for the ticker in relation to the economic indicator.
R2: Provides information on the variance and degree of model fit. A high R2 value means that the model is capable of explaining a large amount of variance between the economic indicator and the ticker price action.
Explaining the Relationship
Owning to the fact that the indicator is a bit on the mathy side (it has to be to do this kind of task), I have included ability for the indicator to explain and make suggestions based on the underlying data. It can assess the model's fit and make suggestions for tweaking. It can also explain the implications of the data being presented in the model.
Here is an example with QQQ and the US Balance Sheet:
This helps to simplify and interpret the results you are looking at.
Forecasting the Economic Indicator
In addition to assessing the economic indicator's impact on the ticker, the indicator is also capable of forecasting out the economic indicator over the next 25 releases.
Here is an example of the CPI forecast:
Overall use of the indicator
The indicator is meant to bridge the gap between Technical Analysis and Fundamental Analysis.
Any trader who is attune to fundamentals would benefit from this, as this provides you with objective data on how and to what extent fundamental and economic data impacts tickers.
It can help affirm hypothesis and dispel myths objectively.
It also omits the need from having to perform these types of analyses outside of Tradingview (i.e. in excel, R or Python), as you can get the data in just a few licks of enabling the indicator.
Conclusion
I have tried to make this indicator as user friendly as possible. Though it uses a lot of math, it is fairly straight forward to interpret.
The band plotted can be considered the fair market value or FMV of the ticker based on the underlying economic data, provided the indicator tells you that the relationship is significant (and it will blatantly give you this information verbatim, you don't have to interpret the math stuff).
This is US economic data only. It does not pull economic data from other countries. You can absolutely see how US economic data impacts other markets like the TSX, BANKNIFTY, NIFTY, DAX etc. but the indicator is only pulling US economic data.
That is it!
I hope you enjoy it and find this helpful!
Thanks everyone and safe trades as always 🚀🚀🚀
Trade Ladder Pro: Compounding & Risk ManagerTrade Ladder Pro: Compounding & Risk Manager
Inspired by the popular $20 to $52,000 trading challenge, this tool is designed to help you scale your trading account using systematic compounding and enhanced risk management techniques. Whether you’re aiming for disciplined growth or fine-tuning your risk/reward, Trade Ladder Pro offers a flexible approach to visualizing your trade levels.
How to Use:
Inputs:
Compounding Mode:
Set your starting balance, final balance goal, number of trades, and current trade level. You can move to the next trade after a successful trade in settings. The entries are not signals. They are there to help manage risk.
The script calculates the necessary compounding factor to grow your balance across the defined trades.
Risk Management Mode:
In addition to the above, specify a risk percentage and risk/reward ratio.
Input an entry price (or leave it at 0 to use the current price) to automatically compute the stop loss and take profit levels.
Display Options:
Choose the table’s position on the chart (e.g., Top Right, Top Left, Bottom Right, Bottom Left).
Pick between a vertical or horizontal layout for a display that suits your workflow.
Results:
The table will display the trade level, starting balance, risk amount, entry price, take profit, and (if in Risk Management mode) stop loss along with the projected ending balance.
Community & Feedback:
Your feedback is invaluable! Please share any tips or report any errors you encounter so we can continue to improve this tool. Happy trading!
Smart % Levels📈 Smart % Levels – Visualize Significant Percentage Moves
What it does:
This indicator plots horizontal levels based on a percentage change from the previous day's close (or open, if selected). It allows traders to visualize price movements relative to meaningful thresholds like ±1%, ±2%, etc.
What makes it different:
Unlike other level indicators, Smart % Levels only displays the relevant levels based on current price action. This avoids clutter by showing only the levels that are being approached or crossed by the current price. It's a clean and dynamic way to visualize key price zones for intraday analysis.
How it works:
- Select between using the previous day's Close or Open as the reference
- Choose the percentage spacing between levels (e.g., 1%, 0.5%, etc.)
- Enable optional labels to see the exact percentage of each level
- Automatically filters levels to only show those between yesterday's price and today's current price
- Includes customization for colors, line styles, widths, and opacity
Best for:
Day traders and scalpers who want a quick, clean view of how far the current price has moved from yesterday’s reference, without being overwhelmed by unnecessary lines.
Extra notes:
- The levels are recalculated each day at the market open
- All graphics reset at the start of each session to maintain clarity
- This script avoids repainting by only plotting levels relative to available historical data (no lookahead)
This tool is for informational purposes only and should not be considered as financial advice. Always do your own research before making trading decisions.
ATR & PTR TableThe ATR & PTR Table Indicator displays a dynamic table that provides Average True Range (measures market volatility over 1D, 1W, and 1M timeframes), Price trading range (difference between the high and low prices over the same periods) & percentage of the typical range that has been traded. This indicator will help traders identify potential breakout zones and assess volatility across multiple timeframes.
This had been optimized to show ATR and PTR on every time frame. The (1D) represents ATR on whatever timeframe you are currently on.
ML Deep Regression Pro (TechnoBlooms)ML Deep Regression Pro is a machine-learning-inspired trading indicator that integrates Polynomial Regression, Linear Regression and Statistical Deviation models to provide a powerful, data-driven approach to market trend analysis.
Designed for traders, quantitative analysts and developers, this tool transforms raw market data into predictive trend insights, allowing for better decision-making and trend validation.
By leveraging statistical regression techniques, ML Deep Regression Pro eliminates market noise and identifies key trend shifts, making it a valuable addition to both manual and algorithmic trading strategies.
REGRESSION ANALYSIS
Regression is a statistical modeling technique used in machine learning and data science to identify patterns and relationships between variables. In trading, it helps detect price trends, reversals and volatility changes by fitting price data into a predictive model.
1. Linear Regression -
The most widely used regression model in trading, providing a best-fit plotted line to track price trends.
2. Polynomial Regression -
A more advanced form of regression that fits curved price structures, capturing complex market cycles and improving trend forecasting accuracy.
3. Standard Deviation Bands -
Based on regression calculations, these bands measure price dispersion and identify overbought/ oversold conditions, similar to Bollinger Bands. By default, these lines are hidden and user can make it visible through Settings.
KEY FEATURES :-
✅ Hybrid Regression Engine – Combines Linear and Polynomial Regression to detect market trends with greater accuracy.
✅ Dynamic Trend Bias Analysis – Identifies bullish & bearish market conditions using real-time regression models.
✅ Standard Deviation Bands – Measures price volatility and potential reversals with an advanced deviation model.
✅ Adaptive EMA Crossover Signals – Generates buy/sell signals when price momentum shifts relative to the regression trend.
