Call ratio spread debit indicatorCall ratio spread debit indicator developed by Chobotaru Brothers.
You need to have basic knowledge in option trading to use this indicator!
This spread is a DEBIT SPREAD.
The indicator shows P&L lines of the options strategy. Use only for stocks since the mathematical model of options for Future instruments is different from stocks. Plus, the days' representation in futures is also different from stocks (stocks have fewer days than futures ).
***Each strategy in options is based on different mathematical equations, use this indicator only for the strategy in the headline.***
What does the indicator do?
The indicator is based on the Black-Scholes model, which uses partial differential equations to determine the option pricing. Due to options non-linear behavior, it is hard to visualize the option price. The indicator calculates the solutions of the Black-Scholes equation and plots them on the chart so traders can view how the option pricing will behave.
How the indicator does it?
The indicator uses five values (four dominants and one less dominant) to solve the Black-Scholes equation. The values are stock price, the strike price of the option, time to expiration, risk-free interest rate, and implied volatility .
How the indicator help the users?
-View the risks and rewards so you can know the profit targets in advance which means you can compare different options in different strikes.
-View the volatility change impact so you can know the risk and the P&L changes in case of a change in the volatility over the life of the option before you enter the trade.
-View the passage of time impact so you can know where and when you could realize a profit.
-Multi-timeframes so you can stay on the same chart (Daily and below).
All these features are to help the user improve his analysis while trading options.
How to use it?
The user needs to obtain from the “option chain” the following inputs:
-Debit paid: The debit paid for one unit of options strategy. Minimum value: 0. 01 .
-Instrument price when entered spread: the stock price when you enter the options strategy.
-Upper strike price: the upper strike price of the options strategy.
-Lower strike price: the lower strike price of the options strategy.
- Upper Strike numbers of calls . This number has to be greater than the number of calls that were bought.
- Lower Strike number of calls . This number has to be less than the number of calls that were sold.
-Interest rate: find the risk-free interest rate from the U.S. DEPARTMENT OF THE TREASURY. Example: for 2% interest rate, input: 0.02.
-Days to expire: how many days until the option expires.
-Volatility: the implied volatility of the option bought/sold. Example: for 45% implied volatility , input: 0.45.
-Day of entry: A calendar day of the month that the option bought/sold.
-Month of entry: Calendar month the option bought/sold.
-Year of entry: Calendar year the option bought/sold.
After entering all the inputs, press Ok and you should see “Calculation Complete” on the chart.
The user should not change the entry date and days to expire inputs as time passes after he entered the trade.
How to access the indicator?
Use the link below to obtain access to the indicator
Search in scripts for "entry"
Call ratio spread Credit indicatorCall ratio spread credit indicator developed by Chobotaru Brothers.
You need to have basic knowledge in option trading to use this indicator!
This spread is a CREDIT SPREAD.
The indicator shows P&L lines of the options strategy. Use only for stocks since the mathematical model of options for Future instruments is different from stocks. Plus, the days' representation in futures is also different from stocks (stocks have fewer days than futures ).
***Each strategy in options is based on different mathematical equations, use this indicator only for the strategy in the headline.***
What does the indicator do?
The indicator is based on the Black-Scholes model, which uses partial differential equations to determine the option pricing. Due to options non-linear behavior, it is hard to visualize the option price. The indicator calculates the solutions of the Black-Scholes equation and plots them on the chart so traders can view how the option pricing will behave.
How the indicator does it?
The indicator uses five values (four dominants and one less dominant) to solve the Black-Scholes equation. The values are stock price, the strike price of the option, time to expiration, risk-free interest rate, and implied volatility .
How the indicator help the users?
-View the risks and rewards so you can know the profit targets in advance which means you can compare different options in different strikes.
-View the volatility change impact so you can know the risk and the P&L changes in case of a change in the volatility over the life of the option before you enter the trade.
-View the passage of time impact so you can know where and when you could realize a profit.
-Multi-timeframes so you can stay on the same chart (Daily and below).
All these features are to help the user improve his analysis while trading options.
How to use it?
The user needs to obtain from the “option chain” the following inputs:
-Credit received: The credit received for one unit of options strategy. Minimum value: 0. 01 .
-Instrument price when entered spread: the stock price when you enter the options strategy.
-Upper strike price: the upper strike price of the options strategy.
-Lower strike price: the lower strike price of the options strategy.
- Upper Strike numbers of calls . This number has to be greater than the number of calls that were bought.
- Lower Strike number of calls . This number has to be less than the number of calls that were sold.
-Interest rate: find the risk-free interest rate from the U.S. DEPARTMENT OF THE TREASURY. Example: for 2% interest rate, input: 0.02.
-Days to expire: how many days until the option expires.
-Volatility: the implied volatility of the option bought/sold. Example: for 45% implied volatility , input: 0.45.
-Day of entry: A calendar day of the month that the option bought/sold.
-Month of entry: Calendar month the option bought/sold.
-Year of entry: Calendar year the option bought/sold.
After entering all the inputs, press Ok and you should see “Calculation Complete” on the chart.
The user should not change the entry date and days to expire inputs as time passes after he entered the trade.
How to access the indicator?
Use the link below to obtain access to the indicator
Put Bull Spread indicatorPut bull spread indicator developed by Chobotaru Brothers.
You need to have basic knowledge in option trading to use this indicator!
This spread is a CREDIT SPREAD.
The indicator shows P&L lines of the options strategy. Use only for stocks since the mathematical model of options for Future instruments is different from stocks. Plus, the days' representation in futures is also different from stocks (stocks have fewer days than futures ).
***Each strategy in options is based on different mathematical equations, use this indicator only for the strategy in the headline.***
What does the indicator do?
The indicator is based on the Black-Scholes model, which uses partial differential equations to determine the option pricing. Due to options non-linear behavior, it is hard to visualize the option price. The indicator calculates the solutions of the Black-Scholes equation and plots them on the chart so traders can view how the option pricing will behave.
How the indicator does it?
The indicator uses five values (four dominants and one less dominant) to solve the Black-Scholes equation. The values are stock price, the strike price of the option, time to expiration, risk-free interest rate, and implied volatility .
How the indicator help the users?
-View the risks and rewards so you can know the profit targets in advance which means you can compare different options in different strikes.
-View the volatility change impact so you can know the risk and the P&L changes in case of a change in the volatility over the life of the option before you enter the trade.
-View the passage of time impact so you can know where and when you could realize a profit.
-Multi-timeframes so you can stay on the same chart (Daily and below).
All these features are to help the user improve his analysis while trading options.
How to use it?
The user needs to obtain from the “option chain” the following inputs:
- Put spread price (Credit): The credit received for one unit of options strategy.
-Instrument price when entered spread: the stock price when you enter the options strategy.
-Upper strike price: the upper strike price of the options strategy.
-Lower strike price: the lower strike price of the options strategy.
-Interest rate: find the risk-free interest rate from the U.S. DEPARTMENT OF THE TREASURY. Example: for 2% interest rate, input: 0.02.
-Days to expire: how many days until the option expires.
-Volatility: the implied volatility of the option bought/sold. Example: for 45% implied volatility , input: 0.45.
-Day of entry: A calendar day of the month that the option bought/sold.
-Month of entry: Calendar month the option bought/sold.
-Year of entry: Calendar year the option bought/sold.
-% of Max Profit/Loss: Profit/loss line defined by the user. Minimum input (-0.95) ; maximum input (0.95).
Example: In this spread, -0.95 means, 95% of the options strategy maximum loss is reached and, 0.95 means, 95% of the options strategy maximum profit is reached.
After entering all the inputs, press Ok and you should see “Calculation Complete” on the chart.
The user should not change the entry date and days to expire inputs as time passes after he entered the trade.
How to access the indicator?
Use the link below to obtain access to the indicator
Put Bear Spread indicatorPut bear spread indicator developed by Chobotaru Brothers.
You need to have basic knowledge in option trading to use this indicator!
This spread is a DEBIT SPREAD.
The indicator shows P&L lines of the options strategy. Use only for stocks since the mathematical model of options for Future instruments is different from stocks. Plus, the days' representation in futures is also different from stocks (stocks have fewer days than futures ).
***Each strategy in options is based on different mathematical equations, use this indicator only for the strategy in the headline.***
What does the indicator do?
The indicator is based on the Black-Scholes model, which uses partial differential equations to determine the option pricing. Due to options non-linear behavior, it is hard to visualize the option price. The indicator calculates the solutions of the Black-Scholes equation and plots them on the chart so traders can view how the option pricing will behave.
How the indicator does it?
The indicator uses five values (four dominants and one less dominant) to solve the Black-Scholes equation. The values are stock price, the strike price of the option, time to expiration, risk-free interest rate, and implied volatility .
How the indicator help the users?
-View the risks and rewards so you can know the profit targets in advance which means you can compare different options in different strikes.
-View the volatility change impact so you can know the risk and the P&L changes in case of a change in the volatility over the life of the option before you enter the trade.
-View the passage of time impact so you can know where and when you could realize a profit.
-Multi-timeframes so you can stay on the same chart (Daily and below).
All these features are to help the user improve his analysis while trading options.
How to use it?
The user needs to obtain from the “option chain” the following inputs:
- Put spread price (Debit): The debit paid for one unit of options strategy.
-Instrument price when entered spread: the stock price when you enter the options strategy.
-Upper strike price: the upper strike price of the options strategy.
-Lower strike price: the lower strike price of the options strategy.
-Interest rate: find the risk-free interest rate from the U.S. DEPARTMENT OF THE TREASURY. Example: for 2% interest rate, input: 0.02.
-Days to expire: how many days until the option expires.
-Volatility: the implied volatility of the option bought/sold. Example: for 45% implied volatility , input: 0.45.
-Day of entry: A calendar day of the month that the option bought/sold.
-Month of entry: Calendar month the option bought/sold.
-Year of entry: Calendar year the option bought/sold.
-% of Max Profit/Loss: Profit/loss line defined by the user. Minimum input (-0.95) ; maximum input (0.95).
Example: In this spread, -0.95 means, 95% of the options strategy maximum loss is reached and, 0.95 means, 95% of the options strategy maximum profit is reached.
After entering all the inputs, press Ok and you should see “Calculation Complete” on the chart.
The user should not change the entry date and days to expire inputs as time passes after he entered the trade.
How to access the indicator?
Use the link below to obtain access to the indicator
Iron Condor / butterfly buy or sell indicatorIron Condor / butterfly indicator developed by Chobotaru Brothers.
You need to have basic knowledge in option trading to use this indicator!
The indicator shows P&L lines of the options strategy. Use only for stocks since the mathematical model of options for Future instruments is different from stocks. Plus, the days' representation in futures is also different from stocks (stocks have fewer days than futures ).
***Each strategy in options is based on different mathematical equations, use this indicator only for the strategy in the headline.***
What does the indicator do?
The indicator is based on the Black-Scholes model, which uses partial differential equations to determine the option pricing. Due to options non-linear behavior, it is hard to visualize the option price. The indicator calculates the solutions of the Black-Scholes equation and plots them on the chart so traders can view how the option pricing will behave.
How the indicator does it?
The indicator uses five values (four dominants and one less dominant) to solve the Black-Scholes equation. The values are stock price, the strike price of the option, time to expiration, risk-free interest rate, and implied volatility .
How the indicator help the users?
-View the risks and rewards so you can know the profit targets in advance which means you can compare different options in different strikes.
-View the volatility change impact so you can know the risk and the P&L changes in case of a change in the volatility over the life of the option before you enter the trade.
-View the passage of time impact so you can know where and when you could realize a profit.
-Multi-timeframes so you can stay on the same chart (Daily and below).
All these features are to help the user improve his analysis while trading options.
How to use it?
The user needs to obtain from the “option chain” the following inputs:
-Buy or sell (the strategy)
- Iron Condor price bought/sold: enter the price that you bought/sold one options strategy.
-Instrument price when bought/sold: the stock price when you bought/sold the options strategy.
-Upper strike price Top: the top upper strike price of the options strategy.
-Lower strike price Top: the top lower strike price of the options strategy.
-Upper strike price Bottom: the bottom upper strike price of the options strategy.
-Lower strike price Bottom: the bottom lower strike price of the options strategy.
-Interest rate: find the risk-free interest rate from the U.S. DEPARTMENT OF THE TREASURY. Example: for 2% interest rate, input: 0.02.
-Days to expire: how many days until the option expires.
-Volatility: the implied volatility of the option bought/sold. Example: for 45% implied volatility , input: 0.45.
-Day of entry: A calendar day of the month that the option bought/sold.
-Month of entry: Calendar month the option bought/sold.
-Year of entry: Calendar year the option bought/sold.
-% of Profit/Loss: Profit/loss line defined by the user. Minimum input (-0.95) ; maximum input (0.95).
Example: If the strategy was bought, -0.95 means, 95% of the options strategy maximum loss is reached. : If the strategy was bought, 0.95 means, 95% of the options strategy maximum profit is reached.
After entering all the inputs, press Ok and you should see “Calculation Complete” on the chart.
The user should not change the entry date and days to expire inputs as time passes after he entered the trade.
How to access the indicator?
Use the link below to obtain access to the indicator
Straddle / strangle buy or sell indicatorStraddle / strangle buy or sell indicator developed by Chobotaru Brothers.
You need to have basic knowledge in option trading to use this indicator!
The indicator shows P&L lines of the options strategy. Use only for stocks since the mathematical model of options for Future instruments is different from stocks. Plus, the days' representation in futures is also different from stocks (stocks have fewer days than futures ).
***Each strategy in options is based on different mathematical equations, use this indicator only for the strategy in the headline.***
What does the indicator do?
The indicator is based on the Black-Scholes model, which uses partial differential equations to determine the option pricing. Due to options non-linear behavior, it is hard to visualize the option price. The indicator calculates the solutions of the Black-Scholes equation and plots them on the chart so traders can view how the option pricing will behave.
How the indicator does it?
The indicator uses five values (four dominants and one less dominant) to solve the Black-Scholes equation. The values are stock price, the strike price of the option, time to expiration, risk-free interest rate, and implied volatility .
How the indicator help the users?
-View the risks and rewards so you can know the profit targets in advance which means you can compare different options in different strikes.
-View the volatility change impact so you can know the risk and the P&L changes in case of a change in the volatility over the life of the option before you enter the trade.
-View the passage of time impact so you can know where and when you could realize a profit.
-Multi-timeframes so you can stay on the same chart (Daily and below).
All these features are to help the user improve his analysis while trading options.
How to use it?
The user needs to obtain from the “option chain” the following inputs:
-Buy or sell (the strategy)
- Straddle/strangle price bought/sold: enter the price that you bought/sold one options strategy.
-Instrument price when bought/sold: the stock price when you bought/sold the options strategy.
-Upper strike price: the upper strike price of the options strategy.
-Lower strike price: the lower strike price of the options strategy.
-Interest rate: find the risk-free interest rate from the U.S. DEPARTMENT OF THE TREASURY. Example: for 2% interest rate, input: 0.02.
-Days to expire: how many days until the option expires.
-Volatility: the implied volatility of the option bought/sold. Example: for 45% implied volatility , input: 0.45.
-Day of entry: A calendar day of the month that the option bought/sold.
-Month of entry: Calendar month the option bought/sold.
-Year of entry: Calendar year the option bought/sold.
-Risk to reward: Profit/loss line defined by the user. Minimum input (-0.95) ; maximum input (3).
Example: If the strategy was bought, -0.95 means, 95% of the options strategy value is lost (unrealized). If the strategy was bought, 3 means, the risk to reward is 3.
After entering all the inputs, press Ok and you should see “Calculation Complete” on the chart.
The user should not change the entry date and days to expire inputs as time passes after he entered the trade.
How to access the indicator?
Use the link below to obtain access to the indicator
Call Bear Spread indicatorCall bear spread indicator developed by Chobotaru Brothers.
You need to have basic knowledge in option trading to use this indicator!
This spread is a CREDIT SPREAD.
The indicator shows P&L lines of the options strategy. Use only for stocks since the mathematical model of options for Future instruments is different from stocks. Plus, the days' representation in futures is also different from stocks (stocks have fewer days than futures ).
***Each strategy in options is based on different mathematical equations, use this indicator only for the strategy in the headline.***
What does the indicator do?
The indicator is based on the Black-Scholes model, which uses partial differential equations to determine the option pricing. Due to options non-linear behavior, it is hard to visualize the option price. The indicator calculates the solutions of the Black-Scholes equation and plots them on the chart so traders can view how the option pricing will behave.
How the indicator does it?
The indicator uses five values (four dominants and one less dominant) to solve the Black-Scholes equation. The values are stock price, the strike price of the option, time to expiration, risk-free interest rate, and implied volatility .
How the indicator help the users?
-View the risks and rewards so you can know the profit targets in advance which means you can compare different options in different strikes.
-View the volatility change impact so you can know the risk and the P&L changes in case of a change in the volatility over the life of the option before you enter the trade.
-View the passage of time impact so you can know where and when you could realize a profit.
-Multi-timeframes so you can stay on the same chart (Daily and below).
All these features are to help the user improve his analysis while trading options.
How to use it?
The user needs to obtain from the “option chain” the following inputs:
- Call spread price (Credit): The credit received for one unit of options strategy.
-Instrument price when entered spread: the stock price when you enter the options strategy.
-Upper strike price: the upper strike price of the options strategy.
-Lower strike price: the lower strike price of the options strategy.
-Interest rate: find the risk-free interest rate from the U.S. DEPARTMENT OF THE TREASURY. Example: for 2% interest rate, input: 0.02.
-Days to expire: how many days until the option expires.
-Volatility: the implied volatility of the option bought/sold. Example: for 45% implied volatility , input: 0.45.
-Day of entry: A calendar day of the month that the option bought/sold.
-Month of entry: Calendar month the option bought/sold.
-Year of entry: Calendar year the option bought/sold.
-% of Max Profit/Loss: Profit/loss line defined by the user. Minimum input (-0.95) ; maximum input (0.95).
Example: In this spread, -0.95 means, 95% of the options strategy maximum loss is reached and, 0.95 means, 95% of the options strategy maximum profit is reached.
After entering all the inputs, press Ok and you should see “Calculation Complete” on the chart.
The user should not change the entry date and days to expire inputs as time passes after he entered the trade.
How to access the indicator?
Use the link below to obtain access to the indicator
Call bull spread indicatorCall bull spread indicator developed by Chobotaru Brothers.
You need to have basic knowledge in option trading to use this indicator!
This spread is a DEBIT SPREAD.
The indicator shows P&L lines of the options strategy. Use only for stocks since the mathematical model of options for Future instruments is different from stocks. Plus, the days' representation in futures is also different from stocks (stocks have fewer days than futures ).
***Each strategy in options is based on different mathematical equations, use this indicator only for the strategy in the headline.***
What does the indicator do?
The indicator is based on the Black-Scholes model, which uses partial differential equations to determine the option pricing. Due to options non-linear behavior, it is hard to visualize the option price. The indicator calculates the solutions of the Black-Scholes equation and plots them on the chart so traders can view how the option pricing will behave.
How the indicator does it?
The indicator uses five values (four dominants and one less dominant) to solve the Black-Scholes equation. The values are stock price, the strike price of the option, time to expiration, risk-free interest rate, and implied volatility .
How the indicator help the users?
-View the risks and rewards so you can know the profit targets in advance which means you can compare different options in different strikes.
-View the volatility change impact so you can know the risk and the P&L changes in case of a change in the volatility over the life of the option before you enter the trade.
-View the passage of time impact so you can know where and when you could realize a profit.
-Multi-timeframes so you can stay on the same chart (Daily and below).
All these features are to help the user improve his analysis while trading options.
How to use it?
The user needs to obtain from the “option chain” the following inputs:
- Call spread price (Debit): The debit paid for one unit of options strategy.
-Instrument price when entered spread: the stock price when you enter the options strategy.
-Upper strike price: the upper strike price of the options strategy.
-Lower strike price: the lower strike price of the options strategy.
-Interest rate: find the risk-free interest rate from the U.S. DEPARTMENT OF THE TREASURY. Example: for 2% interest rate, input: 0.02.
-Days to expire: how many days until the option expires.
-Volatility: the implied volatility of the option bought/sold. Example: for 45% implied volatility , input: 0.45.
-Day of entry: A calendar day of the month that the option bought/sold.
-Month of entry: Calendar month the option bought/sold.
-Year of entry: Calendar year the option bought/sold.
-% of Max Profit/Loss: Profit/loss line defined by the user. Minimum input (-0.95) ; maximum input (0.95).
Example: In this spread, -0.95 means, 95% of the options strategy maximum loss is reached and, 0.95 means, 95% of the options strategy maximum profit is reached.
After entering all the inputs, press Ok and you should see “Calculation Complete” on the chart.
The user should not change the entry date and days to expire inputs as time passes after he entered the trade.
How to access the indicator?
Use the link below to obtain access to the indicator
Put option buy or sell indicatorPut option indicator developed by Chobotaru Brothers.
You need to have basic knowledge in option trading to use this indicator!
The indicator shows P&L lines of the options strategy. Use only for stocks since the mathematical model of options for Future instruments is different from stocks. Plus, the days' representation in futures is also different from stocks (stocks have fewer days than futures ).
***Each strategy in options is based on different mathematical equations, use this indicator only for the strategy in the headline.***
What does the indicator do?
The indicator is based on the Black-Scholes model, which uses partial differential equations to determine the option pricing. Due to options non-linear behavior, it is hard to visualize the option price. The indicator calculates the solutions of the Black-Scholes equation and plots them on the chart so traders can view how the option pricing will behave.
How the indicator does it?
The indicator uses five values (four dominants and one less dominant) to solve the Black-Scholes equation. The values are stock price, the strike price of the option, time to expiration, risk-free interest rate, and implied volatility .
How the indicator help the users?
-View the risks and rewards so you can know the profit targets in advance which means you can compare different options in different strikes.
-View the volatility change impact so you can know the risk and the P&L changes in case of a change in the volatility over the life of the option before you enter the trade.
-View the passage of time impact so you can know where and when you could realize a profit.
-Multi-timeframes so you can stay on the same chart (Daily and below).
All these features are to help the user improve his analysis while trading options.
How to use it?
The user needs to obtain from the “option chain” the following inputs:
-Buy or sell (the strategy)
-The option price bought: at what price did you bought/sold one option.
-Instrument price when bought: the stock price when you bought/sold the option.
-Strike price: the strike price of the option.
-Interest rate: find the risk-free interest rate from the U.S. DEPARTMENT OF THE TREASURY. Example: for 2% interest rate, input: 0.02.
-Days to expire: how many days until the option expires.
-Volatility: the implied volatility of the option bought/sold. Example: for 45% implied volatility , input: 0.45.
-Day of entry: A calendar day of the month that the option bought/sold.
-Month of entry: Calendar month the option bought/sold.
-Year of entry: Calendar year the option bought/sold.
-Risk to reward: Profit/loss line defined by the user. Minimum input (-0.95) ; maximum input (3).
Example: If an option was bought, -0.95 means, 95% of the option value is lost (unrealized). If an option was bought, 3 means, the risk to reward is 3.
After entering all the inputs, press Ok and you should see “Calculation Complete” on the chart.
The user should not change the entry date and days to expire inputs as time passes after he entered the trade.
How to access the indicator?
Use the link below to obtain access to the indicator
Call option buy or sell indicatorCall option indicator developed by Chobotaru Brothers.
You need to have basic knowledge in option trading to use this indicator!
The indicator shows P&L lines of the options strategy. Use only for stocks since the mathematical model of options for Future instruments is different from stocks. Plus, the days' representation in futures is also different from stocks (stocks have fewer days than futures ).
***Each strategy in options is based on different mathematical equations, use this indicator only for the strategy in the headline.***
What does the indicator do?
The indicator is based on the Black-Scholes model, which uses partial differential equations to determine the option pricing. Due to options non-linear behavior, it is hard to visualize the option price. The indicator calculates the solutions of the Black-Scholes equation and plots them on the chart so traders can view how the option pricing will behave.
How the indicator does it?
The indicator uses five values (four dominants and one less dominant) to solve the Black-Scholes equation. The values are stock price, the strike price of the option, time to expiration, risk-free interest rate, and implied volatility .
How the indicator help the users?
-View the risks and rewards so you can know the profit targets in advance which means you can compare different options in different strikes.
-View the volatility change impact so you can know the risk and the P&L changes in case of a change in the volatility over the life of the option before you enter the trade.
-View the passage of time impact so you can know where and when you could realize a profit.
-Multi-timeframes so you can stay on the same chart (Daily and below).
All these features are to help the user improve his analysis while trading options.
How to use it?
The user needs to obtain from the “option chain” the following inputs:
-Buy or sell (the strategy)
-The option price bought: at what price did you bought/sold one option.
-Instrument price when bought: the stock price when you bought/sold the option.
-Strike price: the strike price of the option.
-Interest rate: find the risk-free interest rate from the U.S. DEPARTMENT OF THE TREASURY. Example: for 2% interest rate, input: 0.02.
-Days to expire: how many days until the option expires.
-Volatility: the implied volatility of the option bought/sold. Example: for 45% implied volatility , input: 0.45.
-Day of entry: A calendar day of the month that the option bought/sold.
-Month of entry: Calendar month the option bought/sold.
-Year of entry: Calendar year the option bought/sold.
-Risk to reward: Profit/loss line defined by the user. Minimum input (-0.95) ; maximum input (3).
Example: If an option was bought, -0.95 means, 95% of the option value is lost (unrealized). If an option was bought, 3 means, the risk to reward is 3.
After entering all the inputs, press Ok and you should see “Calculation Complete” on the chart.
The user should not change the entry date and days to expire inputs as time passes after he entered the trade.
How to access the indicator?
Use the link below to obtain access to the indicator
SMMA Breakout ATR retest systemA fast, ATR-based SMMA breakout scalping system designed for Gold (XAUUSD). It can also be used on other Forex and Indices pairs. Uses breakout-retest confirmation, no-chase protection, and clean visual risk levels. Optimized for quick TP1 scalps with controlled drawdowns.
Quick Scalp TP1 — Checklist
🔧 Setup
☐ Symbol: XAUUSD
☐ Timeframe: 5m
☐ SMMA Length: 5
☐ ATR Length: 14
⚙️ Settings
☐ Stop Loss: 1.5× ATR
☐ Take Profit: ATR 1.2× (TP1 only)
☐ Show Entry/SL?TP Lines & Labels✅ ON
☐ Show Entry Arrows✅ ON
☐ Show Early Warning Labels on Chart✅ ON
☐ ATR Range Filter: ❌ OFF
☐ HTF Bias (15m / 1H): ❌OFF
☐ 15m Candle Body Filter: ❌ OFF
☐ NY Session Filter: ❌ OFF
☐ Retest Entry: ✅ ON
☐ No-Chase Filter: ✅ ON
📈 BUY and SELL Entry Rules :
✅ Long setup (BUY)
If Retest Entry is ON:
☐ 1. Price breaks above the 5-SMMA (raw breakout begins)
☐ 2. Price pulls back and retests near/into the SMMA
☐ 3. A confirmation candle closes back up and breaks the retest high
➡️ BUY arrow prints + risk panel switches to SIDE: LONG
If Retest Entry is OFF:
• The BUY arrow prints immediately when the price crosses above the 5-SMMA (if filters pass)
✅ Short setup (SELL)
Same idea, reversed:
☐ 1. Break below SMMA
☐ 2. Retest near/into SMMA
☐ 3. Confirmation closes down, and breaks retest low
➡️ SELL arrow prints + panel shows SIDE: SHORT
🎯 Trade Management
When a confirmed entry happens, the script prints/plot lines to show clearly:
• ENTRY
• SL (ATR-based)
• TP1
☐ Do not hold runners in this mode, take full profit at TP1
🔔 Alerts (Recommended) - Tradingview Essential Package will allow you to use alerts
Create these alerts:
Confirmed Entry Alerts
• GG BUY CONFIRMED
• GG SELL CONFIRMED
• Set to: ✅ Once per bar close
•Type in Alert Name and Message - SELL CONFIRMED or BUY CONFIRMED
• Enable: Popup + Sound
Early Warning Alerts (Optional)
• GG EARLY BUY WARNING
• GG EARLY SELL WARNING
• Set to: ✅ Once per bar
•Type in Alert Name and Message - Potential Buy forming of Potential Sell forming
• Used only as a heads-up, not an entry
⚠️ Important Notes / Disclaimer
This script is a technical analysis tool, not financial advice.
All trading involves risk. Always test settings on a demo before live use.
Results will vary depending on market conditions, broker execution, and risk settings.
MARAL - Ultra Filtered Execution Master EngineMARAL — Super Premium Execution Intelligence
Ultra-Filtered Master Engine + Signals + Entry Checklist + Live Execution Board
What “MARAL” Means
MARAL = Market Awareness + Risk Alignment + Action Logic
Built to align context → risk → decision clearly on the chart.
________________________________________
What MARAL
MARAL is a super-premium TradingView framework that provides:
• ✅ Sharp Buy/Sell signals
• ✅ Pre-entry permission using a visual checklist
• ✅ Post-entry trade management guidance via a live execution board
• ✅ Probability/score readability to support decisions under pressure
Most indicators stop at: “Buy/Sell.”
MARAL goes further: “Should I take it? Should I stay? Should I protect? Should I partially exit? Should I exit?”
________________________________________
Built From Real Trading (Loss → Discipline → System)
MARAL was developed from 3–4 years of live market study, including my own losses and wins.
It’s built for real execution reliability, not “perfect marketing backtests.”
________________________________________
Why MARAL Is Super Premium
Retail traders don’t fail only because of entries. They fail because of execution mistakes:
• entering without context (bias/structure/volatility mismatch)
• trading inside chop/range repeatedly
• holding losers + cutting winners (emotion exits)
• no partial-profit structure
• revenge trading
• late entries/late exits in overextended moves
MARAL is designed to reduce these execution errors with a structured workflow.
________________________________________
MARAL Architecture & “8-Layer” Intelligence
Many premium tools give 1–3 layers (signals + a couple confirmations).
MARAL is built as a multi-layer execution framework (~8 layers):
1. Signal Layer (Buy/Sell triggers)
2. Higher-Timeframe Bias Layer (directional alignment)
3. Structure Layer (bull/bear structure context)
4. Momentum Layer (RSI + Ultra-Filtered RSI confirmation)
5. Volatility Layer (ATR% tradability)
6. Trend-Strength Layer (ADX environment)
7. Scoring & Probability Layer (Long/Short score + trend vs reversal pressure)
8. Execution Layer (post-entry board: hold/protect/partial exit/exit)
This is why MARAL behaves like an execution intelligence system, not just an arrow tool.
________________________________________
Panel 1 — Ultra-Filtered Master Engine (The Brain)
The Ultra-Filtered Master Engine powers MARAL’s signals + context + scoring.
It continuously evaluates:
• Multi-timeframe bias agreement
• Structure confirmation
• Momentum quality (noise-filtered)
• Volatility & trend strength (tradability)
• Score & probability readability (trend vs reversal pressure)
Result: signals + context, not blind arrows.
________________________________________
Panel 2 — Entry Checklist (Pre-Entry Permission — No Signal Blocking)
Instead of hiding signals, MARAL shows a permission checklist that evaluates context and displays:
ENTRY / WAIT / SKIP
✅ Signals remain visible
✅ Reduces impulsive trades
✅ Trader stays in control
________________________________________
Panel 3 — Execution Board (Post-Entry Decision Support — Premium Edge)
A live execution board guides management decisions:
• Trade Status
• Market Phase (trend/range awareness)
• TP Probability
• Obstacle Ahead (nearby friction/risk)
• Exit Pressure
• Structure State
• Momentum Health
• Score Trend
• Risk State (includes Overextended)
• Trade Age
• Action: Hold / Protect / Partial Exit / Exit / Wait
________________________________________
Where MARAL Works (Clear & Honest)
MARAL is designed for liquid, directional instruments:
✅ Crypto: BTC/ETH + major liquid pairs
✅ Forex: major pairs
✅ Gold: XAUUSD
✅ Indices: major global indices
________________________________________
Important Note for Options Traders — Please Read Before Buying
MARAL is NOT recommended for options premium trading (especially short-dated/OTM), because option pricing is strongly affected by IV, Theta decay, Gamma, spreads, and expiry behavior.
Even if the underlying chart direction is correct, options can lose due to IV crush / time decay. Options require an options-specific model.
If your main trading is options buying/selling, please do not purchase.
________________________________________
MARAL in One Screenshot: How the System Thinks (XAUUSD Example).. Live chart examples and screenshots i will share TradingView posts for the below below example.
MARAL is not a “BUY/SELL arrow” indicator.
It is an Execution Intelligence Engine that gives you:
1. Direction (Bias)
2. Permission (Score + Filters)
3. Execution Guidance (Hold / Exit / Wait)
This is exactly why MARAL is premium: it tells you when to trade and when NOT to trade.
________________________________________
1) Direction Engine: Multi-Timeframe Bias (Trade ONLY with the flow)
In your screenshot, the info panel clearly shows:
• Last Signal: LONG
• Direction: Bullish
• H1 Bias: Bullish
• H4 Bias: Bullish
• Daily Bias: Bullish
• Structure: Bull Struct
✅ Meaning: MARAL is not randomly buying. It first confirms the market is aligned across timeframes, then it allows only LONG execution logic.
This alone filters out a huge number of low-quality trades.
________________________________________
2) Strength & Volatility Filter: “Is the move healthy or dangerous?”
From the same panel:
✅ Meaning: MARAL is measuring whether the move has real trend strength, not just “green candles”.
________________________________________
3) Score Engine: MARAL enters only when confirmations stack
This is the core premium layer:
✅ Meaning:
• MARAL gives a high-quality Long rating
• And it explicitly blocks shorts (“No-Trade”) even if a candle looks tempting.
So buyers understand: MARAL doesn’t overtrade. It filters.
________________________________________
4) Execution Board: The “Professional Dashboard” (why this is premium)
Your left panel says:
• TRADE STATUS: ✅ VALID
• MARKET PHASE: CONTINUATION
• TP PROBABILITY: HIGH
• OBSTACLE AHEAD: NO
• EXIT PRESSURE: LOW
• STRUCTURE: Bull Struct
• MOMENTUM HEALTH: STRONG
• RISK STATE: NORMAL
• ACTION: HOLD
✅ Meaning (simple for buyers):
MARAL is telling you:
“This is a continuation long. Probability is high. Risk is normal. Don’t panic. Hold the position.”
This is what most indicators never do. They give a signal and disappear.
MARAL stays with the trade and guides execution.
________________________________________
5) Signals on the chart: Why multiple BUY labels appear
You can see multiple BUY labels during the uptrend.
That is not “spam signals”. It’s continuation entries:
• After trend confirmation,
• MARAL allows re-entries/pyramiding opportunities only when the filters stay valid.
So the buyer sees:
✅ one system catching an entire move, not just one random entry.
________________________________________
6) The “WAIT” feature (this is a super-premium selling point)
On the right panel (Entry Checklist) you have:
• SETUP: WAIT
• ENTRY PERMISSION: WAIT
✅ Meaning:
Even in a bullish market, MARAL will say WAIT when conditions are not perfect (chop / uncertainty / missing confirmation).
This is the premium story:
“MARAL is not just signals. It tells you when NOT to trade.”
That prevents:
• revenge trades
• overtrading
• entries in messy candles after a spike
Pricing & Early Access (First 100 Users Only)
Special early access pricing applies only for the first 100 users.
After 100 users, pricing will increase.
Early Access Pricing (First 100 Users):
• Monthly: $99
• Quarterly: $249
• Annual: $899
Lifetime Plan (Limited):
• $7500 USD — only 3 seats total (once sold out, lifetime will be closed permanently)
________________________________________
How to Buy
✅ Purchase, Access & Support
📌 Payment & Access
MARAL is an invite-only premium indicator. Access is granted via direct approval.
MARAL is a premium Trading View indicator with manual access control.
To purchase MARAL, please email us first with your Trading View username.
Payment instructions will be shared by email based on your country.
📧 Email: ksharish0468@gmail.com
Access Delivery
Invite-only TradingView access will be granted within 12–24 hours after verification.
A full user manual will be provided along with activation . One Trading View username per purchase.
Support
For technical doubts/support: ksharish0468@gmail.com
Response time: within maximum 12 hours.
Updates
MARAL will be updated with new features over time.
You will receive email notifications if when updates are released.
________________________________________
Terms & Conditions
By purchasing, accessing, or using MARAL, you agree:
1) Nature of Product / No Financial Advice
• MARAL is a decision-support indicator for discretionary traders.
• It is not financial advice, not a recommendation, and not a guarantee of results.
2) No Guarantees / User Responsibility
• Trading involves risk and may result in losses.
• You are solely responsible for entries, exits, position sizing, and risk management.
• Examples shown in screenshots are illustrative and not a promise of performance.
3) License & Access
• Access is licensed to one TradingView account (single user).
• The license is non-transferable unless explicitly approved in writing.
• Access is provided via TradingView invite-only / protected script mechanism.
4) Strict Anti-Piracy / Prohibited Use
You may NOT:
• share access, resell access, or provide it to anyone else
• copy, replicate, reverse engineer, decompile, or attempt to recreate the indicator logic
• publish “clone” indicators derived from MARAL’s workflow
• distribute screenshots/videos intended to reveal proprietary logic or reproduce the system
• use group-sharing, “signal forwarding,” or shared accounts
Violation may result in:
✅ immediate access termination without refund
✅ permanent ban from future access
5) Service Availability / Platform Dependency
• Functionality depends on TradingView uptime, data feeds, Pine limitations, and symbol differences.
• Temporary issues can occur due to platform updates or broker feed variance.
6) Updates / Changes
• Features may be improved, refined, added, or adjusted over time.
• Visual layout may change while preserving core framework.
7) Refund Policy (Digital Access Standard)
• Because this is a digital product with immediate access, refunds are generally not available after access is granted.
• Refund requests due to trading losses, profitability, or user execution choices are not eligible.
• Exceptional cases (duplicate payment / access failure) must be reported within 48 hours for review.
8) Limitation of Liability
• The creator is not liable for trading losses, missed entries, data feed discrepancies, platform downtime, or indirect damages.
• Use is at your own risk.
________________________________________
Disclaimer
MARAL does not guarantee profits. Trade responsibly.
________________________________________
Ghost Scalp Protocol By [@Ash_TheTrader]
# 👻 GHOST SCALP PROTOCOL
### 💀 Stop Getting Trapped. Start Tracking the Banks.
Most retail traders lose because they enter exactly where institutions are exiting. They get caught in **"Stop Hunts"** and **"Fake-Outs."**
The **Ghost Scalp Protocol** is not just an indicator; it is a complete institutional trading system designed for **M1 & M5 Scalpers**. It combines **Smart Money Concepts (SMC)** with a **Physics-Based Momentum Engine ($p=mv$)** to detect high-probability reversals.
---
### ⚛️ THE LOGIC: 3-STAGE CONFIRMATION
This algorithm does not rely on lagging indicators. It uses a 3-step "Protocol" to validate every trade:
**1. THE GHOST TRAP (Liquidity Sweeps)**
* The script automatically draws "Ghost Lines" at key Swing Highs/Lows where retail Stop Losses are hiding.
* It waits for price to **sweep** these levels (Stop Hunt).
* **The Signal:** A Neon **Skull (☠️)** appears *only* if price aggressively rejects the level with high volume. This is the "Turtle Soup" pattern.
**2. THE PHYSICS ENGINE ($p = mv$)**
* Momentum is not just price speed; it is **Mass (Volume) x Velocity (Range)**.
* The dashboard calculates the "Force" of every candle.
* **The Signal:** An **Arrow (⬆/⬇)** appears when momentum surges **5x** above the average. This confirms the banks are pushing the move.
**3. BANK BIAS (Elasticity Filter)**
* Markets move like a rubber band.
* The script calculates a hidden "Fair Value" baseline.
* It creates a **Bias**: It only looks for Shorts in **PREMIUM (Shorting)** zones and Longs in **DISCOUNT (Accumulating)** zones.
---
### 📊 THE SMART DASHBOARD (HUD)
A futuristic, non-intrusive Heads-Up Display keeps you focused on the data that matters:
* **🏦 BANK BIAS:** Tells you if Institutions are likely **Accumulating** or **Shorting**.
* **📈 HTF TREND:** Automatically checks the **1-Hour Trend**. Don't fight the tide.
* **🚀 MOMENTUM:** Real-time Physics calculation.
* **Green Text:** Acceleration (Move is getting stronger).
* **Red Text:** Deceleration (Move is dying).
* **🌍 SESSION:** Shows active Bank Sessions (Tokyo, London, NY).
* **⚠️ OVERLAP ALERT:** Flashes GOLD when London & New York are open simultaneously (Peak Volatility).
---
### 🔥 STRATEGY: HOW TO TRADE
Use this checklist to execute high-probability scalps:
#### 📉 SHORT SETUP (SELL)
1. **Liquidity:** Wait for price to break above a **Red Ghost Line** (Sweep Highs).
2. **Signal:** Wait for the **Pink Skull ☠️** (Trap Detected).
3. **Confluence:**
* Dashboard Bias says: **"SHORTING"**
* HTF Trend says: **"BEARISH 📉"** (Optional but recommended).
4. **Entry:** On the Close of the Skull candle.
5. **Stop Loss:** Just above the wick swing high.
#### 📈 LONG SETUP (BUY)
1. **Liquidity:** Wait for price to break below a **Blue Ghost Line** (Sweep Lows).
2. **Signal:** Wait for the **Blue Skull ☠️** (Trap Detected).
3. **Confluence:**
* Dashboard Bias says: **"ACCUMULATING"**
* HTF Trend says: **"BULLISH 📈"** (Optional but recommended).
4. **Entry:** On the Close of the Skull candle.
5. **Stop Loss:** Just below the wick swing low.
---
### 🏆 RECOMMENDED PAIRS & TIMEFRAMES
* **⚡ Best Timeframes:**
* **1 Minute (M1):** For aggressive "Sniper" entries (High Frequency).
* **5 Minute (M5):** The "Gold Standard" for balanced Scalping.
* **15 Minute (M15):** Safer, higher win-rate Day Trading.
* **💎 Best Assets:**
* **Gold (XAUUSD):** Highly effective on liquidity sweeps.
* **Indices:** US100 (Nasdaq), US30 (Dow Jones).
* **Crypto:** BTCUSD, ETHUSD (High volatility).
* **Forex:** GBPUSD, EURUSD (London/NY Session).
---
### 🛠️ SETTINGS & CUSTOMIZATION
* **Surge Factor:** Default is **5.0x**. Lower this to 3.0 if you want more aggressive Momentum Arrows.
* **Smart Sessions:** Automatically converts to **New York Time** (EST) regardless of your location. No more time zone math.
* **Visuals:** Designed with "Ghost Glow" technology—97% transparent backgrounds that look classy and don't clutter your chart.
---
**"The Ghost Algo sees what you can't."**
*Trade Safe. Trade Smart.*
**~ Ash_TheTrader**
Gann Volume Swing (GVS)## **Gann Volume Swing (GVS) Indicator**
*Professional Hybrid Volume-Gann Reversal Detector*
### **Core Concept & Purpose**
The Gann Volume Swing (GVS) indicator is a sophisticated trading tool designed to identify high-probability reversal points by integrating three key market dimensions: **volume dynamics**, **geometric price levels**, and **momentum confirmation**. Developed for serious technical traders, GVS addresses the common challenge of distinguishing meaningful breakouts/reversals from temporary noise.
The indicator operates on the principle that **significant volume expansions** at **precise geometric support/resistance levels** (derived from Gann theory) often precede substantial price movements. By combining these elements with traditional momentum filters (RSI, MACD), GVS provides a multi-factor approach to market timing.
### **Theoretical Foundation**
The methodology synthesizes:
1. **Wyckoff's Volume-Price Relationship**: Volume precedes and confirms price action
2. **Gann's Geometric Trading**: Price moves in predictable angular patterns from swing points
3. **Modern Momentum Filters**: Additional confirmation from established oscillators
This creates a robust framework that respects both classical technical analysis and contemporary trading psychology.
---
## **TECHNICAL ARCHITECTURE**
### **1. Volume Engine Module**
```
Inputs:
• Volume MA Period (20): Smoothing window for volume baseline
• Volume Multiplier (2.0): Threshold for "abnormal" volume detection
Calculation Logic:
Current Volume > AND
Current Volume >
Output: Boolean flag signaling institutional-grade participation
```
### **2. Gann Geometry Module**
```
Pivot Detection:
• Swing Highs: PivotHigh(25,25) - Identifies significant peaks
• Swing Lows: PivotLow(25,25) - Identifies significant troughs
Line Generation:
• 1x1 Lines: Base angular lines from pivots (45-degree equivalents)
• 2x1 Lines: Secondary steeper/flatter lines (dynamic angles)
Key Parameter:
• Gann Sensitivity (0.5): Controls line steepness (0.1=flat, 1.0=steep)
```
### **3. Signal Generation Logic**
```
Long Signal =
+ + + +
Short Signal =
+ + + +
Anti-Whipsaw Protection:
• 5-bar cooldown between same-direction signals
• Proximity threshold: 0.5×ATR from Gann lines
```
### **4. Visualization System**
```
Primary Elements:
• Real-time Gann lines (4 colors, 2 styles)
• Signal markers (▲/▼ triangles)
• Bar coloring (lime/red highlights)
Display Control:
• Toggle Gann lines on/off
• Adjust transparency levels
• Custom alert configurations
```
---
## **QUICK REFERENCE CARD**
**GANN VOLUME SWING (GVS)**
*Volume-Powered Geometric Reversal Indicator*
### **🔧 PARAMETER SETTINGS**
**VOLUME GROUP**
`Volume MA Period`: 20 (14-30 range)
`Volume Multiplier`: 2.0 (1.5-2.5 optimal)
**GANN GROUP**
`Swing Period`: 50 bars (pivot sensitivity)
`Gann Sensitivity`: 0.3-0.5 (adjust for market type)
**FILTERS GROUP**
`RSI Period`: 14 (standard)
`Use Filters`: ON (recommended)
**DISPLAY GROUP**
`Show Gann Levels`: ON
`Cooldown Bars`: 5 (prevents signal flooding)
### **🎯 SIGNAL INTERPRETATION**
**LONG SETUP (Green ▲)**
- Volume spike (2× average) + Price at Gann support + Bullish candle
- Entry: Close of signal bar
- SL: 1.5×ATR below support line
- TP: Next Gann resistance or 2:1 R/R
**SHORT SETUP (Red ▼)**
- Volume spike + Price at Gann resistance + Bearish candle
- Entry: Close of signal bar
- SL: 1.5×ATR above resistance line
- TP: Next Gann support or 2:1 R/R
### **📊 VISUAL ELEMENTS KEY**
**LINES**
- `Solid Green`: 1x1 Support (primary)
- `Solid Red`: 1x1 Resistance (primary)
- `Blue Dots`: 2x1 Support (secondary)
- `Orange Dots`: 2x1 Resistance (secondary)
**MARKERS**
- `▲ Below Bar`: Long signal
- `▼ Above Bar`: Short signal
- `Bar Coloring`: Confirmation highlight
### **⚙️ OPTIMIZATION GUIDE**
**TRENDING MARKETS**
- Sensitivity: 0.2-0.3 (shallower angles)
- Volume Multiplier: 1.8-2.0
- Filters: Strict (RSI 65/35)
**RANGING MARKETS**
- Sensitivity: 0.6-0.8 (steeper angles)
- Volume Multiplier: 2.2-2.5
- Filters: Moderate (RSI 70/30)
**HIGH VOLATILITY**
- Increase ATR multiplier to 0.7-1.0
- Extend cooldown to 7-10 bars
- Require stronger volume confirmation
### **🚫 LIMITATIONS & NOTES**
**KNOWN CONSTRAINTS**
- Less effective in extremely choppy markets
- Requires adequate historical data (200+ bars)
- Volume reliability varies by asset class
- Gann lines repaint as new pivots form
**BEST PRACTICES**
- Combine with higher timeframe trend analysis
- Use on 1H+ charts for reliability
- Wait for close confirmation before acting
- Track win rate by market condition
**ALERT CONFIGURATION**
- Enable both Long/Short alerts
- Set to "Once Per Bar Close"
- Include ATR distance in alert message
- Log all signals for performance review
---
## **TRADING SYSTEM INTEGRATION**
### **Recommended Confluence Factors**
1. **Trend Alignment** (Higher timeframe direction)
2. **Market Structure** (Support/Resistance clusters)
3. **Economic Context** (News event proximity)
4. **Session Timing** (High-volume trading hours)
### **Risk Management Protocol**
- Maximum risk: 1% per trade
- Correlation limit: 2 simultaneous GVS signals
- Daily loss cap: 3% of portfolio
- Weekly review of signal accuracy
### **Performance Metrics to Track**
- Signal-to-Noise ratio (profitable signals/total)
- Average Reward/Risk achieved
- Best/worst market conditions
- Optimal parameter sets per asset
---
## **SUMMARY**
The **Gann Volume Swing** indicator represents a sophisticated approach to technical analysis, blending time-tested principles with modern computational techniques. By focusing on the confluence of **unusual volume**, **geometric price levels**, and **momentum confirmation**, it provides traders with a structured framework for identifying high-quality setups.
**Ideal User Profile**: Intermediate to advanced traders comfortable with multi-factor analysis, geometric concepts, and disciplined risk management.
**Disclaimer**: This tool generates probabilities, not certainties. Always combine with comprehensive market analysis and strict risk control measures.
---
**Version**: 5.0
**Category**: Volume + Geometric Analysis
**Complexity**: Advanced
**Best Timeframe**: 1H - Daily
**Recommended Assets**: Liquid stocks, major Forex pairs, indices
Liquidity Sentiment Profile | LUPENIndicator Guide: Liquidity Sentiment Profile (LSP).
What is the LSP?
The Liquidity Sentiment Profile (LSP) is a "Next-Generation" oscillator designed to look beyond simple price action. While standard indicators (like RSI or MACD) primarily focus on where a candle closes, the LSP analyzes the micro-structure of the entire candle—specifically the relationship between the candle's Body, its Wicks (Shadows), and the Volume.
The Core Philosophy:
Wicks tell the truth: A long lower wick indicates that sellers pushed the price down, but buyers aggressively absorbed that liquidity and pushed it back up.
That is hidden bullish strength.
Volume validates intent: A price move with low volume is noise. A price move (or wick rejection) with high volume is a commitment by institutional players.
The LSP calculates a "Sentiment Score" between -100 and +100 based on these factors.
How to Read the Visuals
The Colors (Intensity)
color: Light Green - Bullish Acceleration. Buyers are in control, and momentum is increasing. This is the ideal time to be in a Long trade.
color: Dark Green - Bullish Deceleration. Buyers are still in control (price is likely rising), but the momentum is fading. This is a warning sign to tighten stop-losses or take profits.
color: Light Red - Bearish Acceleration. Sellers are dominating, and panic is increasing. This is the ideal time to be Short.
color: Dark Red - Bearish Deceleration. Sellers are still in control, but the downward pressure is exhausted. Be careful with new short positions.
The Lines & Fills
The Main Line: The actual LSP sentiment value.
The Yellow Signal Line: A smoothed average of the sentiment.
The Core Fill: The colored area between the Main Line and the Signal Line. When this area "glows", the trend is strong. When it dims (Dark), the trend is weak. Bearish Deceleration. Sellers are still in control, but the downward pressure is exhausted. Be careful with new short positions.
The Lines & Fills
The Main Line: The actual LSP sentiment value.
The Yellow Signal Line: A smoothed average of the sentiment.
The Core Fill: The colored area between the Main Line and the Signal Line. When this area "glows" (Neon), the trend is strong. When it dims (Dark), the trend is weak.
How to Use It (Trading Strategies)
Strategy A: The "Power Cross" (Trend Entry)
Use this for entering trends when the market wakes up.
Long Entry: Wait for the LSP line to cross ABOVE the Yellow Signal Line.
Confirmation: The fill color must turn Neon Green.
Short Entry: Wait for the LSP line to cross BELOW the Yellow Signal Line.
Confirmation: The fill color must turn Neon Red.
Strategy B: The "Absorption" Play (Reversals)
This is where the LSP shines. It detects when liquidity is being absorbed before price turns.
Bullish Absorption: The Price makes a Lower Low, but the LSP makes a Higher Low. This happens because the LSP detects the Volume on the Lower Wicks (buyers absorbing selling pressure). This is a high-probability reversal signal.
Bearish Absorption: The Price makes a Higher High, but the LSP makes a Lower High. The volume on the Upper Wicks suggests sellers are absorbing the buy orders.
Strategy C: The "Dimming" Exit (Risk Management)
Don't wait for the price to crash to exit a trade.
If you are in a Long trade (Neon Green) and the color instantly shifts to Dark Green, it means the "fuel" is running out. Consider taking partial profits or moving your Stop Loss to break even.
Standard oscillators (like RSI) often give false signals during strong trends (showing "Overbought" while price keeps going up). The LSP avoids this because it weights Volume and Wicks. If price goes up and volume increases, the LSP stays Neon Green, telling you the move is genuine, not just overextended.
The Golden Reaper 🟡 THE GOLDEN REAPER
HTF OTE + EMA50 — Futures Scalping Framework
The Golden Reaper is a high-timeframe execution framework designed specifically for futures scalpers who trade with precision, patience, and structure.
This indicator focuses on HTF market structure, Optimal Trade Entry (OTE) zones, and equilibrium (50%) reclaim confirmation to identify high-probability execution areas for fast, controlled scalps.
It is not a signal spam tool.
It is a framework built for disciplined traders who wait for price to come to them.
⸻
🔑 Designed For
✔ Futures markets (ES, NQ, MNQ, MES, GC, MGC, CL, etc.)
✔ Scalpers & intraday traders
✔ 1H structure → 5m / 1m execution
✔ Traders who prefer few high-quality setups
⸻
🧠 Core Logic (How It Works)
1️⃣ High-Timeframe Structure (HTF)
The indicator identifies the most recent HTF swing high and low to define the active trading leg.
2️⃣ OTE Zone (Premium / Discount)
Price is expected to react within the OTE zone where liquidity is commonly targeted.
3️⃣ Golden Entry (EQ 50%)
The 50% equilibrium level is marked as the Golden Entry.
Price must reclaim this level for a setup to become valid.
4️⃣ Golden Execution Zone
After reclaim, a golden execution zone appears to define where entries are allowed.
5️⃣ EMA 50 Trend Filter
Trades are taken only in the direction of the HTF EMA 50 to avoid counter-trend scalps.
⸻
⚡ How Futures Scalpers Use It
Recommended Timeframes
• HTF Structure: 1 Hour
• Execution: 5 Minute / 1 Minute
Process
• Wait for price to reach the OTE zone
• Allow the setup to arm
• Enter only after price reclaims the Golden Entry
• Execute within the Golden Execution Zone
• Manage stops and targets manually
This approach helps scalpers:
✔ Avoid chasing price
✔ Reduce over-trading
✔ Improve entry precision
✔ Maintain consistency
⸻
🔔 Alerts Included
• OTE Touched – Setup is armed
• C-Reclaim Confirmed – Entry condition met
(Alerts are designed to assist — not replace — trader judgment.)
⸻
⚠️ Important Notes
• Designed for futures markets only
• Best used with price action confirmation
• No built-in stop loss or take profit (manual risk management required)
• Not financial advice
⸻
🧬 Who This Indicator Is For
✔ Futures scalpers
✔ ICT / Smart Money traders
✔ Structure-based traders
✔ Traders who value patience over frequency
❌ Not for:
• Signal chasers
• Indicator stacking
• Automated trading
• Beginners who want instant entries
⸻
🟡 Created By
ChartReaper / Tactiko
Instagram:
@officialchartreaper
@tactiko
Star V12⭐ Star Engine — Multi-Component, Multi-Timeframe Trade Execution System
The Star Engine is a stateful trade execution and analytics system designed to transform indicator confluence into structured, measurable trade runs. Rather than producing isolated buy/sell signals, the engine decomposes market behavior into pressure, confirmation, event grouping, and trade lifecycle management. Each component plays a specific role, and no single component is sufficient on its own. Below is a detailed breakdown of each subsystem and why it exists.
💣 Bomb Engine — Directional Pressure Measurement
The Bomb Engine is responsible for identifying directional pressure in the market. It evaluates whether price action exhibits sustained momentum in one direction, independent of whether that direction is immediately tradable.
What Bomb Uses
Bomb aggregates momentum- and trend-oriented inputs such as MACD-based momentum direction, momentum persistence and continuation logic, directional bias filters, and impulse strength evaluation. All inputs are evaluated across multiple timeframes, with each timeframe contributing independently.
How Bomb Works
Each timeframe produces a directional contribution (bullish, bearish, or neutral). Contributions are aggregated into a net Bomb total. The total is mapped into discrete tone buckets (blue, green, red, black, etc.). Higher totals indicate stronger directional dominance.
What Bomb Tells You
Bomb answers one question: Is there directional pressure building or persisting? It does not determine entry timing, exhaustion, or trade quality. Bomb is context, not execution. This allows Bomb to be early without being responsible for precision.
✨ Golden Engine — Structural Confirmation & Regime Filtering
The Golden Engine evaluates whether the directional pressure detected by Bomb is structurally supported. Golden exists to prevent entries during momentum exhaustion, conflicting timeframe regimes, and counter-structure moves.
What Golden Uses
Golden relies on a different indicator stack than Bomb, focused on confirmation and balance, including RSI regime classification (not simple overbought/oversold), momentum agreement vs divergence, trend-following vs counter-trend positioning, overextension detection, and compression and rotational behavior. Each timeframe is evaluated independently using the same logic.
The Role of RSI in Golden
RSI in Golden is used to identify regimes, not signals. It answers questions such as: Is momentum expanding or decaying? Is the move early, mid-structure, or extended? Do multiple timeframes share compatible RSI states? If RSI regimes conflict across timeframes, Golden will not confirm. This is one of the main mechanisms that makes Golden selective.
Momentum & Alignment Logic
Golden evaluates whether momentum supports continuation, is fragmenting, is diverging from price, or is contradicting higher-timeframe structure. If lower-timeframe impulses are not supported by higher-timeframe structure, Golden suppresses confirmation — even if Bomb remains strong.
What Golden Guarantees
Golden does not guarantee profitable trades. Golden guarantees that the detected directional pressure is not internally contradictory across RSI regimes, momentum behavior, and timeframe structure. This replaces vague terms like “clean” with explicit structural conditions.
🔗 Multi-Timeframe Aggregation (MTF)
Both Bomb and Golden operate on a multi-timeframe voting system. Lower timeframes capture early impulses, higher timeframes enforce structural context, each timeframe votes independently, conflicts weaken totals, and alignment strengthens totals. This creates temporal confluence, not just price-based confluence.
⭐ Star Events — Qualified Market Impulses
A Star (⭐) is created only when Bomb is active, Golden is active, both agree on direction, and all gating rules pass (thresholds, time filters, modes). A Star represents a qualified impulse, not a trade. Stars are atomic events used by the execution layer.
⏱ Star Clusters — Trade Run State
The Star Cluster groups Stars into runs. The first Star starts a cluster, anchor price, bar, and time are recorded, each additional Star increments the cluster count, and all Stars belong to the same run until exit. This prevents duplicate entries, signal spam, and overtrading in volatile conditions.
⛔ Reset Gap Logic — Temporal Control
To prevent rapid re-entry, a minimum time gap is required to start a new run. Stars occurring too close together are merged. Reset does not terminate active runs. This enforces time-based discipline, not indicator-based guessing.
1➡️ Entry Logic — Confirmation-Based Execution
The engine never enters on the first Star. Instead, the user defines 🔢 N (Entry Star Index). Entry occurs only on the Nth Star, and that bar is marked 1➡️🔢N. This ensures entries occur after persistence, not detection. At ENTRY, Best = 0.00 and Worst = 0.00. Statistics measure real trade performance, not early signal noise.
📊 STAT Engine — Live Trade Measurement
Once entry is active, the STAT engine tracks ⏱ run progression, 🏅 maximum favorable excursion, and 📉 maximum adverse excursion. Mechanics: uses highs and lows, not closes; updates every bar; entry bar resets stats; historical bars marked 🎨. This creates an objective performance envelope for every trade.
🛑 Exit Engine — Deterministic Outcomes
Trades are exited using explicit rules: 🏅 WIN → profit threshold reached, 📉 LOSE → risk threshold breached, ⏱ QUIT → structural or safety exit.
Safety Exits
🐢 Idle Stop — no Stars for N bars.
🧯 Freeze Failsafe — STAT inactivity.
QUIT is a controlled termination, not failure. Each exit is recorded with a short cause tag.
🧾 Trade Memory & Journaling
Every trade produces immutable records. Entry: time, price, side, confirmation index. Exit: time, price, PnL, result, cause. These records power tables, alerts, JSON output, and external automation.
📊 Time-Block Performance (NY Clock)
Performance is grouped by real time, not bar count. Rolling NY blocks (e.g. 3 hours). Independent statistics per block. Live trades persist across block boundaries. This enables session-based analysis.
🔔 Alerts & Automation
Alerts are state-based: Entry confirmed → Long / Short alert. Trade closed → Exit alert. Optional JSON output allows integration with bots, journals, and dashboards.
Summary
The Star Engine is a component-based trade execution system, where Bomb measures pressure, Golden validates structure, Stars qualify impulses, clusters define runs, entry is delayed by confirmation, stats measure reality, exits are deterministic, and results are time-aware. It is not designed to “predict the market”, but to control how trades are formed, managed, and evaluated.
Momentum by Trading BiZonesSqueeze Momentum Indicator with EMA
Overview
The Squeeze Momentum Indicator with EMA is a powerful technical analysis tool that combines the original Squeeze Momentum concept with an Exponential Moving Average (EMA) overlay. This enhanced version helps traders identify market momentum, volatility contractions (squeezes), and potential trend reversals with greater precision.
Core Concept
The indicator operates on the principle of volatility contraction and expansion:
Squeeze Phase: When Bollinger Bands move inside the Keltner Channel, indicating low volatility and potential energy buildup
Expansion Phase: When momentum breaks out of the squeeze, signaling potential directional moves
Key Components
1. Squeeze Momentum Calculation
Formula: Momentum = Linear Regression(Close - Average Price)
Where Average Price = (Highest High + Lowest Low + SMA(Close)) / 3
Visualization: Histogram bars showing positive (green) and negative (red) momentum
Zero Line: Represents equilibrium point between buyers and sellers
2. EMA Overlay
Purpose: Smooths momentum values to identify underlying trends
Customization:
Adjustable period (default: 20)
Toggle on/off display
Customizable color and line thickness
Cross Signals: Buy/sell signals when momentum crosses above/below EMA
3. Volatility Bands
Bollinger Bands (20-period, 2 standard deviations)
Keltner Channels (20-period, 1.5 ATR multiplier)
Squeeze Detection: Visual background shading when BB are inside KC
Trading Signals
Buy Signals (Green Upward Triangle)
Momentum histogram crosses ABOVE EMA line
Occurs during or after squeeze release
Confirmed by expanding histogram bars
Sell Signals (Red Downward Triangle)
Momentum histogram crosses BELOW EMA line
Often precedes market downturns
Watch for increasing negative momentum
Squeeze Warnings (Gray Background)
Market in low volatility state
Prepare for potential breakout
Direction indicated by momentum bias
Indicator Settings
Main Parameters
Length: Period for calculations (default: 20)
Show EMA: Toggle EMA visibility
EMA Period: Smoothing period for EMA
Visual Settings
Histogram color-coding based on momentum direction
EMA line color and thickness
Signal marker size and visibility
Squeeze zone background display
Practical Applications
Trend Identification
Uptrend: Consistently positive momentum with EMA support
Downtrend: Consistently negative momentum with EMA resistance
Range-bound: Oscillating around zero line
Entry/Exit Points
Conservative Entry: Wait for squeeze release + EMA crossover
Aggressive Entry: Anticipate breakout during squeeze
Exit: Opposite crossover or momentum divergence
Risk Management
Use squeeze zones as warning periods
EMA crossovers as confirmation signals
Combine with support/resistance levels
Advanced Interpretation
Momentum Strength
Strong Bullish: Tall green bars above EMA
Weak Bullish: Short green bars near EMA
Strong Bearish: Tall red bars below EMA
Weak Bearish: Short red bars near EMA
Divergence Detection
Price makes higher high, momentum makes lower high → Bearish divergence
Price makes lower low, momentum makes higher low → Bullish divergence
Squeeze Characteristics
Long squeezes: More potential energy
Frequent squeezes: Choppy market conditions
No squeezes: High volatility, trending markets
Recommended Timeframes
Scalping: 1-15 minute charts
Day Trading: 15-minute to 4-hour charts
Swing Trading: 4-hour to daily charts
Position Trading: Daily to weekly charts
Best Practices
Confirmation
Use with volume indicators
Check higher timeframe direction
Wait for candle close confirmation
Filtering Signals
Ignore signals during extreme volatility
Require minimum bar size for crossovers
Consider market context (news, sessions)
Combination Suggestions
With RSI: Confirm overbought/oversold conditions
With Volume Profile: Identify high-volume nodes
With Support/Resistance: Key level reactions
With Trend Lines: Breakout confirmations
Limitations
Lagging indicator (based on past data)
Works best in trending markets
May give false signals in ranging markets
Requires proper risk management
Conclusion
The Squeeze Momentum Indicator with EMA provides a comprehensive view of market dynamics by combining volatility analysis, momentum measurement, and trend smoothing. Its visual clarity and customizable parameters make it suitable for traders of all experience levels seeking to identify high-probability trading opportunities during volatility contractions and expansions.
Adaptive Genesis Engine [AGE]ADAPTIVE GENESIS ENGINE (AGE)
Pure Signal Evolution Through Genetic Algorithms
Where Darwin Meets Technical Analysis
🧬 WHAT YOU'RE GETTING - THE PURE INDICATOR
This is a technical analysis indicator - it generates signals, visualizes probability, and shows you the evolutionary process in real-time. This is NOT a strategy with automatic execution - it's a sophisticated signal generation system that you control .
What This Indicator Does:
Generates Long/Short entry signals with probability scores (35-88% range)
Evolves a population of up to 12 competing strategies using genetic algorithms
Validates strategies through walk-forward optimization (train/test cycles)
Visualizes signal quality through premium gradient clouds and confidence halos
Displays comprehensive metrics via enhanced dashboard
Provides alerts for entries and exits
Works on any timeframe, any instrument, any broker
What This Indicator Does NOT Do:
Execute trades automatically
Manage positions or calculate position sizes
Place orders on your behalf
Make trading decisions for you
This is pure signal intelligence. AGE tells you when and how confident it is. You decide whether and how much to trade.
🔬 THE SCIENCE: GENETIC ALGORITHMS MEET TECHNICAL ANALYSIS
What Makes This Different - The Evolutionary Foundation
Most indicators are static - they use the same parameters forever, regardless of market conditions. AGE is alive . It maintains a population of competing strategies that evolve, adapt, and improve through natural selection principles:
Birth: New strategies spawn through crossover breeding (combining DNA from fit parents) plus random mutation for exploration
Life: Each strategy trades virtually via shadow portfolios, accumulating wins/losses, tracking drawdown, and building performance history
Selection: Strategies are ranked by comprehensive fitness scoring (win rate, expectancy, drawdown control, signal efficiency)
Death: Weak strategies are culled periodically, with elite performers (top 2 by default) protected from removal
Evolution: The gene pool continuously improves as successful traits propagate and unsuccessful ones die out
This is not curve-fitting. Each new strategy must prove itself on out-of-sample data through walk-forward validation before being trusted for live signals.
🧪 THE DNA: WHAT EVOLVES
Every strategy carries a 10-gene chromosome controlling how it interprets market data:
Signal Sensitivity Genes
Entropy Sensitivity (0.5-2.0): Weight given to market order/disorder calculations. Low values = conservative, require strong directional clarity. High values = aggressive, act on weaker order signals.
Momentum Sensitivity (0.5-2.0): Weight given to RSI/ROC/MACD composite. Controls responsiveness to momentum shifts vs. mean-reversion setups.
Structure Sensitivity (0.5-2.0): Weight given to support/resistance positioning. Determines how much price location within swing range matters.
Probability Adjustment Genes
Probability Boost (-0.10 to +0.10): Inherent bias toward aggressive (+) or conservative (-) entries. Acts as personality trait - some strategies naturally optimistic, others pessimistic.
Trend Strength Requirement (0.3-0.8): Minimum trend conviction needed before signaling. Higher values = only trades strong trends, lower values = acts in weak/sideways markets.
Volume Filter (0.5-1.5): Strictness of volume confirmation. Higher values = requires strong volume, lower values = volume less important.
Risk Management Genes
ATR Multiplier (1.5-4.0): Base volatility scaling for all price levels. Controls whether strategy uses tight or wide stops/targets relative to ATR.
Stop Multiplier (1.0-2.5): Stop loss tightness. Lower values = aggressive profit protection, higher values = more breathing room.
Target Multiplier (1.5-4.0): Profit target ambition. Lower values = quick scalping exits, higher values = swing trading holds.
Adaptation Gene
Regime Adaptation (0.0-1.0): How much strategy adjusts behavior based on detected market regime (trending/volatile/choppy). Higher values = more reactive to regime changes.
The Magic: AGE doesn't just try random combinations. Through tournament selection and fitness-weighted crossover, successful gene combinations spread through the population while unsuccessful ones fade away. Over 50-100 bars, you'll see the population converge toward genes that work for YOUR instrument and timeframe.
📊 THE SIGNAL ENGINE: THREE-LAYER SYNTHESIS
Before any strategy generates a signal, AGE calculates probability through multi-indicator confluence:
Layer 1 - Market Entropy (Information Theory)
Measures whether price movements exhibit directional order or random walk characteristics:
The Math:
Shannon Entropy = -Σ(p × log(p))
Market Order = 1 - (Entropy / 0.693)
What It Means:
High entropy = choppy, random market → low confidence signals
Low entropy = directional market → high confidence signals
Direction determined by up-move vs down-move dominance over lookback period (default: 20 bars)
Signal Output: -1.0 to +1.0 (bearish order to bullish order)
Layer 2 - Momentum Synthesis
Combines three momentum indicators into single composite score:
Components:
RSI (40% weight): Normalized to -1/+1 scale using (RSI-50)/50
Rate of Change (30% weight): Percentage change over lookback (default: 14 bars), clamped to ±1
MACD Histogram (30% weight): Fast(12) - Slow(26), normalized by ATR
Why This Matters: RSI catches mean-reversion opportunities, ROC catches raw momentum, MACD catches momentum divergence. Weighting favors RSI for reliability while keeping other perspectives.
Signal Output: -1.0 to +1.0 (strong bearish to strong bullish)
Layer 3 - Structure Analysis
Evaluates price position within swing range (default: 50-bar lookback):
Position Classification:
Bottom 20% of range = Support Zone → bullish bounce potential
Top 20% of range = Resistance Zone → bearish rejection potential
Middle 60% = Neutral Zone → breakout/breakdown monitoring
Signal Logic:
At support + bullish candle = +0.7 (strong buy setup)
At resistance + bearish candle = -0.7 (strong sell setup)
Breaking above range highs = +0.5 (breakout confirmation)
Breaking below range lows = -0.5 (breakdown confirmation)
Consolidation within range = ±0.3 (weak directional bias)
Signal Output: -1.0 to +1.0 (bearish structure to bullish structure)
Confluence Voting System
Each layer casts a vote (Long/Short/Neutral). The system requires minimum 2-of-3 agreement (configurable 1-3) before generating a signal:
Examples:
Entropy: Bullish, Momentum: Bullish, Structure: Neutral → Signal generated (2 long votes)
Entropy: Bearish, Momentum: Neutral, Structure: Neutral → No signal (only 1 short vote)
All three bullish → Signal generated with +5% probability bonus
This is the key to quality. Single indicators give too many false signals. Triple confirmation dramatically improves accuracy.
📈 PROBABILITY CALCULATION: HOW CONFIDENCE IS MEASURED
Base Probability:
Raw_Prob = 50% + (Average_Signal_Strength × 25%)
Then AGE applies strategic adjustments:
Trend Alignment:
Signal with trend: +4%
Signal against strong trend: -8%
Weak/no trend: no adjustment
Regime Adaptation:
Trending market (efficiency >50%, moderate vol): +3%
Volatile market (vol ratio >1.5x): -5%
Choppy market (low efficiency): -2%
Volume Confirmation:
Volume > 70% of 20-bar SMA: no change
Volume below threshold: -3%
Volatility State (DVS Ratio):
High vol (>1.8x baseline): -4% (reduce confidence in chaos)
Low vol (<0.7x baseline): -2% (markets can whipsaw in compression)
Moderate elevated vol (1.0-1.3x): +2% (trending conditions emerging)
Confluence Bonus:
All 3 indicators agree: +5%
2 of 3 agree: +2%
Strategy Gene Adjustment:
Probability Boost gene: -10% to +10%
Regime Adaptation gene: scales regime adjustments by 0-100%
Final Probability: Clamped between 35% (minimum) and 88% (maximum)
Why These Ranges?
Below 35% = too uncertain, better not to signal
Above 88% = unrealistic, creates overconfidence
Sweet spot: 65-80% for quality entries
🔄 THE SHADOW PORTFOLIO SYSTEM: HOW STRATEGIES COMPETE
Each active strategy maintains a virtual trading account that executes in parallel with real-time data:
Shadow Trading Mechanics
Entry Logic:
Calculate signal direction, probability, and confluence using strategy's unique DNA
Check if signal meets quality gate:
Probability ≥ configured minimum threshold (default: 65%)
Confluence ≥ configured minimum (default: 2 of 3)
Direction is not zero (must be long or short, not neutral)
Verify signal persistence:
Base requirement: 2 bars (configurable 1-5)
Adapts based on probability: high-prob signals (75%+) enter 1 bar faster, low-prob signals need 1 bar more
Adjusts for regime: trending markets reduce persistence by 1, volatile markets add 1
Apply additional filters:
Trend strength must exceed strategy's requirement gene
Regime filter: if volatile market detected, probability must be 72%+ to override
Volume confirmation required (volume > 70% of average)
If all conditions met for required persistence bars, enter shadow position at current close price
Position Management:
Entry Price: Recorded at close of entry bar
Stop Loss: ATR-based distance = ATR × ATR_Mult (gene) × Stop_Mult (gene) × DVS_Ratio
Take Profit: ATR-based distance = ATR × ATR_Mult (gene) × Target_Mult (gene) × DVS_Ratio
Position: +1 (long) or -1 (short), only one at a time per strategy
Exit Logic:
Check if price hit stop (on low) or target (on high) on current bar
Record trade outcome in R-multiples (profit/loss normalized by ATR)
Update performance metrics:
Total trades counter incremented
Wins counter (if profit > 0)
Cumulative P&L updated
Peak equity tracked (for drawdown calculation)
Maximum drawdown from peak recorded
Enter cooldown period (default: 8 bars, configurable 3-20) before next entry allowed
Reset signal age counter to zero
Walk-Forward Tracking:
During position lifecycle, trades are categorized:
Training Phase (first 250 bars): Trade counted toward training metrics
Testing Phase (next 75 bars): Trade counted toward testing metrics (out-of-sample)
Live Phase (after WFO period): Trade counted toward overall metrics
Why Shadow Portfolios?
No lookahead bias (uses only data available at the bar)
Realistic execution simulation (entry on close, stop/target checks on high/low)
Independent performance tracking for true fitness comparison
Allows safe experimentation without risking capital
Each strategy learns from its own experience
🏆 FITNESS SCORING: HOW STRATEGIES ARE RANKED
Fitness is not just win rate. AGE uses a comprehensive multi-factor scoring system:
Core Metrics (Minimum 3 trades required)
Win Rate (30% of fitness):
WinRate = Wins / TotalTrades
Normalized directly (0.0-1.0 scale)
Total P&L (30% of fitness):
Normalized_PnL = (PnL + 300) / 600
Clamped 0.0-1.0. Assumes P&L range of -300R to +300R for normalization scale.
Expectancy (25% of fitness):
Expectancy = Total_PnL / Total_Trades
Normalized_Expectancy = (Expectancy + 30) / 60
Clamped 0.0-1.0. Rewards consistency of profit per trade.
Drawdown Control (15% of fitness):
Normalized_DD = 1 - (Max_Drawdown / 15)
Clamped 0.0-1.0. Penalizes strategies that suffer large equity retracements from peak.
Sample Size Adjustment
Quality Factor:
<50 trades: 1.0 (full weight, small sample)
50-100 trades: 0.95 (slight penalty for medium sample)
100 trades: 0.85 (larger penalty for large sample)
Why penalize more trades? Prevents strategies from gaming the system by taking hundreds of tiny trades to inflate statistics. Favors quality over quantity.
Bonus Adjustments
Walk-Forward Validation Bonus:
if (WFO_Validated):
Fitness += (WFO_Efficiency - 0.5) × 0.1
Strategies proven on out-of-sample data receive up to +10% fitness boost based on test/train efficiency ratio.
Signal Efficiency Bonus (if diagnostics enabled):
if (Signals_Evaluated > 10):
Pass_Rate = Signals_Passed / Signals_Evaluated
Fitness += (Pass_Rate - 0.1) × 0.05
Rewards strategies that generate high-quality signals passing the quality gate, not just profitable trades.
Final Fitness: Clamped at 0.0 minimum (prevents negative fitness values)
Result: Elite strategies typically achieve 0.50-0.75 fitness. Anything above 0.60 is excellent. Below 0.30 is prime candidate for culling.
🔬 WALK-FORWARD OPTIMIZATION: ANTI-OVERFITTING PROTECTION
This is what separates AGE from curve-fitted garbage indicators.
The Three-Phase Process
Every new strategy undergoes a rigorous validation lifecycle:
Phase 1 - Training Window (First 250 bars, configurable 100-500):
Strategy trades normally via shadow portfolio
All trades count toward training performance metrics
System learns which gene combinations produce profitable patterns
Tracks independently: Training_Trades, Training_Wins, Training_PnL
Phase 2 - Testing Window (Next 75 bars, configurable 30-200):
Strategy continues trading without any parameter changes
Trades now count toward testing performance metrics (separate tracking)
This is out-of-sample data - strategy has never seen these bars during "optimization"
Tracks independently: Testing_Trades, Testing_Wins, Testing_PnL
Phase 3 - Validation Check:
Minimum_Trades = 5 (configurable 3-15)
IF (Train_Trades >= Minimum AND Test_Trades >= Minimum):
WR_Efficiency = Test_WinRate / Train_WinRate
Expectancy_Efficiency = Test_Expectancy / Train_Expectancy
WFO_Efficiency = (WR_Efficiency + Expectancy_Efficiency) / 2
IF (WFO_Efficiency >= 0.55): // configurable 0.3-0.9
Strategy.Validated = TRUE
Strategy receives fitness bonus
ELSE:
Strategy receives 30% fitness penalty
ELSE:
Validation deferred (insufficient trades in one or both periods)
What Validation Means
Validated Strategy (Green "✓ VAL" in dashboard):
Performed at least 55% as well on unseen data compared to training data
Gets fitness bonus: +(efficiency - 0.5) × 0.1
Receives priority during tournament selection for breeding
More likely to be chosen as active trading strategy
Unvalidated Strategy (Orange "○ TRAIN" in dashboard):
Failed to maintain performance on test data (likely curve-fitted to training period)
Receives 30% fitness penalty (0.7x multiplier)
Makes strategy prime candidate for culling
Can still trade but with lower selection probability
Insufficient Data (continues collecting):
Hasn't completed both training and testing periods yet
OR hasn't achieved minimum trade count in both periods
Validation check deferred until requirements met
Why 55% Efficiency Threshold?
If a strategy earned 10R during training but only 5.5R during testing, it still proved an edge exists beyond random luck. Requiring 100% efficiency would be unrealistic - market conditions change between periods. But requiring >50% ensures the strategy didn't completely degrade on fresh data.
The Protection: Strategies that work great on historical data but fail on new data are automatically identified and penalized. This prevents the population from being polluted by overfitted strategies that would fail in live trading.
🌊 DYNAMIC VOLATILITY SCALING (DVS): ADAPTIVE STOP/TARGET PLACEMENT
AGE doesn't use fixed stop distances. It adapts to current volatility conditions in real-time.
Four Volatility Measurement Methods
1. ATR Ratio (Simple Method):
Current_Vol = ATR(14) / Close
Baseline_Vol = SMA(Current_Vol, 100)
Ratio = Current_Vol / Baseline_Vol
Basic comparison of current ATR to 100-bar moving average baseline.
2. Parkinson (High-Low Range Based):
For each bar: HL = log(High / Low)
Parkinson_Vol = sqrt(Σ(HL²) / (4 × Period × log(2)))
More stable than close-to-close volatility. Captures intraday range expansion without overnight gap noise.
3. Garman-Klass (OHLC Based):
HL_Term = 0.5 × ²
CO_Term = (2×log(2) - 1) × ²
GK_Vol = sqrt(Σ(HL_Term - CO_Term) / Period)
Most sophisticated estimator. Incorporates all four price points (open, high, low, close) plus gap information.
4. Ensemble Method (Default - Median of All Three):
Ratio_1 = ATR_Current / ATR_Baseline
Ratio_2 = Parkinson_Current / Parkinson_Baseline
Ratio_3 = GK_Current / GK_Baseline
DVS_Ratio = Median(Ratio_1, Ratio_2, Ratio_3)
Why Ensemble?
Takes median to avoid outliers and false spikes
If ATR jumps but range-based methods stay calm, median prevents overreaction
If one method fails, other two compensate
Most robust approach across different market conditions
Sensitivity Scaling
Scaled_Ratio = (Raw_Ratio) ^ Sensitivity
Sensitivity 0.3: Cube root - heavily dampens volatility impact
Sensitivity 0.5: Square root - moderate dampening
Sensitivity 0.7 (Default): Balanced response to volatility changes
Sensitivity 1.0: Linear - full 1:1 volatility impact
Sensitivity 1.5: Exponential - amplified response to volatility spikes
Safety Clamps: Final DVS Ratio always clamped between 0.5x and 2.5x baseline to prevent extreme position sizing or stop placement errors.
How DVS Affects Shadow Trading
Every strategy's stop and target distances are multiplied by the current DVS ratio:
Stop Loss Distance:
Stop_Distance = ATR × ATR_Mult (gene) × Stop_Mult (gene) × DVS_Ratio
Take Profit Distance:
Target_Distance = ATR × ATR_Mult (gene) × Target_Mult (gene) × DVS_Ratio
Example Scenario:
ATR = 10 points
Strategy's ATR_Mult gene = 2.5
Strategy's Stop_Mult gene = 1.5
Strategy's Target_Mult gene = 2.5
DVS_Ratio = 1.4 (40% above baseline volatility - market heating up)
Stop = 10 × 2.5 × 1.5 × 1.4 = 52.5 points (vs. 37.5 in normal vol)
Target = 10 × 2.5 × 2.5 × 1.4 = 87.5 points (vs. 62.5 in normal vol)
Result:
During volatility spikes: Stops automatically widen to avoid noise-based exits, targets extend for bigger moves
During calm periods: Stops tighten for better risk/reward, targets compress for realistic profit-taking
Strategies adapt risk management to match current market behavior
🧬 THE EVOLUTIONARY CYCLE: SPAWN, COMPETE, CULL
Initialization (Bar 1)
AGE begins with 4 seed strategies (if evolution enabled):
Seed Strategy #0 (Balanced):
All sensitivities at 1.0 (neutral)
Zero probability boost
Moderate trend requirement (0.4)
Standard ATR/stop/target multiples (2.5/1.5/2.5)
Mid-level regime adaptation (0.5)
Seed Strategy #1 (Momentum-Focused):
Lower entropy sensitivity (0.7), higher momentum (1.5)
Slight probability boost (+0.03)
Higher trend requirement (0.5)
Tighter stops (1.3), wider targets (3.0)
Seed Strategy #2 (Entropy-Driven):
Higher entropy sensitivity (1.5), lower momentum (0.8)
Slight probability penalty (-0.02)
More trend tolerant (0.6)
Wider stops (1.8), standard targets (2.5)
Seed Strategy #3 (Structure-Based):
Balanced entropy/momentum (0.8/0.9), high structure (1.4)
Slight probability boost (+0.02)
Lower trend requirement (0.35)
Moderate risk parameters (1.6/2.8)
All seeds start with WFO validation bypassed if WFO is disabled, or must validate if enabled.
Spawning New Strategies
Timing (Adaptive):
Historical phase: Every 30 bars (configurable 10-100)
Live phase: Every 200 bars (configurable 100-500)
Automatically switches to live timing when barstate.isrealtime triggers
Conditions:
Current population < max population limit (default: 8, configurable 4-12)
At least 2 active strategies exist (need parents)
Available slot in population array
Selection Process:
Run tournament selection 3 times with different seeds
Each tournament: randomly sample active strategies, pick highest fitness
Best from 3 tournaments becomes Parent 1
Repeat independently for Parent 2
Ensures fit parents but maintains diversity
Crossover Breeding:
For each of 10 genes:
Parent1_Fitness = fitness
Parent2_Fitness = fitness
Weight1 = Parent1_Fitness / (Parent1_Fitness + Parent2_Fitness)
Gene1 = parent1's value
Gene2 = parent2's value
Child_Gene = Weight1 × Gene1 + (1 - Weight1) × Gene2
Fitness-weighted crossover ensures fitter parent contributes more genetic material.
Mutation:
For each gene in child:
IF (random < mutation_rate):
Gene_Range = GENE_MAX - GENE_MIN
Noise = (random - 0.5) × 2 × mutation_strength × Gene_Range
Mutated_Gene = Clamp(Child_Gene + Noise, GENE_MIN, GENE_MAX)
Historical mutation rate: 20% (aggressive exploration)
Live mutation rate: 8% (conservative stability)
Mutation strength: 12% of gene range (configurable 5-25%)
Initialization of New Strategy:
Unique ID assigned (total_spawned counter)
Parent ID recorded
Generation = max(parent generations) + 1
Birth bar recorded (for age tracking)
All performance metrics zeroed
Shadow portfolio reset
WFO validation flag set to false (must prove itself)
Result: New strategy with hybrid DNA enters population, begins trading in next bar.
Competition (Every Bar)
All active strategies:
Calculate their signal based on unique DNA
Check quality gate with their thresholds
Manage shadow positions (entries/exits)
Update performance metrics
Recalculate fitness score
Track WFO validation progress
Strategies compete indirectly through fitness ranking - no direct interaction.
Culling Weak Strategies
Timing (Adaptive):
Historical phase: Every 60 bars (configurable 20-200, should be 2x spawn interval)
Live phase: Every 400 bars (configurable 200-1000, should be 2x spawn interval)
Minimum Adaptation Score (MAS):
Initial MAS = 0.10
MAS decays: MAS × 0.995 every cull cycle
Minimum MAS = 0.03 (floor)
MAS represents the "survival threshold" - strategies below this fitness level are vulnerable.
Culling Conditions (ALL must be true):
Population > minimum population (default: 3, configurable 2-4)
At least one strategy has fitness < MAS
Strategy's age > culling interval (prevents premature culling of new strategies)
Strategy is not in top N elite (default: 2, configurable 1-3)
Culling Process:
Find worst strategy:
For each active strategy:
IF (age > cull_interval):
Fitness = base_fitness
IF (not WFO_validated AND WFO_enabled):
Fitness × 0.7 // 30% penalty for unvalidated
IF (Fitness < MAS AND Fitness < worst_fitness_found):
worst_strategy = this_strategy
worst_fitness = Fitness
IF (worst_strategy found):
Count elite strategies with fitness > worst_fitness
IF (elite_count >= elite_preservation_count):
Deactivate worst_strategy (set active flag = false)
Increment total_culled counter
Elite Protection:
Even if a strategy's fitness falls below MAS, it survives if fewer than N strategies are better. This prevents culling when population is generally weak.
Result: Weak strategies removed from population, freeing slots for new spawns. Gene pool improves over time.
Selection for Display (Every Bar)
AGE chooses one strategy to display signals:
Best fitness = -1
Selected = none
For each active strategy:
Fitness = base_fitness
IF (WFO_validated):
Fitness × 1.3 // 30% bonus for validated strategies
IF (Fitness > best_fitness):
best_fitness = Fitness
selected_strategy = this_strategy
Display selected strategy's signals on chart
Result: Only the highest-fitness (optionally validated-boosted) strategy's signals appear as chart markers. Other strategies trade invisibly in shadow portfolios.
🎨 PREMIUM VISUALIZATION SYSTEM
AGE includes sophisticated visual feedback that standard indicators lack:
1. Gradient Probability Cloud (Optional, Default: ON)
Multi-layer gradient showing signal buildup 2-3 bars before entry:
Activation Conditions:
Signal persistence > 0 (same directional signal held for multiple bars)
Signal probability ≥ minimum threshold (65% by default)
Signal hasn't yet executed (still in "forming" state)
Visual Construction:
7 gradient layers by default (configurable 3-15)
Each layer is a line-fill pair (top line, bottom line, filled between)
Layer spacing: 0.3 to 1.0 × ATR above/below price
Outer layers = faint, inner layers = bright
Color transitions from base to intense based on layer position
Transparency scales with probability (high prob = more opaque)
Color Selection:
Long signals: Gradient from theme.gradient_bull_mid to theme.gradient_bull_strong
Short signals: Gradient from theme.gradient_bear_mid to theme.gradient_bear_strong
Base transparency: 92%, reduces by up to 8% for high-probability setups
Dynamic Behavior:
Cloud grows/shrinks as signal persistence increases/decreases
Redraws every bar while signal is forming
Disappears when signal executes or invalidates
Performance Note: Computationally expensive due to linefill objects. Disable or reduce layers if chart performance degrades.
2. Population Fitness Ribbon (Optional, Default: ON)
Histogram showing fitness distribution across active strategies:
Activation: Only draws on last bar (barstate.islast) to avoid historical clutter
Visual Construction:
10 histogram layers by default (configurable 5-20)
Plots 50 bars back from current bar
Positioned below price at: lowest_low(100) - 1.5×ATR (doesn't interfere with price action)
Each layer represents a fitness threshold (evenly spaced min to max fitness)
Layer Logic:
For layer_num from 0 to ribbon_layers:
Fitness_threshold = min_fitness + (max_fitness - min_fitness) × (layer / layers)
Count strategies with fitness ≥ threshold
Height = ATR × 0.15 × (count / total_active)
Y_position = base_level + ATR × 0.2 × layer
Color = Gradient from weak to strong based on layer position
Line_width = Scaled by height (taller = thicker)
Visual Feedback:
Tall, bright ribbon = healthy population, many fit strategies at high fitness levels
Short, dim ribbon = weak population, few strategies achieving good fitness
Ribbon compression (layers close together) = population converging to similar fitness
Ribbon spread = diverse fitness range, active selection pressure
Use Case: Quick visual health check without opening dashboard. Ribbon growing upward over time = population improving.
3. Confidence Halo (Optional, Default: ON)
Circular polyline around entry signals showing probability strength:
Activation: Draws when new position opens (shadow_position changes from 0 to ±1)
Visual Construction:
20-segment polyline forming approximate circle
Center: Low - 0.5×ATR (long) or High + 0.5×ATR (short)
Radius: 0.3×ATR (low confidence) to 1.0×ATR (elite confidence)
Scales with: (probability - min_probability) / (1.0 - min_probability)
Color Coding:
Elite (85%+): Cyan (theme.conf_elite), large radius, minimal transparency (40%)
Strong (75-85%): Strong green (theme.conf_strong), medium radius, moderate transparency (50%)
Good (65-75%): Good green (theme.conf_good), smaller radius, more transparent (60%)
Moderate (<65%): Moderate green (theme.conf_moderate), tiny radius, very transparent (70%)
Technical Detail:
Uses chart.point array with index-based positioning
5-bar horizontal spread for circular appearance (±5 bars from entry)
Curved=false (Pine Script polyline limitation)
Fill color matches line color but more transparent (88% vs line's transparency)
Purpose: Instant visual probability assessment. No need to check dashboard - halo size/brightness tells the story.
4. Evolution Event Markers (Optional, Default: ON)
Visual indicators of genetic algorithm activity:
Spawn Markers (Diamond, Cyan):
Plots when total_spawned increases on current bar
Location: bottom of chart (location.bottom)
Color: theme.spawn_marker (cyan/bright blue)
Size: tiny
Indicates new strategy just entered population
Cull Markers (X-Cross, Red):
Plots when total_culled increases on current bar
Location: bottom of chart (location.bottom)
Color: theme.cull_marker (red/pink)
Size: tiny
Indicates weak strategy just removed from population
What It Tells You:
Frequent spawning early = population building, active exploration
Frequent culling early = high selection pressure, weak strategies dying fast
Balanced spawn/cull = healthy evolutionary churn
No markers for long periods = stable population (evolution plateaued or optimal genes found)
5. Entry/Exit Markers
Clear visual signals for selected strategy's trades:
Long Entry (Triangle Up, Green):
Plots when selected strategy opens long position (position changes 0 → +1)
Location: below bar (location.belowbar)
Color: theme.long_primary (green/cyan depending on theme)
Transparency: Scales with probability:
Elite (85%+): 0% (fully opaque)
Strong (75-85%): 10%
Good (65-75%): 20%
Acceptable (55-65%): 35%
Size: small
Short Entry (Triangle Down, Red):
Plots when selected strategy opens short position (position changes 0 → -1)
Location: above bar (location.abovebar)
Color: theme.short_primary (red/pink depending on theme)
Transparency: Same scaling as long entries
Size: small
Exit (X-Cross, Orange):
Plots when selected strategy closes position (position changes ±1 → 0)
Location: absolute (at actual exit price if stop/target lines enabled)
Color: theme.exit_color (orange/yellow depending on theme)
Transparency: 0% (fully opaque)
Size: tiny
Result: Clean, probability-scaled markers that don't clutter chart but convey essential information.
6. Stop Loss & Take Profit Lines (Optional, Default: ON)
Visual representation of shadow portfolio risk levels:
Stop Loss Line:
Plots when selected strategy has active position
Level: shadow_stop value from selected strategy
Color: theme.short_primary with 60% transparency (red/pink, subtle)
Width: 2
Style: plot.style_linebr (breaks when no position)
Take Profit Line:
Plots when selected strategy has active position
Level: shadow_target value from selected strategy
Color: theme.long_primary with 60% transparency (green, subtle)
Width: 2
Style: plot.style_linebr (breaks when no position)
Purpose:
Shows where shadow portfolio would exit for stop/target
Helps visualize strategy's risk/reward ratio
Useful for manual traders to set similar levels
Disable for cleaner chart (recommended for presentations)
7. Dynamic Trend EMA
Gradient-colored trend line that visualizes trend strength:
Calculation:
EMA(close, trend_length) - default 50 period (configurable 20-100)
Slope calculated over 10 bars: (current_ema - ema ) / ema × 100
Color Logic:
Trend_direction:
Slope > 0.1% = Bullish (1)
Slope < -0.1% = Bearish (-1)
Otherwise = Neutral (0)
Trend_strength = abs(slope)
Color = Gradient between:
- Neutral color (gray/purple)
- Strong bullish (bright green) if direction = 1
- Strong bearish (bright red) if direction = -1
Gradient factor = trend_strength (0 to 1+ scale)
Visual Behavior:
Faint gray/purple = weak/no trend (choppy conditions)
Light green/red = emerging trend (low strength)
Bright green/red = strong trend (high conviction)
Color intensity = trend strength magnitude
Transparency: 50% (subtle, doesn't overpower price action)
Purpose: Subconscious awareness of trend state without checking dashboard or indicators.
8. Regime Background Tinting (Subtle)
Ultra-low opacity background color indicating detected market regime:
Regime Detection:
Efficiency = directional_movement / total_range (over trend_length bars)
Vol_ratio = current_volatility / average_volatility
IF (efficiency > 0.5 AND vol_ratio < 1.3):
Regime = Trending (1)
ELSE IF (vol_ratio > 1.5):
Regime = Volatile (2)
ELSE:
Regime = Choppy (0)
Background Colors:
Trending: theme.regime_trending (dark green, 92-93% transparency)
Volatile: theme.regime_volatile (dark red, 93% transparency)
Choppy: No tint (normal background)
Purpose:
Subliminal regime awareness
Helps explain why signals are/aren't generating
Trending = ideal conditions for AGE
Volatile = fewer signals, higher thresholds applied
Choppy = mixed signals, lower confidence
Important: Extremely subtle by design. Not meant to be obvious, just subconscious context.
📊 ENHANCED DASHBOARD
Comprehensive real-time metrics in single organized panel (top-right position):
Dashboard Structure (5 columns × 14 rows)
Header Row:
Column 0: "🧬 AGE PRO" + phase indicator (🔴 LIVE or ⏪ HIST)
Column 1: "POPULATION"
Column 2: "PERFORMANCE"
Column 3: "CURRENT SIGNAL"
Column 4: "ACTIVE STRATEGY"
Column 0: Market State
Regime (📈 TREND / 🌊 CHAOS / ➖ CHOP)
DVS Ratio (current volatility scaling factor, format: #.##)
Trend Direction (▲ BULL / ▼ BEAR / ➖ FLAT with color coding)
Trend Strength (0-100 scale, format: #.##)
Column 1: Population Metrics
Active strategies (count / max_population)
Validated strategies (WFO passed / active total)
Current generation number
Total spawned (all-time strategy births)
Total culled (all-time strategy deaths)
Column 2: Aggregate Performance
Total trades across all active strategies
Aggregate win rate (%) - color-coded:
Green (>55%)
Orange (45-55%)
Red (<45%)
Total P&L in R-multiples - color-coded by positive/negative
Best fitness score in population (format: #.###)
MAS - Minimum Adaptation Score (cull threshold, format: #.###)
Column 3: Current Signal Status
Status indicator:
"▲ LONG" (green) if selected strategy in long position
"▼ SHORT" (red) if selected strategy in short position
"⏳ FORMING" (orange) if signal persisting but not yet executed
"○ WAITING" (gray) if no active signal
Confidence percentage (0-100%, format: #.#%)
Quality assessment:
"🔥 ELITE" (cyan) for 85%+ probability
"✓ STRONG" (bright green) for 75-85%
"○ GOOD" (green) for 65-75%
"- LOW" (dim) for <65%
Confluence score (X/3 format)
Signal age:
"X bars" if signal forming
"IN TRADE" if position active
"---" if no signal
Column 4: Selected Strategy Details
Strategy ID number (#X format)
Validation status:
"✓ VAL" (green) if WFO validated
"○ TRAIN" (orange) if still in training/testing phase
Generation number (GX format)
Personal fitness score (format: #.### with color coding)
Trade count
P&L and win rate (format: #.#R (##%) with color coding)
Color Scheme:
Panel background: theme.panel_bg (dark, low opacity)
Panel headers: theme.panel_header (slightly lighter)
Primary text: theme.text_primary (bright, high contrast)
Secondary text: theme.text_secondary (dim, lower contrast)
Positive metrics: theme.metric_positive (green)
Warning metrics: theme.metric_warning (orange)
Negative metrics: theme.metric_negative (red)
Special markers: theme.validated_marker, theme.spawn_marker
Update Frequency: Only on barstate.islast (current bar) to minimize CPU usage
Purpose:
Quick overview of entire system state
No need to check multiple indicators
Trading decisions informed by population health, regime state, and signal quality
Transparency into what AGE is thinking
🔍 DIAGNOSTICS PANEL (Optional, Default: OFF)
Detailed signal quality tracking for optimization and debugging:
Panel Structure (3 columns × 8 rows)
Position: Bottom-right corner (doesn't interfere with main dashboard)
Header Row:
Column 0: "🔍 DIAGNOSTICS"
Column 1: "COUNT"
Column 2: "%"
Metrics Tracked (for selected strategy only):
Total Evaluated:
Every signal that passed initial calculation (direction ≠ 0)
Represents total opportunities considered
✓ Passed:
Signals that passed quality gate and executed
Green color coding
Percentage of evaluated signals
Rejection Breakdown:
⨯ Probability:
Rejected because probability < minimum threshold
Most common rejection reason typically
⨯ Confluence:
Rejected because confluence < minimum required (e.g., only 1 of 3 indicators agreed)
⨯ Trend:
Rejected because signal opposed strong trend
Indicates counter-trend protection working
⨯ Regime:
Rejected because volatile regime detected and probability wasn't high enough to override
Shows regime filter in action
⨯ Volume:
Rejected because volume < 70% of 20-bar average
Indicates volume confirmation requirement
Color Coding:
Passed count: Green (success metric)
Rejection counts: Red (failure metrics)
Percentages: Gray (neutral, informational)
Performance Cost: Slight CPU overhead for tracking counters. Disable when not actively optimizing settings.
How to Use Diagnostics
Scenario 1: Too Few Signals
Evaluated: 200
Passed: 10 (5%)
⨯ Probability: 120 (60%)
⨯ Confluence: 40 (20%)
⨯ Others: 30 (15%)
Diagnosis: Probability threshold too high for this strategy's DNA.
Solution: Lower min probability from 65% to 60%, or allow strategy more time to evolve better DNA.
Scenario 2: Too Many False Signals
Evaluated: 200
Passed: 80 (40%)
Strategy win rate: 45%
Diagnosis: Quality gate too loose, letting low-quality signals through.
Solution: Raise min probability to 70%, or increase min confluence to 3 (all indicators must agree).
Scenario 3: Regime-Specific Issues
⨯ Regime: 90 (45% of rejections)
Diagnosis: Frequent volatile regime detection blocking otherwise good signals.
Solution: Either accept fewer trades during chaos (recommended), or disable regime filter if you want signals regardless of market state.
Optimization Workflow:
Enable diagnostics
Run 200+ bars
Analyze rejection patterns
Adjust settings based on data
Re-run and compare pass rate
Disable diagnostics when satisfied
⚙️ CONFIGURATION GUIDE
🧬 Evolution Engine Settings
Enable AGE Evolution (Default: ON):
ON: Full genetic algorithm (recommended for best results)
OFF: Uses only 4 seed strategies, no spawning/culling (static population for comparison testing)
Max Population (4-12, Default: 8):
Higher = more diversity, more exploration, slower performance
Lower = faster computation, less exploration, risk of premature convergence
Sweet spot: 6-8 for most use cases
4 = minimum for meaningful evolution
12 = maximum before diminishing returns
Min Population (2-4, Default: 3):
Safety floor - system never culls below this count
Prevents population extinction during harsh selection
Should be at least half of max population
Elite Preservation (1-3, Default: 2):
Top N performers completely immune to culling
Ensures best genes always survive
1 = minimal protection, aggressive selection
2 = balanced (recommended)
3 = conservative, slower gene pool turnover
Historical: Spawn Interval (10-100, Default: 30):
Bars between spawning new strategies during historical data
Lower = faster evolution, more exploration
Higher = slower evolution, more evaluation time per strategy
30 bars = ~1-2 hours on 15min chart
Historical: Cull Interval (20-200, Default: 60):
Bars between culling weak strategies during historical data
Should be 2x spawn interval for balanced churn
Lower = aggressive selection pressure
Higher = patient evaluation
Live: Spawn Interval (100-500, Default: 200):
Bars between spawning during live trading
Much slower than historical for stability
Prevents population chaos during live trading
200 bars = ~1.5 trading days on 15min chart
Live: Cull Interval (200-1000, Default: 400):
Bars between culling during live trading
Should be 2x live spawn interval
Conservative removal during live trading
Historical: Mutation Rate (0.05-0.40, Default: 0.20):
Probability each gene mutates during breeding (20% = 2 out of 10 genes on average)
Higher = more exploration, slower convergence
Lower = more exploitation, faster convergence but risk of local optima
20% balances exploration vs exploitation
Live: Mutation Rate (0.02-0.20, Default: 0.08):
Mutation rate during live trading
Much lower for stability (don't want population to suddenly degrade)
8% = mostly inherits parent genes with small tweaks
Mutation Strength (0.05-0.25, Default: 0.12):
How much genes change when mutated (% of gene's total range)
0.05 = tiny nudges (fine-tuning)
0.12 = moderate jumps (recommended)
0.25 = large leaps (aggressive exploration)
Example: If gene range is 0.5-2.0, 12% strength = ±0.18 possible change
📈 Signal Quality Settings
Min Signal Probability (0.55-0.80, Default: 0.65):
Quality gate threshold - signals below this never generate
0.55-0.60 = More signals, accept lower confidence (higher risk)
0.65 = Institutional-grade balance (recommended)
0.70-0.75 = Fewer but higher-quality signals (conservative)
0.80+ = Very selective, very few signals (ultra-conservative)
Min Confluence Score (1-3, Default: 2):
Required indicator agreement before signal generates
1 = Any single indicator can trigger (not recommended - too many false signals)
2 = Requires 2 of 3 indicators agree (RECOMMENDED for balance)
3 = All 3 must agree (very selective, few signals, high quality)
Base Persistence Bars (1-5, Default: 2):
Base bars signal must persist before entry
System adapts automatically:
High probability signals (75%+) enter 1 bar faster
Low probability signals (<68%) need 1 bar more
Trending regime: -1 bar (faster entries)
Volatile regime: +1 bar (more confirmation)
1 = Immediate entry after quality gate (responsive but prone to whipsaw)
2 = Balanced confirmation (recommended)
3-5 = Patient confirmation (slower but more reliable)
Cooldown After Trade (3-20, Default: 8):
Bars to wait after exit before next entry allowed
Prevents overtrading and revenge trading
3 = Minimal cooldown (active trading)
8 = Balanced (recommended)
15-20 = Conservative (position trading)
Entropy Length (10-50, Default: 20):
Lookback period for market order/disorder calculation
Lower = more responsive to regime changes (noisy)
Higher = more stable regime detection (laggy)
20 = works across most timeframes
Momentum Length (5-30, Default: 14):
Period for RSI/ROC calculations
14 = standard (RSI default)
Lower = more signals, less reliable
Higher = fewer signals, more reliable
Structure Length (20-100, Default: 50):
Lookback for support/resistance swing range
20 = short-term swings (day trading)
50 = medium-term structure (recommended)
100 = major structure (position trading)
Trend EMA Length (20-100, Default: 50):
EMA period for trend detection and direction bias
20 = short-term trend (responsive)
50 = medium-term trend (recommended)
100 = long-term trend (position trading)
ATR Period (5-30, Default: 14):
Period for volatility measurement
14 = standard ATR
Lower = more responsive to vol changes
Higher = smoother vol calculation
📊 Volatility Scaling (DVS) Settings
Enable DVS (Default: ON):
Dynamic volatility scaling for adaptive stop/target placement
Highly recommended to leave ON
OFF only for testing fixed-distance stops
DVS Method (Default: Ensemble):
ATR Ratio: Simple, fast, single-method (good for beginners)
Parkinson: High-low range based (good for intraday)
Garman-Klass: OHLC based (sophisticated, considers gaps)
Ensemble: Median of all three (RECOMMENDED - most robust)
DVS Memory (20-200, Default: 100):
Lookback for baseline volatility comparison
20 = very responsive to vol changes (can overreact)
100 = balanced adaptation (recommended)
200 = slow, stable baseline (minimizes false vol signals)
DVS Sensitivity (0.3-1.5, Default: 0.7):
How much volatility affects scaling (power-law exponent)
0.3 = Conservative, heavily dampens vol impact (cube root)
0.5 = Moderate dampening (square root)
0.7 = Balanced response (recommended)
1.0 = Linear, full 1:1 vol response
1.5 = Aggressive, amplified response (exponential)
🔬 Walk-Forward Optimization Settings
Enable WFO (Default: ON):
Out-of-sample validation to prevent overfitting
Highly recommended to leave ON
OFF only for testing or if you want unvalidated strategies
Training Window (100-500, Default: 250):
Bars for in-sample optimization
100 = fast validation, less data (risky)
250 = balanced (recommended) - about 1-2 months on daily, 1-2 weeks on 15min
500 = patient validation, more data (conservative)
Testing Window (30-200, Default: 75):
Bars for out-of-sample validation
Should be ~30% of training window
30 = minimal test (fast validation)
75 = balanced (recommended)
200 = extensive test (very conservative)
Min Trades for Validation (3-15, Default: 5):
Required trades in BOTH training AND testing periods
3 = minimal sample (risky, fast validation)
5 = balanced (recommended)
10+ = conservative (slow validation, high confidence)
WFO Efficiency Threshold (0.3-0.9, Default: 0.55):
Minimum test/train performance ratio required
0.30 = Very loose (test must be 30% as good as training)
0.55 = Balanced (recommended) - test must be 55% as good
0.70+ = Strict (test must closely match training)
Higher = fewer validated strategies, lower risk of overfitting
🎨 Premium Visuals Settings
Visual Theme:
Neon Genesis: Cyberpunk aesthetic (cyan/magenta/purple)
Carbon Fiber: Industrial look (blue/red/gray)
Quantum Blue: Quantum computing (blue/purple/pink)
Aurora: Northern lights (teal/orange/purple)
⚡ Gradient Probability Cloud (Default: ON):
Multi-layer gradient showing signal buildup
Turn OFF if chart lags or for cleaner look
Cloud Gradient Layers (3-15, Default: 7):
More layers = smoother gradient, more CPU intensive
Fewer layers = faster, blockier appearance
🎗️ Population Fitness Ribbon (Default: ON):
Histogram showing fitness distribution
Turn OFF for cleaner chart
Ribbon Layers (5-20, Default: 10):
More layers = finer fitness detail
Fewer layers = simpler histogram
⭕ Signal Confidence Halo (Default: ON):
Circular indicator around entry signals
Size/brightness scales with probability
Minimal performance cost
🔬 Evolution Event Markers (Default: ON):
Diamond (spawn) and X (cull) markers
Shows genetic algorithm activity
Minimal performance cost
🎯 Stop/Target Lines (Default: ON):
Shows shadow portfolio stop/target levels
Turn OFF for cleaner chart (recommended for screenshots/presentations)
📊 Enhanced Dashboard (Default: ON):
Comprehensive metrics panel
Should stay ON unless you want zero overlays
🔍 Diagnostics Panel (Default: OFF):
Detailed signal rejection tracking
Turn ON when optimizing settings
Turn OFF during normal use (slight performance cost)
📈 USAGE WORKFLOW - HOW TO USE THIS INDICATOR
Phase 1: Initial Setup & Learning
Add AGE to your chart
Recommended timeframes: 15min, 30min, 1H (best signal-to-noise ratio)
Works on: 5min (day trading), 4H (swing trading), Daily (position trading)
Load 1000+ bars for sufficient evolution history
Let the population evolve (100+ bars minimum)
First 50 bars: Random exploration, poor results expected
Bars 50-150: Population converging, fitness improving
Bars 150+: Stable performance, validated strategies emerging
Watch the dashboard metrics
Population should grow toward max capacity
Generation number should advance regularly
Validated strategies counter should increase
Best fitness should trend upward toward 0.50-0.70 range
Observe evolution markers
Diamond markers (cyan) = new strategies spawning
X markers (red) = weak strategies being culled
Frequent early activity = healthy evolution
Activity slowing = population stabilizing
Be patient. Evolution takes time. Don't judge performance before 150+ bars.
Phase 2: Signal Observation
Watch signals form
Gradient cloud builds up 2-3 bars before entry
Cloud brightness = probability strength
Cloud thickness = signal persistence
Check signal quality
Look at confidence halo size when entry marker appears
Large bright halo = elite setup (85%+)
Medium halo = strong setup (75-85%)
Small halo = good setup (65-75%)
Verify market conditions
Check trend EMA color (green = uptrend, red = downtrend, gray = choppy)
Check background tint (green = trending, red = volatile, clear = choppy)
Trending background + aligned signal = ideal conditions
Review dashboard signal status
Current Signal column shows:
Status (Long/Short/Forming/Waiting)
Confidence % (actual probability value)
Quality assessment (Elite/Strong/Good)
Confluence score (2/3 or 3/3 preferred)
Only signals meeting ALL quality gates appear on chart. If you're not seeing signals, population is either still learning or market conditions aren't suitable.
Phase 3: Manual Trading Execution
When Long Signal Fires:
Verify confidence level (dashboard or halo size)
Confirm trend alignment (EMA sloping up, green color)
Check regime (preferably trending or choppy, avoid volatile)
Enter long manually on your broker platform
Set stop loss at displayed stop line level (if lines enabled), or use your own risk management
Set take profit at displayed target line level, or trail manually
Monitor position - exit if X marker appears (signal reversal)
When Short Signal Fires:
Same verification process
Confirm downtrend (EMA sloping down, red color)
Enter short manually
Use displayed stop/target levels or your own
AGE tells you WHEN and HOW CONFIDENT. You decide WHETHER and HOW MUCH.
Phase 4: Set Up Alerts (Never Miss a Signal)
Right-click on indicator name in legend
Select "Add Alert"
Choose condition:
"AGE Long" = Long entry signal fired
"AGE Short" = Short entry signal fired
"AGE Exit" = Position reversal/exit signal
Set notification method:
Sound alert (popup on chart)
Email notification
Webhook to phone/trading platform
Mobile app push notification
Name the alert (e.g., "AGE BTCUSD 15min Long")
Save alert
Recommended: Set alerts for both long and short, enable mobile push notifications. You'll get alerted in real-time even if not watching charts.
Phase 5: Monitor Population Health
Weekly Review:
Check dashboard Population column:
Active count should be near max (6-8 of 8)
Validated count should be >50% of active
Generation should be advancing (1-2 per week typical)
Check dashboard Performance column:
Aggregate win rate should be >50% (target: 55-65%)
Total P&L should be positive (may fluctuate)
Best fitness should be >0.50 (target: 0.55-0.70)
MAS should be declining slowly (normal adaptation)
Check Active Strategy column:
Selected strategy should be validated (✓ VAL)
Personal fitness should match best fitness
Trade count should be accumulating
Win rate should be >50%
Warning Signs:
Zero validated strategies after 300+ bars = settings too strict or market unsuitable
Best fitness stuck <0.30 = population struggling, consider parameter adjustment
No spawning/culling for 200+ bars = evolution stalled (may be optimal or need reset)
Aggregate win rate <45% sustained = system not working on this instrument/timeframe
Health Check Pass:
50%+ strategies validated
Best fitness >0.50
Aggregate win rate >52%
Regular spawn/cull activity
Selected strategy validated
Phase 6: Optimization (If Needed)
Enable Diagnostics Panel (bottom-right) for data-driven tuning:
Problem: Too Few Signals
Evaluated: 200
Passed: 8 (4%)
⨯ Probability: 140 (70%)
Solutions:
Lower min probability: 65% → 60% or 55%
Reduce min confluence: 2 → 1
Lower base persistence: 2 → 1
Increase mutation rate temporarily to explore new genes
Check if regime filter is blocking signals (⨯ Regime high?)
Problem: Too Many False Signals
Evaluated: 200
Passed: 90 (45%)
Win rate: 42%
Solutions:
Raise min probability: 65% → 70% or 75%
Increase min confluence: 2 → 3
Raise base persistence: 2 → 3
Enable WFO if disabled (validates strategies before use)
Check if volume filter is being ignored (⨯ Volume low?)
Problem: Counter-Trend Losses
⨯ Trend: 5 (only 5% rejected)
Losses often occur against trend
Solutions:
System should already filter trend opposition
May need stronger trend requirement
Consider only taking signals aligned with higher timeframe trend
Use longer trend EMA (50 → 100)
Problem: Volatile Market Whipsaws
⨯ Regime: 100 (50% rejected by volatile regime)
Still getting stopped out frequently
Solutions:
System is correctly blocking volatile signals
Losses happening because vol filter isn't strict enough
Consider not trading during volatile periods (respect the regime)
Or disable regime filter and accept higher risk
Optimization Workflow:
Enable diagnostics
Run 200+ bars with current settings
Analyze rejection patterns and win rate
Make ONE change at a time (scientific method)
Re-run 200+ bars and compare results
Keep change if improvement, revert if worse
Disable diagnostics when satisfied
Never change multiple parameters at once - you won't know what worked.
Phase 7: Multi-Instrument Deployment
AGE learns independently on each chart:
Recommended Strategy:
Deploy AGE on 3-5 different instruments
Different asset classes ideal (e.g., ES futures, EURUSD, BTCUSD, SPY, Gold)
Each learns optimal strategies for that instrument's personality
Take signals from all 5 charts
Natural diversification reduces overall risk
Why This Works:
When one market is choppy, others may be trending
Different instruments respond to different news/catalysts
Portfolio-level win rate more stable than single-instrument
Evolution explores different parameter spaces on each chart
Setup:
Same settings across all charts (or customize if preferred)
Set alerts for all
Take every validated signal across all instruments
Position size based on total account (don't overleverage any single signal)
⚠️ REALISTIC EXPECTATIONS - CRITICAL READING
What AGE Can Do
✅ Generate probability-weighted signals using genetic algorithms
✅ Evolve strategies in real-time through natural selection
✅ Validate strategies on out-of-sample data (walk-forward optimization)
✅ Adapt to changing market conditions automatically over time
✅ Provide comprehensive metrics on population health and signal quality
✅ Work on any instrument, any timeframe, any broker
✅ Improve over time as weak strategies are culled and fit strategies breed
What AGE Cannot Do
❌ Win every trade (typical win rate: 55-65% at best)
❌ Predict the future with certainty (markets are probabilistic, not deterministic)
❌ Work perfectly from bar 1 (needs 100-150 bars to learn and stabilize)
❌ Guarantee profits under all market conditions
❌ Replace your trading discipline and risk management
❌ Execute trades automatically (this is an indicator, not a strategy)
❌ Prevent all losses (drawdowns are normal and expected)
❌ Adapt instantly to regime changes (re-learning takes 50-100 bars)
Performance Realities
Typical Performance After Evolution Stabilizes (150+ bars):
Win Rate: 55-65% (excellent for trend-following systems)
Profit Factor: 1.5-2.5 (realistic for validated strategies)
Signal Frequency: 5-15 signals per 100 bars (quality over quantity)
Drawdown Periods: 20-40% of time in equity retracement (normal trading reality)
Max Consecutive Losses: 5-8 losses possible even with 60% win rate (probability says this is normal)
Evolution Timeline:
Bars 0-50: Random exploration, learning phase - poor results expected, don't judge yet
Bars 50-150: Population converging, fitness climbing - results improving
Bars 150-300: Stable performance, most strategies validated - consistent results
Bars 300+: Mature population, optimal genes dominant - best results
Market Condition Dependency:
Trending Markets: AGE excels - clear directional moves, high-probability setups
Choppy Markets: AGE struggles - fewer signals generated, lower win rate
Volatile Markets: AGE cautious - higher rejection rate, wider stops, fewer trades
Market Regime Changes:
When market shifts from trending to choppy overnight
Validated strategies can become temporarily invalidated
AGE will adapt through evolution, but not instantly
Expect 50-100 bar re-learning period after major regime shifts
Fitness may temporarily drop then recover
This is NOT a holy grail. It's a sophisticated signal generator that learns and adapts using genetic algorithms. Your success depends on:
Patience during learning periods (don't abandon after 3 losses)
Proper position sizing (risk 0.5-2% per trade, not 10%)
Following signals consistently (cherry-picking defeats statistical edge)
Not abandoning system prematurely (give it 200+ bars minimum)
Understanding probability (60% win rate means 40% of trades WILL lose)
Respecting market conditions (trending = trade more, choppy = trade less)
Managing emotions (AGE is emotionless, you need to be too)
Expected Drawdowns:
Single-strategy max DD: 10-20% of equity (normal)
Portfolio across multiple instruments: 5-15% (diversification helps)
Losing streaks: 3-5 consecutive losses expected periodically
No indicator eliminates risk. AGE manages risk through:
Quality gates (rejecting low-probability signals)
Confluence requirements (multi-indicator confirmation)
Persistence requirements (no knee-jerk reactions)
Regime awareness (reduced trading in chaos)
Walk-forward validation (preventing overfitting)
But it cannot prevent all losses. That's inherent to trading.
🔧 TECHNICAL SPECIFICATIONS
Platform: TradingView Pine Script v5
Indicator Type: Overlay indicator (plots on price chart)
Execution Type: Signals only - no automatic order placement
Computational Load:
Moderate to High (genetic algorithms + shadow portfolios)
8 strategies × shadow portfolio simulation = significant computation
Premium visuals add additional load (gradient cloud, fitness ribbon)
TradingView Resource Limits (Built-in Caps):
Max Bars Back: 500 (sufficient for WFO and evolution)
Max Labels: 100 (plenty for entry/exit markers)
Max Lines: 150 (adequate for stop/target lines)
Max Boxes: 50 (not heavily used)
Max Polylines: 100 (confidence halos)
Recommended Chart Settings:
Timeframe: 15min to 1H (optimal signal/noise balance)
5min: Works but noisier, more signals
4H/Daily: Works but fewer signals
Bars Loaded: 1000+ (ensures sufficient evolution history)
Replay Mode: Excellent for testing without risk
Performance Optimization Tips:
Disable gradient cloud if chart lags (most CPU intensive visual)
Disable fitness ribbon if still laggy
Reduce cloud layers from 7 to 3
Reduce ribbon layers from 10 to 5
Turn off diagnostics panel unless actively tuning
Close other heavy indicators to free resources
Browser/Platform Compatibility:
Works on all modern browsers (Chrome, Firefox, Safari, Edge)
Mobile app supported (full functionality on phone/tablet)
Desktop app supported (best performance)
Web version supported (may be slower on older computers)
Data Requirements:
Real-time or delayed data both work
No special data feeds required
Works with TradingView's standard data
Historical + live data seamlessly integrated
🎓 THEORETICAL FOUNDATIONS
AGE synthesizes advanced concepts from multiple disciplines:
Evolutionary Computation
Genetic Algorithms (Holland, 1975): Population-based optimization through natural selection metaphor
Tournament Selection: Fitness-based parent selection with diversity preservation
Crossover Operators: Fitness-weighted gene recombination from two parents
Mutation Operators: Random gene perturbation for exploration of new parameter space
Elitism: Preservation of top N performers to prevent loss of best solutions
Adaptive Parameters: Different mutation rates for historical vs. live phases
Technical Analysis
Support/Resistance: Price structure within swing ranges
Trend Following: EMA-based directional bias
Momentum Analysis: RSI, ROC, MACD composite indicators
Volatility Analysis: ATR-based risk scaling
Volume Confirmation: Trade activity validation
Information Theory
Shannon Entropy (1948): Quantification of market order vs. disorder
Signal-to-Noise Ratio: Directional information vs. random walk
Information Content: How much "information" a price move contains
Statistics & Probability
Walk-Forward Analysis: Rolling in-sample/out-of-sample optimization
Out-of-Sample Validation: Testing on unseen data to prevent overfitting
Monte Carlo Principles: Shadow portfolio simulation with realistic execution
Expectancy Theory: Win rate × avg win - loss rate × avg loss
Probability Distributions: Signal confidence quantification
Risk Management
ATR-Based Stops: Volatility-normalized risk per trade
Volatility Regime Detection: Market state classification (trending/choppy/volatile)
Drawdown Control: Peak-to-trough equity measurement
R-Multiple Normalization: Performance measurement in risk units
Machine Learning Concepts
Online Learning: Continuous adaptation as new data arrives
Fitness Functions: Multi-objective optimization (win rate + expectancy + drawdown)
Exploration vs. Exploitation: Balance between trying new strategies and using proven ones
Overfitting Prevention: Walk-forward validation as regularization
Novel Contribution:
AGE is the first TradingView indicator to apply genetic algorithms to real-time indicator parameter optimization while maintaining strict anti-overfitting controls through walk-forward validation.
Most "adaptive" indicators simply recalibrate lookback periods or thresholds. AGE evolves entirely new strategies through competitive selection - it's not parameter tuning, it's Darwinian evolution of trading logic itself.
The combination of:
Genetic algorithm population management
Shadow portfolio simulation for realistic fitness evaluation
Walk-forward validation to prevent overfitting
Multi-indicator confluence for signal quality
Dynamic volatility scaling for adaptive risk
...creates a system that genuinely learns and improves over time while avoiding the curse of curve-fitting that plagues most optimization approaches.
🏗️ DEVELOPMENT NOTES
This project represents months of intensive development, facing significant technical challenges:
Challenge 1: Making Genetics Actually Work
Early versions spawned garbage strategies that polluted the gene pool:
Random gene combinations produced nonsensical parameter sets
Weak strategies survived too long, dragging down population
No clear convergence toward optimal solutions
Solution:
Comprehensive fitness scoring (4 factors: win rate, P&L, expectancy, drawdown)
Elite preservation (top 2 always protected)
Walk-forward validation (unproven strategies penalized 30%)
Tournament selection (fitness-weighted breeding)
Adaptive culling (MAS decay creates increasing selection pressure)
Challenge 2: Balancing Evolution Speed vs. Stability
Too fast = population chaos, no convergence. Too slow = can't adapt to regime changes.
Solution:
Dual-phase timing: Fast evolution during historical (30/60 bar intervals), slow during live (200/400 bar intervals)
Adaptive mutation rates: 20% historical, 8% live
Spawn/cull ratio: Always 2:1 to prevent population collapse
Challenge 3: Shadow Portfolio Accuracy
Needed realistic trade simulation without lookahead bias:
Can't peek at future bars for exits
Must track multiple portfolios simultaneously
Stop/target checks must use bar's high/low correctly
Solution:
Entry on close (realistic)
Exit checks on current bar's high/low (realistic)
Independent position tracking per strategy
Cooldown periods to prevent unrealistic rapid re-entry
ATR-normalized P&L (R-multiples) for fair comparison across volatility regimes
Challenge 4: Pine Script Compilation Limits
Hit TradingView's execution limits multiple times:
Too many array operations
Too many variables
Too complex conditional logic
Solution:
Optimized data structures (single DNA array instead of 8 separate arrays)
Minimal visual overlays (only essential plots)
Efficient fitness calculations (vectorized where possible)
Strategic use of barstate.islast to minimize dashboard updates
Challenge 5: Walk-Forward Implementation
Standard WFO is difficult in Pine Script:
Can't easily "roll forward" through historical data
Can't re-optimize strategies mid-stream
Must work in real-time streaming environment
Solution:
Age-based phase detection (first 250 bars = training, next 75 = testing)
Separate metric tracking for train vs. test
Efficiency calculation at fixed interval (after test period completes)
Validation flag persists for strategy lifetime
Challenge 6: Signal Quality Control
Early versions generated too many signals with poor win rates:
Single indicators produced excessive noise
No trend alignment
No regime awareness
Instant entries on single-bar spikes
Solution:
Three-layer confluence system (entropy + momentum + structure)
Minimum 2-of-3 agreement requirement
Trend alignment checks (penalty for counter-trend)
Regime-based probability adjustments
Persistence requirements (signals must hold multiple bars)
Volume confirmation
Quality gate (probability + confluence thresholds)
The Result
A system that:
Truly evolves (not just parameter sweeps)
Truly validates (out-of-sample testing)
Truly adapts (ongoing competition and breeding)
Stays within TradingView's platform constraints
Provides institutional-quality signals
Maintains transparency (full metrics dashboard)
Development time: 3+ months of iterative refinement
Lines of code: ~1500 (highly optimized)
Test instruments: ES, NQ, EURUSD, BTCUSD, SPY, AAPL
Test timeframes: 5min, 15min, 1H, Daily
🎯 FINAL WORDS
The Adaptive Genesis Engine is not just another indicator - it's a living system that learns, adapts, and improves through the same principles that drive biological evolution. Every bar it observes adds to its experience. Every strategy it spawns explores new parameter combinations. Every strategy it culls removes weakness from the gene pool.
This is evolution in action on your charts.
You're not getting a static formula locked in time. You're getting a system that thinks , that competes , that survives through natural selection. The strongest strategies rise to the top. The weakest die. The gene pool improves generation after generation.
AGE doesn't claim to predict the future - it adapts to whatever the future brings. When markets shift from trending to choppy, from calm to volatile, from bullish to bearish - AGE evolves new strategies suited to the new regime.
Use it on any instrument. Any timeframe. Any market condition. AGE will adapt.
This indicator gives you the pure signal intelligence. How you choose to act on it - position sizing, risk management, execution discipline - that's your responsibility. AGE tells you when and how confident . You decide whether and how much .
Trust the process. Respect the evolution. Let Darwin work.
"In markets, as in nature, it is not the strongest strategies that survive, nor the most intelligent - but those most responsive to change."
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
— Happy Holiday's
KSL-Fullsystem V2.0Trend Following & Reversal Trading System. It combines **Price Action (Market Structure)** with multiple technical indicators to generate high-quality Buy and Sell signals.
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1. How Signals are Generated (The Core Logic)
The script uses **"Internal Shifts"** (Market Structure Breaks) to find entry points.
* BUY Signal: The price breaks above a previous bearish structure (Higher High) + All enabled filters are Green.
* SELL Signal: The price breaks below a previous bullish structure (Lower Low) + All enabled filters are Red.
When a signal occurs, the script automatically calculates:
* Stop Loss (SL): Based on the recent Swing High/Low.
* Take Profit (TP): Three levels (TP1, TP2, TP3) based on risk-reward ratios (1.5x, 2.0x, 3.0x).
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2. The Filters (Your Confirmation Checklist)
You can turn these On/Off in the settings. **Note:** If you turn *all* of them on, you might get very few signals because the conditions become too strict.
**A. Bollinger Bands (BB) Filters (Primary Feature)**
This is the main filter for this version.
* Squeeze Filter: Prevents trading when the bands are too narrow (low volatility). If the background turns **Yellow**, it means the market is "Squeezing" – **Do Not Trade.**
* Touch Entry: Looks for price bouncing off the Lower Band (Buy) or Upper Band (Sell).
* Breakout Entry: Looks for price blasting through the bands.
* Mean Reversion: Checks if price is reverting to the middle line (Basis).
**B. Moving Average Filters (Trend)**
The script includes three types of Moving Averages. You can choose which style suits you:
* EMA (Exponential): Fast-reacting. Good for scalping.
* SMA (Simple): Standard trend lines. Good for position trading.
* LWMA (Linear Weighted): Focuses heavily on recent data.
* Configuration: You can select specific setups like "Scalping" (9/21/50 EMA) or "Trend" (50/200 EMA).
**C. Momentum Filters**
* MACD: Checks momentum. You can choose settings for Scalping, Day Trading, or Swing Trading.
* AO (Awesome Oscillator) & AC: Helps confirm if the momentum is strong enough to support the trend.
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**3. Visual Guide: What You See on the Chart**
* Green Box: A Buy Zone (Demand).
* Red Box: A Sell Zone (Supply).
* Labels (Text): Shows "BUY" or "SELL" with exact prices for TP1, TP2, TP3, and SL.
* Blue Lines: The Bollinger Bands (Upper and Lower).
* Orange Line: The Bollinger Band Basis (Middle).
* Small Triangles:
* Green Triangle (Below Bar): Price touched the Lower Bollinger Band.
* Red Triangle (Above Bar): Price touched the Upper Bollinger Band.
* Yellow Background: **WARNING.** The market has low volume/volatility (BB Squeeze). Wait for a breakout.
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4. How to Use This Script
1. Select Your Style: Go to the Settings (Inputs).
* If you are a **Scalper**, turn on "Scalping EMA" or "Scalping MACD".
* If you are a **Swing Trader**, turn on "Swing SMA" or "Trend EMA".
2. Configure Bollinger Bands: Keep `Use Bollinger Bands Filter` checked. Decide if you want to trade "Squeezes" (usually safer to avoid them).
3. Wait for the Label: Do not enter blindly. Wait for the script to print a **BUY** or **SELL** label with the TP/SL targets.
4. Check the Background: If the background is **Yellow**, ignore the signal or wait until the color clears.
5. Manage Risk: Place your Stop Loss at the price shown on the label ("SL").
Opening Range & Session Liquidity [LTS]“Opening Range & Session Liquidity ” is an intraday planning tool that combines a configurable Opening Range box with session highs/lows and previous-day reference levels. It is designed to help you visualize where liquidity is likely to build up around the cash open and major global sessions, without making any forecasts or performance promises. It is designed with our signature attention to user customization and accessibility.
Opening Range & Bias
The script builds a configurable Opening Range (OR) in New York time (default 08:00–08:15 on a 15-minute basis), regardless of your chart timeframe (up to 1-hour). The high, low, and midline of this window are drawn as a transparent box and dashed midline that extend forward so you can see how the session trades around that range.
At a user-defined Bias Check Time (default 09:30–09:31 NY), the script classifies the OR as:
Bullish if price is above the OR high
Bearish if price is below the OR low
Neutral if price is still trading inside the OR
The box color updates to reflect the current bias if bias mode is enabled. All OR parameters (formation window, bias check, colors, maximum number of zones, etc.) are adjustable.
Entry Signal Logic
The indicator can optionally generate non-repainting visual signals when price interacts with the OR midline.
1. 9:30 Bias mode (trend-following)
A directional bias is locked in at the bias check time.
Signals trigger only when price trades through the OR midline inside the box, aligned with that bias:
Bullish bias → long signal when price touches the midline from below and closes inside the range.
Bearish bias → short signal when price touches the midline from above and closes inside the range.
Each “episode” can fire only once; signals are confirmed on the bar where the conditions first become true.
2. Entry Direction mode (reaction to first touch)
Instead of using a fixed 9:30 bias, the script detects from which side price first enters the OR (from above or from below).
That “entry direction” stays active until price fully exits and closes outside the OR again.
When price later touches the midline while the entry direction is defined, a single long or short signal is triggered based on the stored direction of entry.
In both modes, historical signals are plotted without using future data; only the real-time bar can change state until it closes.
Optional TP/SL Visualization
When a long or short signal appears, the script can draw simple take-profit/stop-loss boxes to illustrate a basic one-trade idea:
Stop-loss distance can be defined as:
A fixed number of points beyond the OR high/low, or
A percentage of ATR (configurable length and percent).
Take-profit is automatically placed at a user-defined risk-to-reward multiple of that stop distance.
The boxes extend forward bar by bar and stop updating once either TP or SL is touched, or when a new OR session resets the context.
These boxes are for visualization only and do not place or manage orders.
Session Liquidity & PDH/PDL
To help you map where liquidity frequently builds up, the script tracks three configurable intraday sessions in New York time:
Asian session (default 18:00–02:00)
London session (default 03:00–08:00)
New York session (default 09:30–16:00)
For each completed session, the indicator records the session high and low, then:
Draws solid horizontal lines and labels (e.g., “Asia Hi/Lo”, “London Hi/Lo”, “NY Hi/Lo”).
Extends these solid lines to the right as long as they remain untouched by price.
When price first trades through a level, the solid line is cut at that bar and replaced by a dashed line that extends only until the next session of the same type begins.
Older sessions are automatically removed according to the “Max Sessions to Display” setting to reduce chart clutter.
In addition, the indicator plots:
Previous Day High (PDH) & Previous Day Low (PDL)
Previous Day Point of Control (PDPoC) – an approximate volume-weighted price computed from intraday data using a simple binning approach on a user-chosen lower timeframe.
Like the session levels, PDH/PDL/PDPoC start as solid lines. After the first touch, each level switches to a dashed style and continues only until the following trading day, at which point the previous day’s dashed lines are stopped and new levels are created.
Info Table & Multi-Timeframe Logic
An optional on-chart info table summarizes the most recent Opening Range:
OR high, low, and midline
Current OR range in points
Active mode (9:30 Bias vs. Entry Direction)
Current bias or entry-direction status
Whether a signal is “Waiting”, “Armed”, or “Triggered”
Whether the OR was built from the chart timeframe or from a 15-minute higher-timeframe feed
If your chart timeframe is higher than the OR calculation timeframe, the script automatically uses multi-timeframe data to build a consistent OR, while enforcing a maximum chart timeframe of 1-hour for reliability.
How to Use This Tool
Use the OR box and bias to define your primary intraday context around the cash open.
Use session highs/lows and PDH/PDL/PDPoC as objective reference levels for where price may react or where stops and liquidity might cluster.
Treat the signal markers and TP/SL boxes as visual guides only. They can help you structure trade ideas, but they are not a trading system by themselves.
Always confirm levels and signals with your own analysis, risk management, and execution rules.
Limitations & Notes
The script is intended for intraday charts up to 1-hour. By the nature of the information being displayed, any time frame above that may result is undesirable visual clutter.
The POC calculation is an approximation based on lower timeframe bar-level volume and binning; it is not a tick-by-tick volume profile.
Signals and levels update in real time on the current forming bar. Once a bar closes, completed historical signals do not repaint, but the last live bar can change until it closes.
The indicator does not use lookahead or offset plotting into the past; it is not designed to predict the future or guarantee any particular trading result.
Always test settings on a demo environment first and manage risk according to your own plan.
XΩ — Trade Commander (Global)1. What is XΩ — Trade Commander?
XΩ — Trade Commander (Global) is a post‑entry position management system.
It does not tell you where to enter. Instead, it helps you manage a trade after you are already in:
Dynamic Trailing Stop based on volatility (ATR)
Visual Safe Zone under price
R‑Multiple targets (1R, 2R, 3R) for profit‑taking
A live Position Dashboard with PnL and suggested actions
Exit alert when price breaks the Trailing Stop
Plus a ZERO GENESIS brand signature on the chart
Think of it as a trade commander / position guardian that enforces your risk and trailing rules.
2. Basic setup (Inputs)
In the Active Position Settings group:
Position Active?
Turn ON when you have a live position you want to manage.
Turn OFF when flat (no position), to effectively disable the management logic.
Avg Entry Price
Enter your average entry price (if you scaled in, use your weighted average).
This is the reference for all PnL and R calculations.
Initial Stop Loss
Your original invalidation price (hard stop) when you planned the trade.
Used to define:
The size of 1R (initial risk unit)
The locations of 1R, 2R, 3R targets.
Position Size (Units)
Size of your current position (number of shares/coins/contracts, etc.).
Used to convert PnL into currency value.
In the Trailing Stop Engine group:
Trailing Width (xATR)
Controls how tight/loose the trailing stop is:
Smaller value → tighter, closer to price (protects faster, more likely to get stopped out early)
Larger value → looser, farther from price (lets winners run, accepts more swing)
Source
Price source for the trailing engine:
AVA → smoothed price (reduces noise and “random” stop‑outs)
Close → closing price
High/Low → mid of high & low
In the Take Profit Targets (R-Multiples) group:
Show R-Levels
Turn ON to draw 1R, 2R, 3R reference lines on the chart.
Turn OFF if you prefer a cleaner chart.
3. How to read the indicator on the chart
Once Position Active? is ON and you’ve filled Avg Entry Price / Initial Stop Loss / Position Size, you’ll see:
3.1. Trailing Stop line (“The Shield”)
A blue/gray line below price (for long trades):
It only moves up, never down (ratchet‑style trailing).
When price rises → the trailing stop is adjusted upward.
When price falls → the trailing stop stays in place, not lowered.
Color:
Blue → price is still above the trailing stop (protected, trade is “alive”).
Gray → price is below the trailing stop (trailing has been violated).
Visually, this line is your dynamic protective shield.
3.2. Safe Zone (blue fill)
Light blue fill between price (chosen source) and the Trailing Stop line.
Represents your current buffer:
Thick Safe Zone → good distance to the stop → room for normal volatility.
Thin Safe Zone → close to stop → trade is at risk of being closed.
3.3. Entry & Hard Stop lines
Horizontal lines:
Entry Price → gray dotted line
Initial Stop Loss → solid red line
Helps you always see:
Where the trade started
Where the original invalidation was (your planned “I’m wrong here” level)
3.4. R‑Multiple Targets (1R, 2R, 3R)
When Show R-Levels is ON and Initial Stop Loss is set:
1R: dashed green line, labeled 1R
2R: dashed green line, labeled 2R
3R: dashed green line, labeled 3R (Target)
Use these for:
Planning partial take‑profits
Knowing when it’s reasonable to move your stop (e.g., to breakeven at 1R)
Evaluating your trade in terms of reward vs initial risk
3.5. “POSITION GUARDIAN” Dashboard label
Near the current price, you’ll see a label like:
Title: 🛡️ POSITION GUARDIAN
Inside:
Size: your position size and entry price
PnL: current profit/loss percentage and value (auto‑formatted, e.g. 1.23M, 45K, etc.)
R-Multiple: your current R (e.g., 0.7R, 1.5R, 3.2R)
TRAILING STOP: the current trailing stop price
ACTION: a suggested action string, for example:
🚫 TRAILING HIT -> EXIT NOW!
🚀 RUNNING PROFIT (x.xR) -> Hold or Trim
✅ IN PROFIT (x.xR) -> Move SL to BE
⚠️ DRAWDOWN -> Watch Trailing Stop
🟢 BREAKEVEN -> Holding
The text color changes (red, green, yellow, orange, etc.) to match the situation, so you can read your trade status at a glance.
4. How to use it in practice
Step 1 – Right after entering a trade
Open a position using your own entry strategy (Commander does not give entries).
On the TradingView chart:
Set Position Active? = true
Fill:
Avg Entry Price = your actual entry
Initial Stop Loss = your planned hard stop
Position Size = the size of your position
Adjust:
Trailing Width (xATR):
Lower for tight, short‑term trades (scalp/intraday).
Higher for swing/position trades to avoid premature exits.
Turn Show R-Levels ON if you trade in terms of R.
Now the script will start drawing the Trailing Stop, Safe Zone, R levels, and Dashboard.
Step 2 – While the trade is running
When price moves in your favor:
Track:
Your current R-Multiple
How much Safe Zone you have
Typical logic:
Once you reach ≥ 1R, consider moving your hard stop to breakeven (BE).
Around 2R–3R, consider:
Taking partial profits
Tightening the trailing
Letting the remainder run with the Shield.
When price pulls back:
If price breaks below the Trailing Stop:
Dashboard shows the red warning: TRAILING HIT -> EXIT NOW!
The alert (if enabled) will also fire.
→ This is your disciplined exit condition according to Commander.
When price hovers near entry:
Dashboard shows BREAKEVEN or DRAWDOWN.
You can:
Give the setup more time
Or decide to scratch the trade if it no longer fits your plan
(The key is: you’re deciding based on a clear snapshot, not pure emotion.)
5. Alerts
The script contains one key alert:
XΩ EXIT SIGNAL
Triggers when price crosses under the Trailing Stop.
Message: "Price breached Trailing Stop. Exit position immediately!"
Use this alert to automate your exit discipline: you don’t need to stare at the chart to know when your trailing stop is hit.
