[SHORT ONLY] Internal Bar Strength (IBS) Mean Reversion Strategy

█ STRATEGY DESCRIPTION
The "Internal Bar Strength (IBS) Strategy" is a mean-reversion strategy designed to identify trading opportunities based on the closing price's position within the daily price range. It enters a short position when the IBS indicates overbought conditions and exits when the IBS reaches oversold levels. This strategy is Short-Only and was designed to be used on the Daily timeframe for Stocks and ETFs.

█ WHAT IS INTERNAL BAR STRENGTH (IBS)?
Internal Bar Strength (IBS) measures where the closing price falls within the high-low range of a bar. It is calculated as:

IBS = (Close - Low) / (High - Low)

- Low IBS (≤ 0.2): Indicates the close is near the bar's low, suggesting oversold conditions.
- High IBS (≥ 0.8): Indicates the close is near the bar's high, suggesting overbought conditions.


█ SIGNAL GENERATION
1. SHORT ENTRY
A Short Signal is triggered when:

• The IBS value rises to or above the Upper Threshold (default: 0.9).
  
• The Closing price is greater than the previous bars High (close>high[1]).
  
• The signal occurs within the specified time window (between `Start Time` and `End Time`).
  

2. EXIT CONDITION

• An exit Signal is generated when the IBS value drops to or below the Lower Threshold (default: 0.3). This prompts the strategy to exit the position.
  

█ ADDITIONAL SETTINGS

• Upper Threshold: The IBS level at which the strategy enters trades. Default is 0.9.
  
• Lower Threshold: The IBS level at which the strategy exits short positions. Default is 0.3.
  
• Start Time and End Time: The time window during which the strategy is allowed to execute trades.
  

█ PERFORMANCE OVERVIEW

• This strategy is designed for Stocks and ETFs markets and performs best when prices frequently revert to the mean.
  
• The strategy can be optimized further using additional conditions such as using volume or volatility filters.
  
• It is sensitive to extreme IBS values, which help identify potential reversals.
  
• Backtesting results should be analyzed to optimize the Upper/Lower Thresholds for specific instruments and market conditions.