OPEN-SOURCE SCRIPT

Session Liquidity Reversion Strategy (Asia Range False Breakout)

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Overview

This strategy is based on a session-driven liquidity hypothesis rather than a simple indicator combination.

During the Asian trading session, many markets enter a low-liquidity equilibrium, forming a relatively narrow price range. When higher-volume participants enter during the London and New York sessions, price often performs false expansions beyond this Asian range before reverting back toward fair value.

This script systematically identifies and trades those failed session expansions.

Core Concept

The strategy operates in three distinct phases:
Asia Session Range Formation
The high and low of the Asian session are recorded.
This range represents a temporary balance area formed under reduced participation.

Range Locking

Once the Asian session ends, the range is frozen.
No repainting or forward-looking calculations are used.
False Breakout Detection & Reversion

During the London/New York session, price must break beyond the Asia range and fail to hold.
A momentum filter (RSI) confirms rejection strength.
Trades are entered only after price closes back inside the range, targeting reversion rather than continuation.

This approach avoids chasing breakouts and instead focuses on liquidity traps and failed expansions.

Risk Management & Assumptions

Risk parameters are intentionally conservative and realistic:
Position sizing uses percentage of equity
Default risk per trade is approximately 2%
Stop losses are ATR-based, adapting to volatility
Risk-to-reward is fixed and configurable
Realistic commission and slippage are included
One trade per session is allowed to avoid over-exposure
No martingale, grid, or averaging logic is used.


Usage Notes

Recommended timeframes: 5m – 30m
Designed for: Forex, Indices, Crypto
Performance will vary by instrument and session volatility
All parameters are configurable for research and optimization

This strategy is intended for educational and research purposes, demonstrating how session-based liquidity behavior can be tested systematically using Pine Script.

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