Multi-Filter Regime, Liquidity, Structure, and Trigger Strategy
Summary
This strategy combines several price-based filters to qualify long and short entries. It defines market regime from the relationship between fast and slow EMA/HMA averages, scales their separation by ATR, and requires both minimum strength and persistence. A volume-based liquidity estimate groups recent bars into price bins, while pivot levels, a slow EMA, and swing ranges describe market structure.
Entries require aligned regime, liquidity, and structure conditions plus at least one trigger: a gap across bars, a momentum and RSI displacement shift, or a pullback continuation setup. Risk controls set an ATR-based stop and two reward targets, with an option to trail in a strong regime; the script also plots a dashboard and uses fixed commission and slippage assumptions for its strategy configuration. The supplied excerpt omits part of the execution logic and gives no performance results, so it does not establish profitability. Its volume-bin bias classifies whole bars by candle direction and should not be mistaken for order-flow data.
Key ideas
- Regime direction comes from fast and slow smoothed price averages, while ATR-normalized spread, range position, and persistence determine regime maturity.
- Recent volume is aggregated into price bins and split by whether each candle closed up or down to estimate directional liquidity bias.
- Pivot and swing comparisons, along with the slow EMA, form a separate structure filter for entries.
- Gap, momentum-shift, and continuation triggers can each activate a trade when the broader context agrees.
- Stops are ATR-based, profit targets use risk multiples, and strong regimes can optionally use trailing risk management.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.