Wave Signals with Dynamic Sizing and Multi-Timeframe Risk Filters
Summary
This strategy combines Wave Theory crossovers with moving average, MACD, and volatility filters to trade in the direction of a broader trend. A long signal occurs when WT1 crosses above WT2 below zero, and a short signal when it crosses below above zero. The strategy also checks 15- and 30-minute MACD histograms, price relative to 70- and 140-period averages, distance from the slower average, and extension from the faster average. Bollinger Band zones determine whether position size is full or reduced.
Trades are split so that 65% of the position targets a partial profit and the remainder can continue toward a final target; after partial profit, the runner’s stop moves to entry. Stops use a 1.7-standard-deviation band, with a maximum permitted loss, and an opposite-signal cooldown limits reversals. The document gives backtest settings but no performance results or detailed validation. It says the approach suits trending markets better than sideways ones, and its reported backtest claims should not be treated as evidence of future returns.
Key ideas
- Wave Theory crossovers provide entries when they occur on the specified side of zero.
- MACD histograms on two shorter timeframes and moving averages filter trades by direction.
- Bollinger Band zones scale position size, while a maximum stop distance can exclude trades.
- Partial profit taking leaves a smaller runner whose stop moves to entry after the first target.
- A cooldown and an ATR-based extension filter aim to reduce churn and late entries.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.