A Multi-Timeframe Bollinger Strategy and Its Iterative Backtest Refinement

Summary

The author recounts developing a daily-oriented spot strategy for ETH and proposes a three-timeframe framework: a slower chart sets market direction, a middle timeframe guides trades, and a faster chart signals when a move may be ending. Each timeframe is classified by its relationship to Bollinger Bands, creating combinations that could be assigned entry and exit rules. The author later simplifies the framework and adds rules involving bearish conditions, a five-day moving average, sharp moves beyond the bands, and exits when the trade rationale breaks. A market “heat” measure changes the jump parameters, while a panic threshold can trigger adding or selling around prior highs and lows.

The article reports differing backtest results across iterations, including a final stated annualized return of 210 and drawdown of 16.4%, and notes that much of the gain occurred during the rising first half of 2019. It offers no independent validation or detailed test assumptions. The strategy is long-only spot, so its conclusions may not transfer to other periods, instruments, or short-selling systems.

Key ideas

• The proposed framework uses a slow timeframe for direction, a middle timeframe for trade decisions, and a fast timeframe for exit signals.
• Bollinger Band relationships across three timeframes form a set of market states that can be mapped to trading rules.
• The author refined the strategy by adding bearish exits, moving-average direction, sharp-drop handling, and conditional stop or profit-taking rules.
• The reported backtest outcomes varied across iterations, and the author links performance to the rising market in early 2019.
• The strategy is spot-only and long-only, and the article does not establish that its backtest results will generalize.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.