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Bull, Bear, and Range Trading with Multi-Timeframe Breakouts

Article Strategy library · Author: 区班量化
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Summary

This ETH futures strategy classifies market conditions using highs and lows from daily and 30-minute windows. A breakout of the shorter window’s high or low beyond the corresponding daily level signals a bullish or bearish state; when both sides break, the relative centers of the ranges are used to distinguish direction from a less directional market. The strategy then changes its trading behavior: it adds long exposure in a bull state, short exposure in a bear state, and is intended to trade both sides in a range state. Entries are staged relative to the last operating price, and the code caps exposure using account equity.

The article motivates short positions as a way to address falling markets, and gives parameters for polling interval, initial allocation, and lookback windows. It notes that contract sizing depends on the exchange’s ETH contract denomination and that same-direction positions may be combined by the platform. The published backtest covers ETH/USDT on OKEx from January through October 2019, but the document supplies no measured results. The range-trading function is commented out in the code, and the trend classification and exposure logic rely on fixed thresholds and platform-specific assumptions.

Key ideas

  • The strategy classifies conditions by comparing recent 30-minute highs and lows with daily highs and lows.
  • It uses breakout direction and relative range centers to distinguish bull, bear, and less directional states.
  • Bull and bear states trigger staged entries in the corresponding direction, while range trading is intended but disabled in the supplied code.
  • The implementation uses leverage and exposure limits, and contract sizing depends on the exchange’s contract denomination.
  • The article provides a historical ETH futures backtest window but no performance results, and its fixed thresholds may not generalize.

Tags

FuturesCryptoBreakoutTrend followingPosition sizingBacktesting

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