Scalping Bots: Bracket Orders, Stops, and Execution Risks
Summary
The post sketches a short-horizon futures mean-reversion scalper built around symmetric bracket limit orders. It models the strategy as a state machine: after an entry fills, the bot protects the position with a stop while retaining a profit-taking order, then cancels the remaining order after either exit and resets. It also identifies operational controls such as soft and hard daily close times, volatility filters, daily loss limits, tick-size constraints, and avoiding futures rolls.
The author discusses the variables that determine outcomes, including bracket width, stop distance, position size, volatility, price autocorrelation, fees, and fill assumptions. The later analysis compares horizons and parameter choices, emphasizing how tight stops can leave only a few ticks between orders and make results highly sensitive to execution. The post concludes that slower horizons with tighter stops appear preferable in the described analysis, but the author reports that the approach ultimately did not work. Its discussion is exploratory, and profitability depends on realistic costs, passive fills, and robust handling of asynchronous order events.
Key ideas
- A bracket-order scalper can be represented as states that track entry, protection, profit-taking, and cancellation.
- Fast mean reversion can have negative skew and requires careful management of drawdowns.
- Trading costs and fill assumptions strongly affect short-horizon strategy results.
- Tick size constrains feasible stop and target distances, especially at short horizons.
- The author reports that the proposed scalping approach ultimately failed.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.