Improving Moving Average Strategies with Trend Filters
Summary
The document traces several ways to build moving average trading rules, using a 15-minute Chinese rebar futures index as its backtest example. It starts with price crossing a single average and short-period averages crossing longer ones, then adds directional checks on the averages, compares a pair of averages, and describes a three-average alignment rule. It also presents a variant based on differences between exponential moving averages and a smoothed signal, with a price-direction condition.
The examples illustrate how extra trend conditions can filter repeated crossover signals. The author reports that a simple single-average strategy looks promising before trading costs but may perform poorly once slippage and commissions are considered; later variants are described as improving results, though the supporting figures are not included in the text. The document gives no detailed test statistics, parameter search, risk analysis, or evidence that the reported performance generalizes beyond the example market and timeframe. It presents the strategies as starting points for experimentation rather than validated systems.
Key ideas
- A short-period moving average crossing above a longer-period average can serve as a long entry signal, with the reverse crossing used for an exit or short signal.
- A single-average rule treats price as one side of a moving-average comparison and can trigger repeatedly.
- Checking whether averages have risen or fallen over recent periods can filter some crossover signals.
- A difference between fast and slow exponential averages can be compared with a smoothed signal to generate directional trades.
- Three-average alignment extends the same trend-following idea across short, medium, and long horizons.
- Transaction costs can materially reduce the apparent performance of simple moving-average rules.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.