Building an ADX Trend-Following Strategy from Natural-Language Rules
Summary
The article presents a workflow for translating a written trading specification into a QMT strategy. Its example applies ADX and directional indicators to one Chinese-listed equity: buy when ADX exceeds a threshold and positive directional movement is stronger, then exit when ADX falls below the threshold or negative directional movement takes over. It specifies daily evaluation, a lookback for price data, and full-position entry and exit rules.
The author says a tool converts the description into Python code, which is then imported into QMT and backtested. The document supplies no code, backtest statistics, comparison, or details about dates, transaction costs, slippage, position sizing beyond all-in trading, or risk controls. It therefore illustrates how to make strategy requirements explicit and translate them into a platform workflow, but it does not establish that the example is profitable or robust. The rules and thresholds are an example rather than a validated recommendation.
Key ideas
- A strategy specification should state its instrument, parameters, data needs, signals, and order actions.
- The example enters when ADX indicates trend strength and positive directional movement exceeds negative movement.
- It exits when trend strength weakens below the selected threshold or directional movement turns negative.
- The article describes natural-language conversion to code followed by a QMT backtest, but reports no performance evidence.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.