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Using ChatGPT and Editor Tools to Build and Validate Trading Code

Article FMZ digest · Author: 发明者量化-小小梦
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Summary

This article presents FMZ's editor integration with ChatGPT as a way to help users design, explain, and refine quantitative trading code. Its worked example asks for a JavaScript function that aggregates one-minute market bars into bars of a chosen minute interval, aligning intervals that divide an hour to the hour boundary. The article emphasizes writing a precise prompt that specifies the platform API, input data fields, language, function requirements, and a plotting method.

The generated aggregation is compared visually with the platform's five-minute backtest chart, which the author says appears consistent. This is a limited visual check on one example, not a broad validation across missing bars, irregular timestamps, or other intervals. The article also surveys editor features for renaming symbols, formatting, navigating definitions and references, and viewing code previews. It offers a practical coding workflow, while providing no evidence that ChatGPT-generated code is reliable without independent review and testing.

Key ideas

  • Detailed prompts that specify data structures, platform APIs, and expected output can improve generated code.
  • The example aggregates minute bars by interval, combining open, high, low, close, and volume fields.
  • The article visually compares generated five-minute bars with a platform backtest chart as a basic check.
  • Visual agreement in one example does not establish correctness for irregular or incomplete data.
  • Editor navigation, formatting, and symbol tools can support code review and maintenance.

Tags

CryptoBacktestingStatistics

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