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AI EngineeringPython

QMT 内置因子回测

QMT 内置因子回测 is an AI Engineering skill for Claude Code, published by dfkai in xtquantai.

161 stars40 forkson dfkai/xtquantaiAdded 2026/09/08+1% in starsRepository updated 2026/06/11

View source on GitHub Download repo ZIP

agent-skillsclaude-codecursorpythonqmtquantquantitative-tradingxtquant

Install in seconds

Install QMT 内置因子回测

Copy QMT 内置因子回测 into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/dfkai/xtquantai/tree/master/skills/qmt-inner-backtest ~/.claude/skills/qmt-inner-backtest

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/dfkai/xtquantai.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: skills/qmt-inner-backtest/SKILL.md in dfkai/xtquantai
Installs to: ~/.claude/skills/qmt-inner-backtest
Collection: The only skill cataloged from this repository
Category: AI Engineering — 3670 skills

What QMT 内置因子回测 does

QMT 内置因子回测根据策略描述、研报 PDF 或截图，解读因子与选股逻辑，并基于日频回测母版生成 QMT 策略编辑器内置回测脚本。适合截面因子选股、研报复现和 handlebar 调仓信号生成。

QMT 内置因子回测 is cataloged under AI Engineering on DirSkills. QMT 内置因子回测 comes from a repository tagged agent-skills, claude-code, cursor, python and qmt.

Documentation

README

Excerpt

QMT 内置因子回测

概述

基于 scripts/daily-factors-backtest.py 生成 QMT 策略编辑器内置回测 脚本。

核心模式：after_init 预计算全区间因子与买卖信号 → handlebar 按调仓日执行交易。

母版路径：本 skill 目录下的 scripts/daily-factors-backtest.py（相对 SKILL.md 所在目录）

适用场景

适合	不适合
日频截面因子选股（Barra 风格处理）	Tick/分钟高频
固定持仓数 Top-N 等权调仓	期货开平仓（`qmt-future-trade`，规划中）
研报因子复现、上下影线/价值/动量等	目标持仓型期货实盘（`qmt-live-strategy-template`，规划中）
申万行业 + 市值中性化	仅要信号推送（`qmt-live-signal-feishu`，规划中）

母版架构（必须理解再改）

This is the opening of the README. Read the full README on GitHub.

Frequently asked about QMT 内置因子回测

How does QMT 内置因子回测 compare to other AI Engineering skills?
QMT 内置因子回测 ranks #3442 by stars among the 3670 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of QMT 内置因子回测 against them. Open each page to compare what they document and how they install.

More AI Engineering skills

QMT 内置因子回测 is one of 3670 AI Engineering skills cataloged on DirSkills, ranked #3442 by stars among them.

Browse all AI Engineering skills →

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Architecture Decision Records captures architectural decisions made during Claude Code sessions as structured ADRs, recording context, alternatives, and rationale. Use it when significant technical choices are made so future developers understand why the codebase is shaped the way it is.

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AI-First Engineering defines process, review, and architecture standards for teams where AI agents produce most implementation output. Use it to set ownership rules, quality gates, and evaluation criteria for agent-generated code.

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Agentic OS codifies a persistent multi-agent operating system architecture for Claude Code. Use it when building a multi-agent workflow with file-based memory, slash commands, and scheduled automation that survives session restarts.