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Loveyless / stock-indicator-backtest

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股票量化助手，根据量化策略生成股票收益报告。

43
3
100% credibility
Found Mar 04, 2026 at 43 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
JavaScript
AI Summary

A backtesting tool for simulating periodic stock rotation strategies on A-share market data from CSV files, generating HTML reports with equity curves, drawdowns, and performance metrics.

How It Works

1
📈 Discover the stock strategy tester

You hear about a simple tool that lets you test stock trading ideas on past market data to see how they might perform.

2
💾 Download the tool and data

Grab the free tool and ready-made stock history files from the share site to get started right away.

3
📁 Add your stock files

Drop the stock data files into a special folder so the tool knows what markets to check.

4
▶️ Run your first test

Hit go with the ready example plan, and watch it crunch the numbers on daily, weekly, or longer trades.

5
✏️ Tweak your trading plan

Change the example rules, like moving averages or filters, to match your own stock picking ideas.

6
📊 View your colorful results

Open the new webpage report full of charts showing growth curves, risks, win rates, and trade details.

🎉 Master your strategy

Celebrate understanding exactly how your stock ideas performed over time, ready to refine and try more.

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Star Growth

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AI-Generated Review

What is stock-indicator-backtest?

This JavaScript tool handles stock indicator backtesting for A-shares: drop CSV files with stock data into a folder, tweak a strategy using built-in indicators like moving averages, and run periodic trades on daily, weekly, monthly, or quarterly cycles. It spits out an HTML report with equity curves, drawdowns, win rates, and trade logs—idealized long-only simulation without halts or lot restrictions. No strategy coding needed to start; a working example runs out of the box via simple CLI commands like `pnpm start -- --freq=W`.

Why is it gaining traction?

It skips heavy frameworks for lightweight Node.js CLI runs, delivering visual reports in seconds versus building custom backtests from scratch. Customizable flags for dates, fees, limits, and even strategy params via JSON make iteration fast, while bilingual docs cover data prep and pitfalls like lookahead bias. For stock backtesting in JavaScript, it's a low-friction alternative to Python libs bloated with extras.

Who should use this?

Quant hobbyists testing A-share rotation strategies on CSV data, JS developers exploring stock indicators without switching languages, or traders prototyping multi-period backtests before coding full platforms. Skip if you need short-selling, slippage models, or massive universes.

Verdict

Grab it for quick stock indicator backtesting prototypes—solid docs and CLI make 43 stars and 1.0% credibility score forgivable for an early project. Not production-ready yet; lacks tests and realism for live trading.

(187 words)

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