gridtrader
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Grid-trading strategy development & backtesting toolset (Python / backtrader): A-share daily-K via baostock, CSV-driven grid backtests, Pipenv-managed. | 网格交易策略开发及回测工具:baostock 拉 A 股日 K、CSV 驱动网格回测、Pipenv 管理依赖。
gridtrader — Grid-Trading Strategy Toolset
🌐 简体中文
gridtrader is a grid-trading strategy development and backtesting toolset built on backtrader: it fetches A-share daily-K data via baostock (get_data_scripts/get_data.py), runs grid backtests from CSV data (main.py's gridrun() plus the GridStrategy in gridtrader.py), and ships sample datasets under data/ (CSI 300 index, a single A-share, and a segmented Binance series). Dependencies are managed with Pipenv.
A sub-project of QuantStrategistAgent (Markowitz), the quant-strategy agent of the xhqing AI agent team. Research tooling only: not for live trading, not financial advice.
How it works
GridStrategy derives a mid price from the highest/lowest range of the past 1440 bars and builds 11 price levels spaced 0.5% apart across ±2.5% around that mid. Each level maps to a target position (lightest at the top, fully invested at the bottom); whenever the close crosses a level, the strategy re-balances to that level's target — classic grid logic (buy the dips, sell the rips), implemented with order_target_percent.
Quick start
Requires Python (the project declares 3.7) and Pipenv:
pip install pipenv
pipenv install
pipenv run python main.py
All settings live in the __main__ block of main.py:
filename— input CSV path (default./data/binance-segment.csv);timeframe— the data's backtrader timeframe (defaultMinutes; the dict maps index → name);all_cash— starting cash (default100000.00).
The CSV must have exactly the columns ['time', 'open', 'high', 'low', 'close', 'volume'] in that order (pandas CSV format, time parsed as datetimes).
The run prints the starting and final portfolio value.
Repository layout
gridtrader/
├── main.py # Backtest entry: gridrun() + all settings
├── gridtrader.py # GridStrategy (the backtrader strategy) implementation
├── get_data_scripts/
│ └── get_data.py # Sample A-share daily-K fetcher (baostock)
├── data/ # Sample datasets (CSV): CSI 300, one A-share, segmented Binance
├── Pipfile / Pipfile.lock # Dependencies (pandas / backtrader / baostock)
└── .claude/skills/quant/ # Quant skill (superset copy from QuantStrategistAgent)
License & attribution
This project is released under the MIT License, and you are additionally asked to credit the author and cite the source whenever you use, redistribute, or build upon it:
- Author: All Contributors
- Project: gridtrader — grid-trading strategy development & backtesting toolset (QuantStrategistAgent sub-project)
- Main repository: https://github.com/xhqing/QuantStrategistAgent
If you reference code or derive from this repository, please retain this attribution in your documentation, README, or acknowledgements.
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