rqalpha

RQAlpha (Ricequant open-source backtesting framework)

RQAlpha is Ricequant Technology developed open-source event-driven backtesting framework. Provides a complete solution for strategy development, backtesting, and simulated trading in the A-share and futures markets. Highly modular, supports extension through the plugin (Mod) system.

Documentation:https://rqalpha.readthedocs.io

Installation

pip install rqalpha

# 下载内置数据包（A股日线数据）
rqalpha download-bundle

# 验证安装
python -c "import rqalpha; print(rqalpha.__version__)"

Strategy Structure

from rqalpha.api import *  # 导入所有 API 函数（含 logger）

def init(context):
    """策略启动时调用一次 — 设置订阅和参数"""
    context.stock = '000001.XSHE'
    context.fired = False

def handle_bar(context, bar_dict):
    """每根K线调用 — 主要交易逻辑"""
    if not context.fired:
        order_shares(context.stock, 1000)
        context.fired = True
        logger.info('买入完成')  # logger 通过 from rqalpha.api import * 自动可用

def before_trading(context):
    """每个交易日开盘前调用"""
    pass

def after_trading(context):
    """每个交易日收盘后调用"""
    pass

Note：from rqalpha.api import * will automatically import logger, you can directly use logger.info()、logger.warn()、logger.error() to output logs.

Run Backtest

Command Line

rqalpha run \
    -f strategy.py \
    -s 2024-01-01 \
    -e 2024-06-30 \
    --account stock 100000 \
    --benchmark 000300.XSHG \
    --plot

Python API

from rqalpha.api import *
from rqalpha import run_func

config = {
    "base": {
        "start_date": "2024-01-01",
        "end_date": "2024-06-30",
        "accounts": {"stock": 100000},
        "benchmark": "000300.XSHG",
        "frequency": "1d",
    },
    "extra": {
        "log_level": "warning",
    },
    "mod": {
        "sys_analyser": {"enabled": True, "plot": True},
    },
}

result = run_func(init=init, handle_bar=handle_bar, config=config)
print(result)

---

Code Format

Market	Suffix	Example
Shanghai A-shares	.XSHG	600000.XSHG(Shanghai Pudong Development Bank)
Shenzhen A-shares	.XSHE	000001.XSHE(Ping An Bank)
Index	.XSHG/.XSHE	000300.XSHG(CSI 300)
Futures	.XSGE/.XDCE/.XZCE/.CCFX	IF2401.CCFX(CSI 300 Futures)

---

Order Functions

Stock Orders

# 按股数买卖
order_shares('000001.XSHE', 1000)       # 买入1000股
order_shares('000001.XSHE', -500)       # 卖出500股

# 按手买入（1手=100股）
order_lots('000001.XSHE', 10)           # 买入10手（1000股）

# 按金额买入
order_value('000001.XSHE', 50000)       # 买入5万元

# 按组合比例买入
order_percent('000001.XSHE', 0.5)       # 买入组合值50%的仓位

# 目标仓位
order_target_value('000001.XSHE', 100000)   # 调整到10万元
order_target_percent('000001.XSHE', 0.3)    # 调整到组合的30%

# 撤单
cancel_order(order_id)

Futures Orders

# 开仓
buy_open('IF2401.CCFX', 1)              # 买入开多1手
sell_open('IF2401.CCFX', 1)             # 卖出开空1手

# 平仓
sell_close('IF2401.CCFX', 1)            # 卖出平多1手
buy_close('IF2401.CCFX', 1)             # 买入平空1手

Data Query Functions

def handle_bar(context, bar_dict):
    # 当前K线数据
    bar = bar_dict['000001.XSHE']
    price = bar.close
    volume = bar.volume
    dt = bar.datetime

    # 历史数据（返回DataFrame）
    prices = history_bars('000001.XSHE', bar_count=20, frequency='1d',
                          fields=['close', 'volume', 'open', 'high', 'low'])

    # 检查股票是否可交易
    tradable = is_valid_price(bar.close)

    # 检查是否停牌
    suspended = is_suspended('000001.XSHE')

Portfolio and Positions

def handle_bar(context, bar_dict):
    # 组合信息
    cash = context.portfolio.cash                    # 可用资金
    total = context.portfolio.total_value            # 总资产
    market_value = context.portfolio.market_value    # 持仓市值
    pnl = context.portfolio.pnl                      # 总盈亏
    returns = context.portfolio.daily_returns        # 日收益率

    # 持仓信息
    positions = context.portfolio.positions
    for stock, pos in positions.items():
        print(f'{stock}: quantity={pos.quantity}, '
              f'sellable={pos.sellable}, '
              f'avg_price={pos.avg_price:.2f}, '
              f'market_value={pos.market_value:.2f}, '
              f'pnl={pos.pnl:.2f}')

Scheduled Scheduling

from rqalpha.api import *

def init(context):
    # 每个交易日指定时间运行函数
    scheduler.run_daily(rebalance, time_rule=market_open(minute=5))
    # 每周运行（每周一）
    scheduler.run_weekly(weekly_task, tradingday=1, time_rule=market_open(minute=5))
    # 每月运行（首个交易日）
    scheduler.run_monthly(monthly_task, tradingday=1, time_rule=market_open(minute=5))

def rebalance(context, bar_dict):
    pass

---

Mod System (Plugins)

RQAlpha's modular architecture allows functionality to be extended through Mods:

config = {
    "mod": {
        "sys_analyser": {
            "enabled": True,
            "plot": True,
            "benchmark": "000300.XSHG",
        },
        "sys_simulation": {
            "enabled": True,
            "matching_type": "current_bar",    # 撮合方式：current_bar（当前Bar）或 next_bar（下一Bar）
            "slippage": 0.01,                  # 滑点（元）
        },
        "sys_transaction_cost": {
            "enabled": True,
            "commission_rate": 0.0003,         # 手续费率
            "tax_rate": 0.001,                 # 印花税（仅卖出）
            "min_commission": 5,               # 最低手续费
        },
    },
}

Available Built-in Mods

Mod	Description
sys_analyser	Performance analysis and chart plotting
sys_simulation	Matching simulation
sys_transaction_cost	Commission and tax calculation
sys_accounts	Account management
sys_benchmark	Benchmark tracking
sys_progress	Progress bar display
sys_risk	Risk management checks

---

Advanced Examples

For more complete strategy examples (dual moving average, multi-stock equal weight, RSI mean reversion, stop loss and take profit, futures CTA), see references/advanced-strategies.md。

Performance Analysis Output

After running the backtest, thesys_analyser Mod will output the following metrics:

Metric	Description
total_returns	Total Return
annualized_returns	Annualized Return
benchmark_total_returns	Benchmark Total Return
alpha	Alpha
beta	Beta
sharpe	Sharpe Ratio
sortino	Sortino Ratio
max_drawdown	Maximum Drawdown
tracking_error	Tracking Error
information_ratio	Information Ratio
volatility	Volatility

Common Error Handling

Error	Cause	Solution
Bundle not found	Data bundle not downloaded	Run rqalpha download-bundle
Insufficient cash	Insufficient available funds	Check context.portfolio.cash
Order Creation Failed: suspended	Stock suspended	Use is_suspended() to check in advance
No data for instrument	Incorrect stock code	Check the code format (e.g. .XSHG / .XSHE）
logger is not defined	API not imported	Ensure from rqalpha.api import * is at the top of the file

Usage Tips

• RQAlpha is a purely local framework with no cloud dependency, suitable for offline research.
• Use rqalpha download-bundle to get free built-in A-share daily data.
• The Mod system allows inserting custom data sources, broker interfaces, and risk control modules.
• Live trading can connect to vn.py's broker gateway via rqalpha-mod-vnpy .
• Supports daily and minute-level backtesting.
• Documentation:https://rqalpha.readthedocs.io/

Resource Index

• references/advanced-strategies.md — Complete strategy examples (dual moving average, multi-stock equal weight, RSI mean reversion, stop loss and take profit, futures CTA). Read when you need to reference advanced strategy implementations.

Rules

• Before using this Skill, confirm that the user explicitly needs the rqalpha framework for strategy backtesting. If the user only needs data acquisition, guide them to use data Skills such as baostock/pywencai.
• The top of the strategy file must include from rqalpha.api import *, to ensure that all order functions and logger are available.
• Futures strategies must use buy_open/sell_open/buy_close/sell_close, and cannot use stock functions such as order_shares .
• Before placing an order, use is_suspended() to check the suspension status, to avoid order failure.
• Stock codes must have a suffix (.XSHG/.XSHE/.CCFX , etc.), and pure numeric codes cannot be used.