EasyQuant¶

Event-driven backtesting — initialize → run_daily → handle_data, consistent with JoinQuant / Zipline
Comprehensive A-share data — Daily / minute / tick bars, financial summaries, money flow, northbound capital, limit up/down statistics
Risk analysis — Sharpe / Sortino / Max Drawdown / Alpha & Beta / Brinson attribution
Portfolio risk control — VaR, strategy correlation, concentration risk, Kill Switch circuit breaker
Paper trading + PTrade/QMT adapter — Pre-live verification + one-click export to broker platforms

Minimal Example¶

from eqlib import *

def initialize(context):
    g.security = '601390'
    set_benchmark('000300.XSHG')
    run_daily(market_open, time='every_bar')

def market_open(context):
    hist = attribute_history(g.security, 20, '1d', ['close'])
    ma20 = hist['close'].mean()
    price = hist['close'].iloc[-1]

    if price > ma20 * 1.02:
        order_value(g.security, context.portfolio.available_cash)
    elif price < ma20 * 0.98 and context.portfolio.positions.get(g.security):
        order_target(g.security, 0)

result = run_strategy(
    initialize,
    start_date='2024-01-01',
    end_date='2024-12-31',
    starting_cash=100000,
    securities=['601390'],
)

Order execution model: order* APIs only place orders within the current callback; they are actually filled at the next trading day's opening price to avoid look-ahead bias. See Backtest Execution Model for details.

Report Preview¶

MACD Trend + Volume	Bollinger Band Mean Reversion	Support/Resistance
Results vary with market conditions	Results vary with market conditions	Results vary with market conditions

Info

This documentation is for learning and research purposes only and does not constitute investment advice.