pyBacktest 1.1.4

A backtesting framework for stock price prediction strategies

Stock Trading Backtest Framework

A Python framework for backtesting trading strategies with support for multiple order types and technical indicators.

Features

Trading Operations

• Market Orders (Buy/Sell)
• Limit Orders
• GTC (Good Till Cancelled) Orders
• Short
• Commission Handling
  • Flat Fee
  • Percentage
  • Per Share

Technical Indicators

• Simple Moving Average (SMA)
• Exponential Moving Average (EMA)
• Relative Strength Index (RSI)
• Bollinger Bands
• MACD (Moving Average Convergence Divergence)
• Crossover Detection
• Volume Weighted Average Price (VWAP)
• Average True Range (ATR)

Portfolio Management

• Position Tracking
• Transaction History
• Portfolio Valuation
• Cash Management
• Performance Metrics

Example

import pyBacktest as pbt
from pyBacktest.strategy import Strategy
from pyBacktest.utils import calculateSMA, detectCrossover
from pyBacktest.tradeTypes import TradeType, InsufficientFundsError, InsufficientSharesError, ShortPositionError
from datetime import datetime
import pandas as pd

class SimpleMovingAverageCrossover(Strategy):
    def setup(self) -> None:
        self.sma20: pd.Series = calculateSMA(self.data['Close'], 20)
        self.sma50: pd.Series = calculateSMA(self.data['Close'], 50)

    def maxBuyableShares(self, price: float, cash: float) -> int:
        numShares = 0
        while True:
            commission = self.backtest.calculateCommision(price, numShares + 1)
            total_cost_per_share = price + (commission / (numShares + 1))
            if cash >= total_cost_per_share * (numShares + 1):
                numShares += 1
            else:
                break
        return numShares
    
    def next(self, row: pd.Series) -> None:
        if len(self.data['Close']) < 51:
            return

        current_price: float = row['Close']
        current_sma20: float = self.sma20[row.name]
        current_sma50: float = self.sma50[row.name]
        position: int = self.get_position()

        try:
            if current_sma20 > current_sma50:
                numShares = self.maxBuyableShares(current_price, self.backtest.cash)
                if numShares > 0:
                    self.backtest.trade(TradeType.MARKET_BUY, numShares)
            elif current_sma20 < current_sma50 and position > 0:
                sharesToSell = max(1, position // 3)
                self.backtest.trade(TradeType.MARKET_SELL, sharesToSell)
        except InsufficientFundsError as e:
            print("Insufficient funds to execute trade")
            

if __name__ == "__main__":
    backtest = pbt.Backtest(
        "NVDA",
        10000.0,
        strategy=SimpleMovingAverageCrossover(),
        commision=0.0,
        commisionType="FLAT",
        startDate=datetime(2020, 1, 1),
        endDate=datetime(2024, 1, 1)
    )
    results = backtest.run()
    print(f"Final Portfolio Value: ${results['final_value']:,.2f}")