backtrader 简单双均线策略

策略的主要行为：
1） 初始化5日均线以及20日均线，sma5， sma20
2) sma5上穿sma20买入
3） sma5 下穿sma20卖出

策略绩效：

Starting Portfolio Value: 100000.00
Final Portfolio Value: 99796.00

# 简单用双均线，测试一下
from __future__ import (absolute_import, division, print_function,
                        unicode_literals)

import time

from backtest.tool import *
import backtrader as bt

# Create a Stratey
class TestStrategy(bt.Strategy):
    params = (
        ('period_low', 5),
        ('period_high', 20),
    )

    def log(self, txt, dt=None):
        ''' Logging function for this strategy'''
        dt = dt or self.datas[0].datetime.date(0)
        print('%s, %s' % (dt.isoformat(), txt))

    def __init__(self):
        self.sma_low = bt.indicators.SimpleMovingAverage(self.datas[0].close, period=self.params.period_low)
        self.sma_high = bt.indicators.SimpleMovingAverage(self.datas[0].close, period=self.params.period_high)
        self.sell_sig = self.sma_high > self.sma_low
        self.buy_sig = self.sma_high < self.sma_low
        self.last_sig = False #上一次信号是买或者是卖， False表示上一次是卖
    def next(self):
        if self.sell_sig[0] and self.last_sig :
            self.sell()
            self.last_sig = False

        if self.buy_sig[0] and not self.last_sig:
            self.buy()
            self.last_sig = True



if __name__ == '__main__':
    # Create a cerebro entity
    cerebro = bt.Cerebro()

    # Add a strategy
    cerebro.addstrategy(TestStrategy)

    df = load_data_from_csv("000001.SZ")
    # 加载数据
    data = bt.feeds.PandasData(dataname=df, fromdate=pd.to_datetime("20100101", format='%Y%m%d'),
                               todate=pd.to_datetime("20241201", format='%Y%m%d'))

    # Add the Data Feed to Cerebro
    cerebro.adddata(data)

    # Set our desired cash start
    cerebro.broker.setcash(100000.0)

    # Print out the starting conditions
    print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())

    # Run over everything
    cerebro.run()

    # Print out the final result
    print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())

---

增加买卖的监控信号：notify_order / notify_trader

# 简单用双均线，测试一下
from __future__ import (absolute_import, division, print_function,
                        unicode_literals)

import time

from backtest.tool import *
import backtrader as bt


# Create a Stratey
class TestStrategy(bt.Strategy):
    params = (
        ('period_low', 5),
        ('period_high', 20),
    )

    def log(self, txt, dt=None):
        ''' Logging function for this strategy'''
        dt = dt or self.datas[0].datetime.date(0)
        print('%s, %s' % (dt.isoformat(), txt))

    def __init__(self):
        self.sma_low = bt.indicators.SimpleMovingAverage(self.datas[0].close, period=self.params.period_low)
        self.sma_high = bt.indicators.SimpleMovingAverage(self.datas[0].close, period=self.params.period_high)
        self.sell_sig = self.sma_high > self.sma_low
        self.buy_sig = self.sma_high < self.sma_low
        self.last_sig = False  # 上一次信号是买或者是卖， False表示上一次是卖

    def next(self):
        if self.sell_sig[0] and self.last_sig:
            self.sell()
            self.last_sig = False

        if self.buy_sig[0] and not self.last_sig:
            self.buy()
            self.last_sig = True
    def notify_order(self, order):
        if order.status in [order.Submitted, order.Accepted]:
            # Buy/Sell order submitted/accepted to/by broker - Nothing to do
            return

        # Check if an order has been completed
        # Attention: broker could reject order if not enough cash
        if order.status in [order.Completed]:
            if order.isbuy():
                self.log(
                    'BUY EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %
                    (order.executed.price,
                     order.executed.value,
                     order.executed.comm))
            else:  # Sell
                self.log('SELL EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %
                         (order.executed.price,
                          order.executed.value,
                          order.executed.comm))
        elif order.status in [order.Canceled, order.Margin, order.Rejected]:
            self.log('Order Canceled/Margin/Rejected')

    def notify_trade(self, trade):
        if not trade.isclosed:
            return

        self.log('OPERATION PROFIT, GROSS %.2f, NET %.2f' % (trade.pnl, trade.pnlcomm))


if __name__ == '__main__':
    # Create a cerebro entity
    cerebro = bt.Cerebro()

    # Add a strategy
    cerebro.addstrategy(TestStrategy)

    df = load_data_from_csv("000001.SZ")
    # 加载数据
    data = bt.feeds.PandasData(dataname=df, fromdate=pd.to_datetime("20100101", format='%Y%m%d'),
                               todate=pd.to_datetime("20241201", format='%Y%m%d'))

    # Add the Data Feed to Cerebro
    cerebro.adddata(data)

    # Set our desired cash start
    cerebro.broker.setcash(100000.0)

    # Print out the starting conditions
    print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())

    # Run over everything
    cerebro.run()

    # Print out the final result
    print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())