Backtrader：用最简单策略回测

翻译自： Quickstart Guide - Backtrader

原文数据无法下载，对代码进行部分修改以获取tushare股票数据。

运行结果：

期初资金: 100000.00
2020-02-03, Close, 4.68
2020-02-04, Close, 4.51
2020-02-05, Close, 4.57
2020-02-06, Close, 4.61
2020-02-07, Close, 4.70
2020-02-10, Close, 4.71
2020-02-11, Close, 4.78
2020-02-12, Close, 4.85
2020-02-13, Close, 4.76
2020-02-14, Close, 4.74
2020-02-14, 买入单, 4.74
2020-02-17, 已买入, 价格: 4.75, 费用: 4.75, 佣金 0.00
2020-02-17, Close, 4.88
2020-02-18, Close, 4.89
2020-02-19, Close, 4.86
2020-02-20, Close, 4.92
2020-02-21, Close, 4.90
2020-02-24, Close, 4.77
2020-02-24, 卖出单, 4.77
2020-02-25, 已卖出, 价格: 4.65, 费用: 4.75, 佣金 0.00
2020-02-25, 交易利润, 毛利润 -0.10, 净利润 -0.11
......
2020-03-16, Close, 4.56
2020-03-17, Close, 4.51
2020-03-17, 卖出单, 4.51
2020-03-18, 已卖出, 价格: 4.49, 费用: 4.61, 佣金 0.00
2020-03-18, 交易利润, 毛利润 -0.12, 净利润 -0.13
2020-03-18, Close, 4.40
2020-03-18, 买入单, 4.40
2020-03-19, 已买入, 价格: 4.40, 费用: 4.40, 佣金 0.00
2020-03-19, Close, 4.34
2020-03-20, Close, 4.43
2020-03-23, Close, 4.26
2020-03-24, Close, 4.30
2020-03-25, Close, 4.44
2020-03-26, Close, 4.47
2020-03-26, 卖出单, 4.47
2020-03-27, 已卖出, 价格: 4.49, 费用: 4.40, 佣金 0.00
2020-03-27, 交易利润, 毛利润 0.09, 净利润 0.08
2020-03-27, Close, 4.48
2020-03-30, Close, 4.44
2020-03-31, Close, 4.48
期末资金: 100000.04

# -*- coding: utf-8 -*-
"""
Created on Sat Feb  5 17:37:50 2022

"""

from __future__ import (absolute_import, division, print_function,
                        unicode_literals)
from datetime import datetime  # For datetime objects
# Import the backtrader platform
import backtrader as bt
import pandas as pd
import tushare as ts

# 创建策略继承bt.Strategy
class TestStrategy(bt.Strategy):

    def log(self, txt, dt=None):
        # 记录策略的执行日志
        dt = dt or self.datas[0].datetime.date(0)
        print('%s, %s' % (dt.isoformat(), txt))

    def __init__(self):
        # 保持对收盘价的引用
        self.dataclose = self.datas[0].close
		
        # 跟踪挂单
        self.order = None
        # 买入价格和手续费
        self.buyprice = None
        self.buycomm = None

    # 订单状态通知，买入卖出都是下单
    def notify_order(self, order):
        if order.status in [order.Submitted, order.Accepted]:
            # broker 提交/接受了，买/卖订单则什么都不做
            return

        # 检查一个订单是否完成
        # 注意: 当资金不足时，broker会拒绝订单
        if order.status in [order.Completed]:
            if order.isbuy():
                self.log(
                    '已买入, 价格: %.2f, 费用: %.2f, 佣金 %.2f' %
                    (order.executed.price,
                     order.executed.value,
                     order.executed.comm))

                self.buyprice = order.executed.price
                self.buycomm = order.executed.comm
            elif order.issell():
                self.log('已卖出, 价格: %.2f, 费用: %.2f, 佣金 %.2f' %
                         (order.executed.price,
                          order.executed.value,
                          order.executed.comm))
            # 记录当前交易数量
            self.bar_executed = len(self)

        elif order.status in [order.Canceled, order.Margin, order.Rejected]:
            self.log('订单取消/保证金不足/拒绝')

        # 其他状态记录为：无挂起订单
        self.order = None

    # 交易状态通知，一买一卖算交易
    def notify_trade(self, trade):
        if not trade.isclosed:
            return
        self.log('交易利润, 毛利润 %.2f, 净利润 %.2f' %
                 (trade.pnl, trade.pnlcomm))

    def next(self):
        # 记录收盘价
        self.log('Close, %.2f' % self.dataclose[0])

        # 如果有订单正在挂起，不操作
        if self.order:
            return

        # 如果没有持仓则买入
        if not self.position:
            # 今天的收盘价 < 昨天收盘价 
            if self.dataclose[0] < self.dataclose[-1]:
                # 昨天收盘价 < 前天的收盘价
                if self.dataclose[-1] < self.dataclose[-2]:
                    # 买入
                    self.log('买入单, %.2f' % self.dataclose[0])
                     # 跟踪订单避免重复
                    self.order = self.buy()
        else:
            # 如果已经持仓，且当前交易数据量在买入后5个单位后
            if len(self) >= (self.bar_executed + 5):
                # 全部卖出
                self.log('卖出单, %.2f' % self.dataclose[0])
                # 跟踪订单避免重复
                self.order = self.sell()

        

def get_data(code,start='2010-01-01',end='2020-03-31'):
    df=ts.get_k_data(code,autype='qfq',start=start,end=end)
    df.index=pd.to_datetime(df.date)
    df['openinterest']=0
    df=df[['open','high','low','close','volume','openinterest']]
    return df

dataframe=get_data('600018')

start=datetime(2020, 1, 31)
end=datetime(2021, 3, 31)

if __name__ == '__main__':
	
    # 初始化cerebro回测系统设置
    cerebro = bt.Cerebro()

    # 取得股票历史数据
    data = bt.feeds.PandasData(dataname=dataframe, fromdate=start, todate=end)
	
    # 为Cerebro引擎添加策略
    cerebro.addstrategy(TestStrategy)
    # 加载交易数据
    cerebro.adddata(data)
	
	# 设置投资金额
    cerebro.broker.setcash(100000.0)
    # 设置佣金为0.001,除以100去掉%号
    cerebro.broker.setcommission(commission=0.001)
	
    #获取回测开始时的总资金
    print('期初资金: %.2f' % cerebro.broker.getvalue())
    #运行回测系统
    cerebro.run()
    #获取回测结束后的总资金
    print('期末资金: %.2f' % cerebro.broker.getvalue())

标签：02,03,策略,Backtrader,self,回测,2020,Close,order
来源： https://blog.csdn.net/bq_cui/article/details/122807807