量化交易7-backtrader中支持的指标

先上代码，以下代码描述了，当MACD柱大于0（红柱）且无持仓时满仓买入，当MACD柱小于0（绿柱）且持仓时全部清仓。

import tushare as ts
import pandas as pd

import datetime  # For datetime objects
import os.path  # To manage paths
import sys  # To find out the script name (in argv[0])
# Import the backtrader platform
import backtrader as bt

class TestStrategy(bt.Strategy):
    params = (('p1', 12), ('p2', 26), ('p3', 9))

    def __init__(self):
        self.order = None
        # 获取MACD柱
        self.macdhist = bt.ind.MACDHisto(self.data,
                                         period_me1=self.p.p1,
                                         period_me2=self.p.p2,
                                         period_signal=self.p.p3)

    def next(self):
        pos = self.getposition(data).size
    
        if not self.position:
            # 得到当前的账户价值
            total_value = self.broker.getcash()
            # 1手=100股，满仓买入
            size = int((total_value / 100) / self.datas[0].close[0]) * 100
            # 当MACD柱大于0（红柱）且无持仓时满仓买入
            if self.macdhist > 0:
                print('买入，macdhist->' + ',持仓数量->' + str(pos) + ',买入数量->' + str(size))
                self.order = self.buy(size=size)
        else:
            # 当MACD柱小于0（绿柱）且持仓时全部清仓
            if self.macdhist < 0:
                print('卖出，macdhist->' + ',持仓数量->' + str(pos))
                self.close()

    def log(self, txt, dt=None, doprint=False):
        if True or doprint:
            dt = dt or self.datas[0].datetime.date(0)
            print(f'{dt.isoformat()},{txt}')

    # 记录交易执行情况（可省略，默认不输出结果）
    def notify_order(self, order):
        # 如果order为submitted/accepted,返回空
        if order.status in [order.Submitted, order.Accepted]:
            return
        # 如果order为buy/sell executed,报告价格结果
        if order.status in [order.Completed]:
            if order.isbuy():
                self.log(f'买入:\n价格:{order.executed.price:.2f},\
                成本:{order.executed.value:.2f},\
                数量:{order.executed.size:.2f},\
                手续费:{order.executed.comm:.2f}')
                self.buyprice = order.executed.price
                self.buycomm = order.executed.comm
            else:
                self.log(f'卖出:\n价格：{order.executed.price:.2f},\
                成本: {order.executed.value:.2f},\
                数量:{order.executed.size:.2f},\
                手续费{order.executed.comm:.2f}')
            self.bar_executed = len(self)
            # 如果指令取消/交易失败, 报告结果
        elif order.status in [order.Canceled, order.Margin, order.Rejected]:
            self.log('交易失败')
        self.order = None

    # 记录交易收益情况（可省略，默认不输出结果）
    def notify_trade(self, trade):
        if not trade.isclosed:
            return
        self.log(f'策略收益：\n毛收益 {trade.pnl:.2f}, 净收益 {trade.pnlcomm:.2f}')


if __name__ == '__main__':
    # 加载策略
    cerebro = bt.Cerebro()

    cerebro.addstrategy(TestStrategy)

    dataframe = pd.read_csv('dfqc.csv', index_col=0, parse_dates=True)
    dataframe['openinterest'] = 0
    data = bt.feeds.PandasData(dataname=dataframe,
                               fromdate=datetime.datetime(2006, 8, 18),
                               todate=datetime.datetime(2007, 8, 18)
                               )

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

    # 设置初始资本为10,000
    startcash = 100000
    cerebro.broker.setcash(startcash)
    # 设置交易手续费为 0.1%
    cerebro.broker.setcommission(commission=0.001)
    print('组合期初资金: %.2f' % cerebro.broker.getvalue())
    cerebro.run()
    #获取回测结束后的总资金
    print('组合期末资金: %.2f' % cerebro.broker.getvalue())

    cerebro.plot()

组合期末资金：328495.06 

数据下载地址 

链接：https://pan.baidu.com/s/1nWxz7hQBKIYMozgNHfIBsQ 
提取码：bh1q

以上的代码中使用到了另外股票中另外一个重要的指标MACD指标，MACD的指标获取方式self.macdhist = bt.ind.MACDHisto(self.data, period_me1=self.p.p1, period_me2=self.p.p2, period_signal=self.p.p3)

backtrader所有支持的指标封装在indicators中。打开backtrader安装路径，以Anaconda为例，打开\Lib\site-packages\backtrader\，进入indicators文件夹，可以看到里面有48个py文件，文件名是各个技术指标或公示的简称

 以上是包含了策略的代码，以下是没有策略的代码，只输出了 指标的代码，包括：MACD、BBands、RSI

import tushare as ts
import pandas as pd

import datetime  # For datetime objects
import os.path  # To manage paths
import sys  # To find out the script name (in argv[0])
# Import the backtrader platform
import backtrader as bt

class TestStrategy(bt.Strategy):
    def __init__(self):
        bt.ind.MACD(self.data)
        bt.ind.MACDHisto(self.data)
        bt.ind.RSI(self.data, period=5)
        bt.ind.BBands(self.data)

    def next(self):
        if not self.position:
            print('aaa')

if __name__ == '__main__':
    # 加载策略
    cerebro = bt.Cerebro()

    cerebro.addstrategy(TestStrategy)

    dataframe = pd.read_csv('dfqc.csv', index_col=0, parse_dates=True)
    dataframe['openinterest'] = 0
    data = bt.feeds.PandasData(dataname=dataframe,
                               fromdate=datetime.datetime(2006, 8, 18),
                               todate=datetime.datetime(2007, 8, 18)
                               )
    # Add the Data Feed to Cerebro
    cerebro.adddata(data)

    # 设置初始资本为10,000
    startcash = 100000
    cerebro.broker.setcash(startcash)
    # 设置交易手续费为 0.1%
    cerebro.broker.setcommission(commission=0.001)
    print('组合期初资金: %.2f' % cerebro.broker.getvalue())
    cerebro.run()
    #获取回测结束后的总资金
    print('组合期末资金: %.2f' % cerebro.broker.getvalue())

    cerebro.plot()