BackTrader 中文文档（二十五）（3）https://developer.aliyun.com/article/1505459
MultiTrades
原文：
www.backtrader.com/blog/posts/2015-10-05-multitrades/multitrades/
现在可以为每笔交易添加唯一标识符，即使在相同数据上运行。
根据Tick Data and Resampling的请求，在backtrader的 1.1.12.88 版本中支持“MultiTrades”，即：为订单分配tradeid的能力。此 id 传递给Trades，使得可以拥有不同类别的交易并同时开放。
当：
- 使用带有关键字参数
tradeid的 Calling Strategy.buy/sell/close - 使用带有关键字参数
tradeid的 Calling Broker.buy/sell - 创建带有关键字参数
tradeid的订单实例
如果未指定，默认值为：
tradeid = 0
已实现了一个小脚本进行测试，通过实现自定义的MTradeObserver来可视化结果，根据tradeid分配不同的标记在图表上（测试值使用 0、1 和 2）
该脚本支持使用三个 id（0、1、2）或仅使用 0（默认值）
未启用多个 id 的执行：
$ ./multitrades.py --plot
结果图表显示所有交易都携带 id 0，因此无法区分。
第二次执行通过在 0、1 和 2 之间循环实现多交易：
$ ./multitrades.py --plot --mtrade
现在 3 个不同的标记交替显示，每个交易都可以使用tradeid成员进行区分。
注意
backtrader尝试使用模拟现实的模型。因此，“交易”不是由仅负责订单的Broker实例计算的。
交易由策略计算。
因此，tradeid（或类似的内容）可能不会被真实经纪人支持，在这种情况下，需要手动跟踪经纪人分配的唯一订单 id。
现在，自定义观察者的代码
from __future__ import (absolute_import, division, print_function, unicode_literals) import math import backtrader as bt class MTradeObserver(bt.observer.Observer): lines = ('Id_0', 'Id_1', 'Id_2') plotinfo = dict(plot=True, subplot=True, plotlinelabels=True) plotlines = dict( Id_0=dict(marker='*', markersize=8.0, color='lime', fillstyle='full'), Id_1=dict(marker='o', markersize=8.0, color='red', fillstyle='full'), Id_2=dict(marker='s', markersize=8.0, color='blue', fillstyle='full') ) def next(self): for trade in self._owner._tradespending: if trade.data is not self.data: continue if not trade.isclosed: continue self.lines[trade.tradeid][0] = trade.pnlcomm
主要脚本用法：
$ ./multitrades.py --help usage: multitrades.py [-h] [--data DATA] [--fromdate FROMDATE] [--todate TODATE] [--mtrade] [--period PERIOD] [--onlylong] [--cash CASH] [--comm COMM] [--mult MULT] [--margin MARGIN] [--stake STAKE] [--plot] [--numfigs NUMFIGS] MultiTrades optional arguments: -h, --help show this help message and exit --data DATA, -d DATA data to add to the system --fromdate FROMDATE, -f FROMDATE Starting date in YYYY-MM-DD format --todate TODATE, -t TODATE Starting date in YYYY-MM-DD format --mtrade Activate MultiTrade Ids --period PERIOD Period to apply to the Simple Moving Average --onlylong, -ol Do only long operations --cash CASH Starting Cash --comm COMM Commission for operation --mult MULT Multiplier for futures --margin MARGIN Margin for each future --stake STAKE Stake to apply in each operation --plot, -p Plot the read data --numfigs NUMFIGS, -n NUMFIGS Plot using numfigs figures
脚本的代码。
from __future__ import (absolute_import, division, print_function, unicode_literals) import argparse import datetime import itertools # The above could be sent to an independent module import backtrader as bt import backtrader.feeds as btfeeds import backtrader.indicators as btind import mtradeobserver class MultiTradeStrategy(bt.Strategy): '''This strategy buys/sells upong the close price crossing upwards/downwards a Simple Moving Average. It can be a long-only strategy by setting the param "onlylong" to True ''' params = dict( period=15, stake=1, printout=False, onlylong=False, mtrade=False, ) def log(self, txt, dt=None): if self.p.printout: dt = dt or self.data.datetime[0] dt = bt.num2date(dt) print('%s, %s' % (dt.isoformat(), txt)) def __init__(self): # To control operation entries self.order = None # Create SMA on 2nd data sma = btind.MovAv.SMA(self.data, period=self.p.period) # Create a CrossOver Signal from close an moving average self.signal = btind.CrossOver(self.data.close, sma) # To alternate amongst different tradeids if self.p.mtrade: self.tradeid = itertools.cycle([0, 1, 2]) else: self.tradeid = itertools.cycle([0]) def next(self): if self.order: return # if an order is active, no new orders are allowed if self.signal > 0.0: # cross upwards if self.position: self.log('CLOSE SHORT , %.2f' % self.data.close[0]) self.close(tradeid=self.curtradeid) self.log('BUY CREATE , %.2f' % self.data.close[0]) self.curtradeid = next(self.tradeid) self.buy(size=self.p.stake, tradeid=self.curtradeid) elif self.signal < 0.0: if self.position: self.log('CLOSE LONG , %.2f' % self.data.close[0]) self.close(tradeid=self.curtradeid) if not self.p.onlylong: self.log('SELL CREATE , %.2f' % self.data.close[0]) self.curtradeid = next(self.tradeid) self.sell(size=self.p.stake, tradeid=self.curtradeid) def notify_order(self, order): if order.status in [bt.Order.Submitted, bt.Order.Accepted]: return # Await further notifications if order.status == order.Completed: if order.isbuy(): buytxt = 'BUY COMPLETE, %.2f' % order.executed.price self.log(buytxt, order.executed.dt) else: selltxt = 'SELL COMPLETE, %.2f' % order.executed.price self.log(selltxt, order.executed.dt) elif order.status in [order.Expired, order.Canceled, order.Margin]: self.log('%s ,' % order.Status[order.status]) pass # Simply log # Allow new orders self.order = None def notify_trade(self, trade): if trade.isclosed: self.log('TRADE PROFIT, GROSS %.2f, NET %.2f' % (trade.pnl, trade.pnlcomm)) elif trade.justopened: self.log('TRADE OPENED, SIZE %2d' % trade.size) def runstrategy(): args = parse_args() # Create a cerebro cerebro = bt.Cerebro() # Get the dates from the args fromdate = datetime.datetime.strptime(args.fromdate, '%Y-%m-%d') todate = datetime.datetime.strptime(args.todate, '%Y-%m-%d') # Create the 1st data data = btfeeds.BacktraderCSVData( dataname=args.data, fromdate=fromdate, todate=todate) # Add the 1st data to cerebro cerebro.adddata(data) # Add the strategy cerebro.addstrategy(MultiTradeStrategy, period=args.period, onlylong=args.onlylong, stake=args.stake, mtrade=args.mtrade) # Add the commission - only stocks like a for each operation cerebro.broker.setcash(args.cash) # Add the commission - only stocks like a for each operation cerebro.broker.setcommission(commission=args.comm, mult=args.mult, margin=args.margin) # Add the MultiTradeObserver cerebro.addobserver(mtradeobserver.MTradeObserver) # And run it cerebro.run() # Plot if requested if args.plot: cerebro.plot(numfigs=args.numfigs, volume=False, zdown=False) def parse_args(): parser = argparse.ArgumentParser(description='MultiTrades') parser.add_argument('--data', '-d', default='../../datas/2006-day-001.txt', help='data to add to the system') parser.add_argument('--fromdate', '-f', default='2006-01-01', help='Starting date in YYYY-MM-DD format') parser.add_argument('--todate', '-t', default='2006-12-31', help='Starting date in YYYY-MM-DD format') parser.add_argument('--mtrade', action='store_true', help='Activate MultiTrade Ids') parser.add_argument('--period', default=15, type=int, help='Period to apply to the Simple Moving Average') parser.add_argument('--onlylong', '-ol', action='store_true', help='Do only long operations') parser.add_argument('--cash', default=100000, type=int, help='Starting Cash') parser.add_argument('--comm', default=2, type=float, help='Commission for operation') parser.add_argument('--mult', default=10, type=int, help='Multiplier for futures') parser.add_argument('--margin', default=2000.0, type=float, help='Margin for each future') parser.add_argument('--stake', default=1, type=int, help='Stake to apply in each operation') parser.add_argument('--plot', '-p', action='store_true', help='Plot the read data') parser.add_argument('--numfigs', '-n', default=1, help='Plot using numfigs figures') return parser.parse_args() if __name__ == '__main__': runstrategy()
