因为世界上没有任何事物是孤立存在的，购买资产的触发因素很可能实际上是另一种资产。
使用不同的分析技术，可能已经在两个不同的数据之间发现了相关性。
backtrader支持同时使用不同的数据源，因此它可以在大多数情况下用于此目的。
假设在以下公司之间发现了相关性：
OracleYahoo
可以想像，当雅虎生意好的时候，它会从甲骨文购买更多的服务器、更多的数据库和更专业的服务，从而推高股价。
因此，经过深入分析，制定了一项策略：
如果
Yahoo的收盘价超过简单移动平均线（第 15 期）购买
Oracle
退出仓位：
- 使用收盘价的向下交叉
订单运行类型：
- 市场
总之，使用backtrader进行设置需要什么：
创建一个
cerebro加载数据源 1 (Oracle) 并将其添加到cerebro
加载数据源 2 (Yahoo) 并将其添加到cerebro
加载我们设计的策略
策略细节：
在数据源 2 (Yahoo) 上创建一个简单的移动平均线
使用 Yahoo 的收盘价和移动平均线创建 CrossOver 指针
然后如上所述在数据源 1 (Oracle) 上运行买/卖订单。
下面的脚本使用以下默认值：
甲骨文（数据源 1）
雅虎（数据源 2）
现金：10000（系统默认）
股份：10股
佣金：每轮0.5%（表示为0.005）
期限：15个交易日
期间：2003、2004 和 2005
该脚本可以接受参数来修改上述设置，如帮助文本中所示：
$ ./multidata-strategy.py --help
usage: multidata-strategy.py [-h] [--data0 DATA0] [--data1 DATA1]
[--fromdate FROMDATE] [--todate TODATE]
[--period PERIOD] [--cash CASH]
[--commperc COMMPERC] [--stake STAKE] [--plot]
[--numfigs NUMFIGS]
MultiData Strategy
optional arguments:
-h, --help show this help message and exit
--data0 DATA0, -d0 DATA0
1st data into the system
--data1 DATA1, -d1 DATA1
2nd data into the system
--fromdate FROMDATE, -f FROMDATE
Starting date in YYYY-MM-DD format
--todate TODATE, -t TODATE
Starting date in YYYY-MM-DD format
--period PERIOD Period to apply to the Simple Moving Average
--cash CASH Starting Cash
--commperc COMMPERC Percentage commission for operation (0.005 is 0.5%
--stake STAKE Stake to apply in each operation
--plot, -p Plot the read data
--numfigs NUMFIGS, -n NUMFIGS
Plot using numfigs figures
标准运行的结果：
$ ./multidata-strategy.py 2003-02-11T23:59:59+00:00, BUY CREATE , 9.14 2003-02-12T23:59:59+00:00, BUY COMPLETE, 11.14 2003-02-12T23:59:59+00:00, SELL CREATE , 9.09 2003-02-13T23:59:59+00:00, SELL COMPLETE, 10.90 2003-02-14T23:59:59+00:00, BUY CREATE , 9.45 2003-02-18T23:59:59+00:00, BUY COMPLETE, 11.22 2003-03-06T23:59:59+00:00, SELL CREATE , 9.72 2003-03-07T23:59:59+00:00, SELL COMPLETE, 10.32 ... ... 2005-12-22T23:59:59+00:00, BUY CREATE , 40.83 2005-12-23T23:59:59+00:00, BUY COMPLETE, 11.68 2005-12-23T23:59:59+00:00, SELL CREATE , 40.63 2005-12-27T23:59:59+00:00, SELL COMPLETE, 11.63 ================================================== Starting Value - 100000.00 Ending Value - 99959.26 ==================================================
经过两年完整的战略运行后：
- 损失了 40.74 个货币单位
雅虎和甲骨文之间的相关性就这么多
视觉输出（添加--plot以生成图表）
以及脚本（已添加到samples/multidata-strategy目录下的backtrader的源代码分发中。
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import argparse
import datetime
# The above could be sent to an independent module
import backtrader as bt
import backtrader.feeds as btfeeds
import backtrader.indicators as btind
class MultiDataStrategy(bt.Strategy):
'''
This strategy operates on 2 datas. The expectation is that the 2 datas are
correlated and the 2nd data is used to generate signals on the 1st
- Buy/Sell Operationss will be executed on the 1st data
- The signals are generated using a Simple Moving Average on the 2nd data
when the close price crosses upwwards/downwards
The strategy is a long-only strategy
'''
params = dict(
period=15,
stake=10,
printout=True,
)
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 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.orderid = None
def __init__(self):
# To control operation entries
self.orderid = None
# Create SMA on 2nd data
sma = btind.MovAv.SMA(self.data1, period=self.p.period)
# Create a CrossOver Signal from close an moving average
self.signal = btind.CrossOver(self.data1.close, sma)
def next(self):
if self.orderid:
return # if an order is active, no new orders are allowed
if not self.position: # not yet in market
if self.signal > 0.0: # cross upwards
self.log('BUY CREATE , %.2f' % self.data1.close[0])
self.buy(size=self.p.stake)
else: # in the market
if self.signal < 0.0: # crosss downwards
self.log('SELL CREATE , %.2f' % self.data1.close[0])
self.sell(size=self.p.stake)
def stop(self):
print('==================================================')
print('Starting Value - %.2f' % self.broker.startingcash)
print('Ending Value - %.2f' % self.broker.getvalue())
print('==================================================')
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
data0 = btfeeds.YahooFinanceCSVData(
dataname=args.data0,
fromdate=fromdate,
todate=todate)
# Add the 1st data to cerebro
cerebro.adddata(data0)
# Create the 2nd data
data1 = btfeeds.YahooFinanceCSVData(
dataname=args.data1,
fromdate=fromdate,
todate=todate)
# Add the 2nd data to cerebro
cerebro.adddata(data1)
# Add the strategy
cerebro.addstrategy(MultiDataStrategy,
period=args.period,
stake=args.stake)
# 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.commperc)
# 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='MultiData Strategy')
parser.add_argument('--data0', '-d0',
default='../../datas/orcl-1995-2014.txt',
help='1st data into the system')
parser.add_argument('--data1', '-d1',
default='../../datas/yhoo-1996-2014.txt',
help='2nd data into the system')
parser.add_argument('--fromdate', '-f',
default='2003-01-01',
help='Starting date in YYYY-MM-DD format')
parser.add_argument('--todate', '-t',
default='2005-12-31',
help='Starting date in YYYY-MM-DD format')
parser.add_argument('--period', default=15, type=int,
help='Period to apply to the Simple Moving Average')
parser.add_argument('--cash', default=100000, type=int,
help='Starting Cash')
parser.add_argument('--commperc', default=0.005, type=float,
help='Percentage commission for operation (0.005 is 0.5%%')
parser.add_argument('--stake', default=10, 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()