技术指标(Indicators) #
本节将介绍如何使用技术指标,将技术指标作为入场和出场信号。我们将用简单移动平均线(Simple Moving Average),或称 SMA,作为演示指标。SMA 是一个非常简单的技术指标,计算一定周期的价格均值。
交易规则 #
基于 SMA 交易规则,定义如下所示:
- 入场条件: 当收盘价大于最新的 SMA,则入场买入。
- 出场条件: 当持有头寸,当收盘价小于 SMA,则出场卖出。
前面章节的策略代码大部分可复用,现在重点关注如何计算技术指标。
指标计算 #
backtrader 下的 indicators
模块内置了大量技术指标的计算方法,如 SMA 简单移动均线的计算。
self.sma = bt.indicators.MovingAverageSimple(self.datas[0], period=self.params.maperiod)
如上代码中参数 self.params.maperiod
就是 SMA 的均线周期。
注:如果安装了 talib,backtrader 也集成了 talib 的支持,详情文档 指标-TALib。
条件判断 #
现在基于 self.sma
判断进出场条件。
为了简化代码,这里只考虑 SMA 的判断逻辑,在完整实例中会包含所有情况。
入场判断:
self.dataclose[0] > self.sma[0]
出场判断:
self.dataclose[0] < self.sma[0]
策略代码 #
起始现金 1000 货币单位。
import datetime # For datetime objects
import os.path # To manage paths
import sys # To find out the script name (in argv[0])
import backtrader as bt
策略部分:
class TestStrategy(bt.Strategy):
params = (
('maperiod', 15),
)
def log(self, txt, dt=None):
dt = dt or self.datas[0].datetime.date(0)
print('%s, %s' % (dt.isoformat(), txt))
def __init__(self):
self.dataclose = self.datas[0].close
self.order = None
self.buyprice = None
self.buycomm = None
self.sma = bt.indicators.SimpleMovingAverage(
self.datas[0], period=self.params.maperiod)
def notify_order(self, order):
if order.status in [order.Submitted, order.Accepted]:
return
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))
self.buyprice = order.executed.price
self.buycomm = order.executed.comm
else:
self.log('SELL EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %
(order.executed.price,
order.executed.value,
order.executed.comm))
self.bar_executed = len(self)
elif order.status in [order.Canceled, order.Margin, order.Rejected]:
self.log('Order Canceled/Margin/Rejected')
self.order = None
def notify_trade(self, trade):
if not trade.isclosed:
return
self.log('OPERATION PROFIT, GROSS %.2f, NET %.2f' %
(trade.pnl, trade.pnlcomm))
def next(self):
self.log('Close, %.2f' % self.dataclose[0])
if self.order:
return
if not self.position:
if self.dataclose[0] > self.sma[0]:
self.log('BUY CREATE, %.2f' % self.dataclose[0])
self.order = self.buy()
else:
if self.dataclose[0] < self.sma[0]:
self.log('SELL CREATE, %.2f' % self.dataclose[0])
self.order = self.sell()
if __name__ == '__main__':
cerebro = bt.Cerebro()
cerebro.addstrategy(TestStrategy)
modpath = os.path.dirname(os.path.abspath(sys.argv[0]))
datapath = os.path.join(modpath, '../../datas/orcl-1995-2014.txt')
data = bt.feeds.YahooFinanceCSVData(
dataname=datapath,
fromdate=datetime.datetime(2000, 1, 1),
todate=datetime.datetime(2000, 12, 31),
reverse=False)
cerebro.adddata(data)
cerebro.broker.setcash(1000.0)
cerebro.addsizer(bt.sizers.FixedSize, stake=10)
cerebro.broker.setcommission(commission=0.0)
print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())
cerebro.run()
print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
输出:
Starting Portfolio Value: 1000.00
2000-01-24, Close, 25.55
2000-01-25, Close, 26.61
2000-01-25, BUY CREATE, 26.61
2000-01-26, BUY EXECUTED, Size 10, Price: 26.76, Cost: 267.60, Commission 0.00
2000-01-26, Close, 25.96
2000-01-27, Close, 24.43
2000-01-27, SELL CREATE, 24.43
2000-01-28, SELL EXECUTED, Size 10, Price: 24.28, Cost: 242.80, Commission 0.00
2000-01-28, OPERATION PROFIT, GROSS -24.80, NET -24.80
...
...
...
2000-12-20, SELL CREATE, 26.88
2000-12-21, SELL EXECUTED, Size 10, Price: 26.23, Cost: 262.30, Commission 0.00
2000-12-21, OPERATION PROFIT, GROSS -20.60, NET -20.60
2000-12-21, Close, 27.82
2000-12-21, BUY CREATE, 27.82
2000-12-22, BUY EXECUTED, Size 10, Price: 28.65, Cost: 286.50, Commission 0.00
2000-12-22, Close, 30.06
2000-12-26, Close,
29.17
2000-12-27, Close, 28.94
2000-12-28, Close, 29.29
2000-12-29, Close, 27.41
2000-12-29, SELL CREATE, 27.41
Final Portfolio Value: 973.90
现在,投资组合变得亏损了。