from __future__ import (absolute_import, division, print_function, unicode_literals) import datetime # For datetime objects import os.path # To manage paths import sys # To find out the script name (in argv[0]) import pandas as pd #import statsmodel as sm # Import the backtrader platform import backtrader as bt # Create a Stratey class TestStrategy(bt.Strategy): params = ( # Standard MACD Parameters ('period', 252), ('prepend_constant', True), ) def log(self, txt, dt=None): ''' Logging function for this strategy''' dt = dt or self.datas[0].datetime.date(0) print('%s, %s' % (dt.isoformat(), txt)) def __init__(self): self.dataclose_x = self.datas[0].close self.dataclose_y = self.datas[1].close self.ma1 = bt.indicators.SMA(self.datas[0], period=self.p.period ) self.ma2 = bt.indicators.SMA(self.datas[1], period=self.p.period ) self.order = None self.buyprice = None self.buycomm = None def notify_cashvalue(self, cash, value): self.log('Cash %s Value %s' % (cash, value)) def notify_order(self, order): print(type(order), 'Is Buy ', order.isbuy()) if order.status in [order.Submitted, order.Accepted]: # Buy/Sell order submitted/accepted to/by broker - Nothing to do return # Check if an order has been completed # Attention: broker could reject order if not enough cash 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: # Sell 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): # Simply log the closing price of the series from the reference self.log('Close, %.2f' % self.dataclose_x[0]) self.log('Close, %.2f' % self.dataclose_y[0]) # Check if we are in the market if not self.getposition(self.datas[1]): # Not yet ... we MIGHT BUY if ... if (self.ma1[0]-self.ma1[-1])/self.ma1[-1]>(self.ma2[0]-self.ma2[-1])/self.ma2[-1]: #if sma[0]<top[-5]: # BUY, BUY, BUY!!! (with default parameters) self.log('BUY CREATE,{},{}'.format(self.dataclose_y[0],self.dataclose_x[0]) ) # Keep track of the created order to avoid a 2nd order self.order=self.buy(self.datas[0]) self.order = self.sell(self.datas[1]) else: # Already in the market ... we might sell if (self.ma1[0]-self.ma1[-1])/self.ma1[-1]<=(self.ma2[0]-self.ma2[-1])/self.ma2[-1]: # SELL, SELL, SELL!!! (with all possible default parameters) self.log('BUY CREATE,{},{}'.format(self.dataclose_y[0],self.dataclose_x[0]) ) # Keep track of the created order to avoid a 2nd order self.log('Pos size %s' % self.position.size) self.order = self.close(self.datas[1]) self.order = self.close(self.datas[0]) if __name__ == '__main__': # Create a cerebro entity cerebro = bt.Cerebro() cerebro.addstrategy(TestStrategy) # Datas are in a subfolder of the samples. Need to find where the script is # because it could have been called from anywhere datapath_1='C:/Users/Administrator/Documents/000001.SZ.csv' datapath_2='C:/Users/Administrator/Documents/000002.SZ.csv' # Create a Data Feed data_1 = bt.feeds.GenericCSVData( dataname=datapath_1, # Do not pass values before this date fromdate=datetime.datetime(1991, 12, 23), # Do not pass values after this date todate=datetime.datetime(2017, 12, 31), dtformat=('%Y-%m-%d'), tmformat=('%H.%M.%S'), date=0, open=1, close=2, high=3, low=4, volume=5, openinterest=6, code=-1, reverse=False) data_2 = bt.feeds.GenericCSVData( dataname=datapath_2, # Do not pass values before this date fromdate=datetime.datetime(1991, 12, 23), # Do not pass values after this date todate=datetime.datetime(2017, 12, 31), dtformat=('%Y-%m-%d'), tmformat=('%H.%M.%S'), date=0, open=1, close=2, high=3, low=4, volume=5, openinterest=6, reverse=False) # Add the Data Feed to Cerebro cerebro.adddata(data_1) cerebro.adddata(data_2) # Set our desired cash start cerebro.broker.setcash(100000.0) cerebro.broker.setcommission(commission=0.001) cerebro.addsizer(bt.sizers.FixedSize, stake=100) # Print out the starting conditions print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue()) # Run over everything cerebro.run() # Print out the final result print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue()) cerebro.plot()
