Hourly Data

KT

Hi Just wanna check whether this is the way to import an hourly data.

data0 = btfeeds.GenericCSVData(dataname=datapath0,
                                   timeframe=bt.TimeFrame.Minutes,
                                  fromdate = datetime.datetime(2017,3,15),
                                  todate=datetime.datetime(2017,3,20),                                  
                                  nullvalue=0.0,
                                  dtformat=('%Y.%m.%d'),
                                  tmformat=('%H:%M'),
                                  datetime=0,
                                  time=1,
                                  open=2,
                                  high=3,
                                  low=4,
                                  close=5,
                                  volume=6,
                                  openinterest=-1)

is this the way to set the order to be valid for an hour?

self.sell(exectype = bt.Order.Limit,price=self.data.close[-1],
                            transmit=False,valid=datetime.datetime.now()+datetime.timedelta(hours=1))

This is the full code.



from __future__ import (absolute_import, division, print_function,
                        unicode_literals)
import os.path
import argparse
import datetime

import backtrader as bt
import backtrader.feeds as btfeeds
import backtrader.plot as plt
import backtrader.indicators as btinds

class EMA(btinds.PeriodN):
    lines = ('signal1','signal2')
    params = (('p1',5),('p2',20),('p3',50),)
    
    def __init__(self):
        ema5 = btinds.ExponentialMovingAverage(self.data.close, period=self.p.p1)
        ema20 = btinds.ExponentialMovingAverage(self.data.close, period=self.p.p2)
        ema50 = btinds.ExponentialMovingAverage(self.data.close,period=self.p.p3)
        self.lines.signal1 = ema5-ema20
        self.lines.signal2 = ema20-ema50

class St(bt.Strategy):
    
    def log(self, txt, dt=None):
        ''' Logging function fot this strategy'''
        dt = dt or self.data0.datetime.date(0)
        dt1 = self.data0.datetime.time(0)
        print('%s,%s, %s' % (dt.isoformat(),dt1.isoformat(), txt))
        
    def __init__(self):
        self.trigger = EMA()
        self.spread = btinds.AverageTrueRange(period=20)
        
    def notify_order(self, order):
        print('{} {}: Order ref: {} / Type {} / Status {}'.format(
            self.data.datetime.date(0),self.data.datetime.time(0),
            order.ref, 'Buy' * order.isbuy() or 'Sell',
            order.getstatusname()))
        
        if order.status in [order.Submitted, order.Accepted]:
            return
        
        if order.status in [order.Completed]:
            if order.isbuy():
                self.log(
                    'BUY EXECUTED, Ref: %d, Price: %.5f, Cost: %.5f' %
                    (order.ref,order.executed.price,
                     order.executed.value))
                
                self.buyprice = order.executed.price
                
            else:  # Sell
                self.log('SELL EXECUTED, Ref: %d,Price: %.5f, Cost: %.5f' %
                         (order.ref,order.executed.price,
                          order.executed.value))
        
            self.bar_executed = len(self)
            
        elif order.status in [order.Canceled, order.Margin, order.Rejected]:
            self.log('Order Canceled/Margin/Rejected')
        
        if not order.alive() and order.ref in self.orefs:
            self.orefs.remove(order.ref)
        
    def notify_trade(self, trade):
        if not trade.isclosed:
            return

        self.log('OPERATION PROFIT, GROSS %.5f, NET %.5f' %
                 (trade.pnl, trade.pnlcomm))
        
    def next(self):
        txt = ','.join(
            ['%04d' % len(self.data0),
             self.data0.datetime.date(0).isoformat(),
             self.data0.datetime.time(0).isoformat(),
             'Open : %.5f' % self.data0.open[0],
             'High : %.5f' % self.data.high[0],
             'Low : %.5f' % self.data.low[0],
             'Close : %.5f' % self.data.close[0]]) 
        print(txt)

 

        if (self.trigger.signal1[0] > 0) and (self.trigger.signal2[0] > 0):
             o1 = self.sell(exectype = bt.Order.Limit,price=self.data.close[-1],
                            transmit=False,valid=datetime.datetime.now()+datetime.timedelta(hours=1))
             
             print(self.datetime.date(0),self.datetime.time(0),' : Oref %d / Sell at %.5f' % (
                        o1.ref, self.data.close[-1]))
            
             o2 = self.buy(exectype=bt.Order.Limit,price=(self.data.close[-1] - self.spread.atr[0] * 2),
                            parent=o1,transmit=False)
             
             print(self.datetime.date(0),self.datetime.time(0),' : Oref %d / Sell Take Profit at %.5f' % (
                        o2.ref, (self.data.close[-1] - self.spread.atr[0] * 2)))
             
             o3 = self.buy(exectype=bt.Order.Stop,price = (self.spread.atr[0] * 2 +self.data.close[-1]),
                           parent=o1,transmit = True)
             
             print(self.datetime.date(0),self.datetime.time(0),' : Oref %d / Sell Stop Loss at %.5f' % (
                        o3.ref, (self.spread.atr[0] * 2 +self.data.close[-1])))
             
             self.orefs = [o1.ref, o2.ref, o3.ref]
             
        elif (self.trigger.signal1[0] < 0) and (self.trigger.signal2[0] < 0):
             o1 = self.buy(exectype = bt.Order.Limit,price=self.data.close[-1],
                            transmit=False,valid= datetime.datetime.now()+datetime.timedelta(hours=1))
             
             print(self.datetime.date(0),self.datetime.time(0),' : Oref %d / Buy at %.5f' % (
                        o1.ref, self.data.close[-1]))
            
             o2 = self.sell(exectype=bt.Order.Limit,price=(self.spread.atr[0] * 2 +self.data.close[-1]),
                            parent=o1,transmit=False)
             
             print(self.datetime.date(0),self.datetime.time(0),' : Oref %d / Buy Take Profit at %.5f' % (
                        o2.ref, (self.spread.atr[0] * 2 +self.data.close[-1])))
             
             o3 = self.sell(exectype=bt.Order.Stop,price = (self.data.close[-1] - self.spread.atr[0] * 2),
                           parent=o1,transmit = True)
             
             print(self.datetime.date(0),self.datetime.time(0),' : Oref %d / Buy Stop Loss at %.5f' % (
                        o3.ref, (self.data.close[-1] - self.spread.atr[0] * 2))) 
             
             self.orefs = [o1.ref, o2.ref, o3.ref]
        
        else:
             return



class Plotter(plt.Plot):

    def __init__(self):
        super().__init__(volup='#60cc73')  # custom color for volume up bars 

    def show(self):
        mng = self.mpyplot.get_current_fig_manager()
        mng.window.state('zoomed')
        self.mpyplot.show()  
                  
def runstrat():
    args = parse_args()

    cerebro = bt.Cerebro()
    modpath = 'd:\\I - TradersGPS\\'
    datapath0 = os.path.join(modpath, 'GBPUSD_H1_UTC+2_00.csv')
   
    data0 = btfeeds.GenericCSVData(dataname=datapath0,
                                   timeframe=bt.TimeFrame.Minutes,
                                  fromdate = datetime.datetime(2017,3,15),
                                  todate=datetime.datetime(2017,3,20),                                  
                                  nullvalue=0.0,
                                  dtformat=('%Y.%m.%d'),
                                  tmformat=('%H:%M'),
                                  datetime=0,
                                  time=1,
                                  open=2,
                                  high=3,
                                  low=4,
                                  close=5,
                                  volume=6,
                                  openinterest=-1)

    cerebro.adddata(data0,name ="Hourly Data")


    cerebro.addstrategy(St)
    cerebro.broker.setcash(100000.0)
    print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())
    cerebro.run(stdstats=False)
    print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
    plotter = Plotter()
    cerebro.plot(plotter=plotter,subplot=False)
    

        
def parse_args():
    parser = argparse.ArgumentParser(
        formatter_class=argparse.ArgumentDefaultsHelpFormatter,
        description='Sample for pivot point and cross plotting')

    parser.add_argument('--data0',
                        default='d:\\I - TradersGPS\\GBPUSD_D1_UTC+2_00.csv',
                        required=False, help='Data0 to read in')

    parser.add_argument('--data1', 
                        default='d:\\I - TradersGPS\\GBPUSD_H1_UTC+2_00.csv',
                        required=False, help='Data1 to read in')

    parser.add_argument('--fromdate', required=False, default='2001-01-01',
                        help='Date[time] in YYYY-MM-DD[THH:MM:SS] format')
    
    parser.add_argument('--todate', required=False, default='2007-01-01',
                        help='Date[time] in YYYY-MM-DD[THH:MM:SS] format')

    parser.add_argument('--plot', required=False, action='store_true',
                        help=('Plot the result'))

    return parser.parse_args()


if __name__ == '__main__':
    runstrat()

This is the full data used for the code. Its in csv format. The col names are date, time, open, high,low,close,and volume.

2017.03.15,00:00,1.21542,1.21545,1.21469,1.21524,2206
2017.03.15,01:00,1.21526,1.21579,1.21512,1.21565,2452
2017.03.15,02:00,1.21564,1.21629,1.21543,1.21585,6088
2017.03.15,03:00,1.21585,1.2165,1.21583,1.21614,5760
2017.03.15,04:00,1.21615,1.21641,1.21561,1.21563,5428
2017.03.15,05:00,1.21561,1.21578,1.21547,1.21573,3666
2017.03.15,06:00,1.21573,1.21652,1.21568,1.21632,5902
2017.03.15,07:00,1.21633,1.21775,1.21632,1.21761,5403
2017.03.15,08:00,1.21759,1.22564,1.21724,1.2222,16657
2017.03.15,09:00,1.22222,1.22303,1.22128,1.22296,14750
2017.03.15,10:00,1.22295,1.22361,1.22216,1.22276,15442
2017.03.15,11:00,1.22276,1.22369,1.21891,1.22035,19990
2017.03.15,12:00,1.22034,1.22037,1.21783,1.21926,13041
2017.03.15,13:00,1.21926,1.21959,1.21845,1.21933,10811
2017.03.15,14:00,1.21936,1.22084,1.21913,1.21942,13239
2017.03.15,15:00,1.21943,1.22046,1.21929,1.22,12251
2017.03.15,16:00,1.22,1.22058,1.21905,1.22004,12706
2017.03.15,17:00,1.22004,1.22258,1.21993,1.22209,13129
2017.03.15,18:00,1.22212,1.22264,1.22104,1.22214,12973
2017.03.15,19:00,1.22216,1.22228,1.21994,1.22021,12341
2017.03.15,20:00,1.22021,1.23017,1.21963,1.22933,34103
2017.03.15,21:00,1.22932,1.23022,1.22725,1.22972,21987
2017.03.15,22:00,1.22972,1.23091,1.22814,1.22911,16419
2017.03.15,23:00,1.22904,1.22911,1.22789,1.22869,3891
2017.03.16,00:00,1.2287,1.22958,1.22856,1.22908,5988
2017.03.16,01:00,1.22907,1.22945,1.22765,1.22822,7144
2017.03.16,02:00,1.22822,1.22913,1.22731,1.2274,11114
2017.03.16,03:00,1.22745,1.22778,1.22654,1.22672,8733
2017.03.16,04:00,1.22676,1.22776,1.22649,1.2269,7097
2017.03.16,05:00,1.2269,1.22734,1.22601,1.22641,10835
2017.03.16,06:00,1.22641,1.22714,1.22627,1.2266,10021
2017.03.16,07:00,1.2266,1.22724,1.22651,1.22659,7106
2017.03.16,08:00,1.2266,1.22816,1.22618,1.22804,12500
2017.03.16,09:00,1.2281,1.22956,1.22669,1.22725,21005
2017.03.16,10:00,1.22728,1.22795,1.22551,1.22554,16387
2017.03.16,11:00,1.22554,1.22659,1.22413,1.22497,13910
2017.03.16,12:00,1.22497,1.22758,1.22473,1.22548,14495
2017.03.16,13:00,1.22549,1.22718,1.22472,1.22639,14245
2017.03.16,14:00,1.2264,1.23721,1.22639,1.23694,29017
2017.03.16,15:00,1.23686,1.23713,1.23365,1.23411,17264
2017.03.16,16:00,1.23411,1.23665,1.23404,1.23621,15739
2017.03.16,17:00,1.23621,1.2375,1.2344,1.2368,14576
2017.03.16,18:00,1.23682,1.23721,1.23589,1.23711,11462
2017.03.16,19:00,1.23711,1.23769,1.2348,1.23522,10574
2017.03.16,20:00,1.2352,1.2364,1.2343,1.23588,10558
2017.03.16,21:00,1.23589,1.23602,1.23463,1.2357,11578
2017.03.16,22:00,1.23567,1.2363,1.23526,1.23586,6554
2017.03.16,23:00,1.23586,1.23628,1.23512,1.23595,3276
2017.03.17,00:00,1.23587,1.23589,1.23501,1.23552,4564
2017.03.17,01:00,1.23558,1.23559,1.23451,1.23498,3733
2017.03.17,02:00,1.23499,1.23572,1.23487,1.23561,5700
2017.03.17,03:00,1.23561,1.23576,1.23476,1.2349,6879
2017.03.17,04:00,1.23489,1.23521,1.23433,1.23518,4409
2017.03.17,05:00,1.23517,1.23547,1.23477,1.23519,4274
2017.03.17,06:00,1.23521,1.23559,1.23492,1.23553,3473
2017.03.17,07:00,1.23553,1.23572,1.2349,1.23538,3402
2017.03.17,08:00,1.2354,1.23723,1.23538,1.23649,7620
2017.03.17,09:00,1.23646,1.23689,1.23237,1.23378,15104
2017.03.17,10:00,1.23375,1.23893,1.23333,1.2387,14981
2017.03.17,11:00,1.23866,1.23983,1.23783,1.23888,16611
2017.03.17,12:00,1.2389,1.23958,1.23779,1.23842,16616
2017.03.17,13:00,1.23846,1.23849,1.23346,1.23598,21205
2017.03.17,14:00,1.23602,1.23702,1.23461,1.23574,16343
2017.03.17,15:00,1.23576,1.23694,1.23485,1.23653,15528
2017.03.17,16:00,1.23653,1.23765,1.23615,1.23676,14217
2017.03.17,17:00,1.23675,1.23729,1.23603,1.23701,14439
2017.03.17,18:00,1.23701,1.23895,1.23671,1.23874,14336
2017.03.17,19:00,1.23873,1.23972,1.2386,1.23936,10018
2017.03.17,20:00,1.23936,1.24047,1.23908,1.23956,6863
2017.03.17,21:00,1.23961,1.24014,1.23907,1.23908,6511
2017.03.17,22:00,1.23908,1.23984,1.23886,1.23945,5466
2017.03.19,23:00,1.2381,1.23915,1.23796,1.23847,1394
2017.03.20,00:00,1.23847,1.23911,1.23838,1.23868,2758
2017.03.20,01:00,1.23868,1.23881,1.2382,1.23833,2955
2017.03.20,02:00,1.23833,1.23884,1.23812,1.23824,4078
2017.03.20,03:00,1.23825,1.23907,1.2382,1.23902,5344
2017.03.20,04:00,1.23902,1.23926,1.23838,1.23848,4912
2017.03.20,05:00,1.23852,1.23877,1.23804,1.23839,4008
2017.03.20,06:00,1.23838,1.23877,1.23832,1.23866,3246
2017.03.20,07:00,1.23868,1.23944,1.23868,1.23937,3854
2017.03.20,08:00,1.23935,1.24018,1.23871,1.23994,6686
2017.03.20,09:00,1.23995,1.24354,1.23976,1.24177,14185
2017.03.20,10:00,1.24177,1.24256,1.24023,1.24095,13778
2017.03.20,11:00,1.24095,1.24246,1.2406,1.24115,13768
2017.03.20,12:00,1.24117,1.24202,1.23997,1.24183,10369
2017.03.20,13:00,1.24184,1.24184,1.23787,1.23839,13195
2017.03.20,14:00,1.23842,1.23883,1.23664,1.23822,13276
2017.03.20,15:00,1.23818,1.23961,1.23747,1.23884,11533
2017.03.20,16:00,1.23883,1.23964,1.23827,1.2383,12111
2017.03.20,17:00,1.23832,1.23874,1.2364,1.23655,13787
2017.03.20,18:00,1.23655,1.23715,1.2335,1.23453,14811
2017.03.20,19:00,1.2346,1.23538,1.23396,1.23443,11122
2017.03.20,20:00,1.23442,1.23511,1.23431,1.23462,7742
2017.03.20,21:00,1.23462,1.23593,1.23454,1.23562,6938
2017.03.20,22:00,1.23562,1.23606,1.23532,1.23578,5342
2017.03.20,23:00,1.23573,1.23601,1.2355,1.23573,2112

Thanks!!

backtrader

@KT said in Hourly Data:

timeframe=bt.TimeFrame.Minutes,

If you don't specify the compression=60, the default of compression=1 will be used.

@KT said in Hourly Data:

valid=datetime.datetime.now()+datetime.timedelta(hours=1)

If you were doing live trading, the current clock time would approximate the data source time. But it doesn't in backtesting. Use self.dataX.datetime.datetime(), or the reference clock of the strategy self.datetime.datetime()

KT

Thanks @backtrader !!