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    BackTrader plots but does not calculate trades or profits what did I do wrong?

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    • Feather BTC
      Feather BTC last edited by

      The Data is in Timestamp format from Bitmex using CCXT, I am testing a simple strategy from the docs and have followed a few threads to make changed an example output is :

      Starting Portfolio Value: 10000.00
      2 5
      2019-08-11, Close, 210.45
      2019-08-11, Close, 210.55
      2019-08-11, Close, 210.60
      2019-08-11, Close, 210.55
      2019-08-11, BUY CREATE, 210.55
      2019-08-11, Close, 210.60
      2019-08-11, Close, 210.65
      2019-08-11, Close, 210.65
      2019-08-11, Close, 210.50
      2019-08-11, Close, 210.05
      2019-08-11, Close, 210.05
      2019-08-11, Close, 210.20
      2019-08-11, Close, 209.95
      2019-08-11, Close, 210.15
      2019-08-11, Close, 210.05
      2019-08-11, Close, 210.05
      2019-08-11, Close, 210.15
      2019-08-11, Close, 210.20
      2019-08-11, Close, 210.20
      2019-08-11, Close, 210.20
      2019-08-11, Close, 210.10
      2019-08-11, Close, 210.05
      2019-08-11, Close, 209.90
      2019-08-11, Close, 209.95
      2019-08-11, Close, 210.05
      2019-08-11, Close, 210.20
      2019-08-11, Close, 210.20
      2019-08-11, Close, 210.15
      2019-08-11, Close, 210.20
      2019-08-11, Close, 210.15
      2019-08-11, Close, 210.15
      2019-08-11, Close, 210.20
      2019-08-11, Close, 210.25
      2019-08-11, Close, 210.20
      2019-08-11, Close, 210.15
      2019-08-11, Close, 210.10
      2019-08-11, Close, 210.10
      2019-08-11, Close, 210.15
      2019-08-11, Close, 210.15
      2019-08-11, Close, 210.15
      2019-08-11, Close, 210.10
      2019-08-11, Close, 210.10
      2019-08-11, Close, 210.15
      2019-08-11, Close, 210.10
      2019-08-11, Close, 210.15
      2019-08-11, Close, 210.15
      2019-08-11, Close, 210.15
      2019-08-11, Close, 210.10
      2019-08-11, Close, 210.10
      2019-08-11, Close, 210.15
      2019-08-11, Close, 210.10
      2019-08-11, Close, 210.15
      2019-08-11, Close, 210.15
      2019-08-11, Close, 210.15
      2019-08-11, Close, 210.20
      2019-08-11, Close, 210.15
      2019-08-11, Close, 210.10
      2019-08-11, Close, 210.10
      2019-08-11, Close, 210.15
      2019-08-11, Close, 210.15
      2019-08-11, Close, 210.15
      2019-08-11, Close, 210.15
      2019-08-11, Close, 210.30
      2019-08-11, Close, 210.70
      2019-08-11, Close, 210.85
      2019-08-11, Close, 210.90
      2019-08-11, Close, 210.90
      2019-08-11, Close, 210.90
      2019-08-11, Close, 210.90
      2019-08-11, Close, 210.95
      2019-08-11, Close, 210.90
      2019-08-11, Close, 210.90
      2019-08-11, Close, 210.95
      2019-08-11, Close, 210.90
      2019-08-11, Close, 210.95
      2019-08-11, Close, 210.95
      2019-08-11, Close, 210.95
      2019-08-11, Close, 210.90
      2019-08-11, Close, 210.90
      2019-08-11, Close, 210.90
      Final Portfolio Value: 10000.00
      

      One of the Issues I see both on the Matlib chart and on the responses are that the time is always the same date when the timestamps are not

      here is my code :

      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 the backtrader platform
      import backtrader as bt
      import backtrader.feeds as btfeed
      import math
      
      
      
      class customCSV(btfeed.GenericCSVData):
          params = (
              ('nullvalue', float('NaN')),
              ('dtformat', lambda x: datetime.datetime.utcfromtimestamp(int(x[:-3]))),
              ('tmformat', '%yyy:%MM:%dd %H:%M:%S'),
              ('datetime', 1),
              ('time', -1),
              ('open', 2),
              ('high', 3),
              ('low', 4),
              ('close', 5),
              ('volume', 6),
              ('openinterest', -1),
              ('seperator',',')
          )
      
      
      class SmaCross(bt.SignalStrategy):
          params = (('pfast', 10), ('pslow', 21),)
      
          def __init__(self):
              # Keep a reference to the "close" line in the data[0] dataseries
              self.dataclose = self.datas[0].close
              
               # To keep track of pending orders and buy price/commission
              self.order = None
              self.buyprice = None
              self.buycomm = None
              
              
              sma1, sma2 = bt.ind.SMA(period=self.p.pfast), bt.ind.SMA(period=self.p.pslow)
              self.signal_add(bt.SIGNAL_LONG, bt.ind.CrossOver(sma1, sma2))
              self.signal_add(bt.SIGNAL_SHORT, bt.ind.CrossOver(sma2,sma1))
              self.buysig = bt.ind.CrossOver(sma1, sma2)
              self.sellsig = bt.ind.CrossOver(sma2,sma1)
              print(bt.SIGNAL_LONG,bt.SIGNAL_SHORT)
            
          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 notify_order(self, order):
              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('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[0])
      
              # Check if an order is pending ... if yes, we cannot send a 2nd one
              if self.order:
                  return
              
              # Check if we are in the market
              if not self.position:
              
                  # buy signal
                  if self.buysig > 0:
                      # BUY
                      self.log('BUY CREATE, %.2f' % self.dataclose[0])
                      # Keep track of the created order to avoid a 2nd order
                      self.order = self.buy()
                  elif self.sellsig > 0:
                      #if len(self) >= (self.bar_executed + self.params.exitbars):
                          # Sell
                      self.log('SELL CREATE, %.2f' % self.dataclose[0])
                          # Keep track of the created order to avoid a 2nd order
                      self.order = self.sell(size=1000)
                      #else:
                          #return
                  else:
                      return
              else:    # in a position        
                  if self.buysig < 0:
                      # Buy Closed
                      self.log('BUY CLOSE, %.2f' % self.dataclose[0])
                      self.order = self.close()
                      self.order = self.sell(size=1000)
                  # elif ignore zero case
                  elif self.sellsig < 0:
                      # Sell Closed
                      self.log('SELL CLOSE, %.2f' % self.dataclose[0])
                      self.order = self.close()
                      self.order = self.buy()
                  else:
                      return
                  
      
      class maxRiskSizer(bt.Sizer):
          '''
          Returns the number of shares rounded down that can be purchased for the
          max rish tolerance
          '''
          params = (('risk', 0.20),)
      
          def __init__(self):
              if self.p.risk > 1 or self.p.risk < 0:
                  raise ValueError('The risk parameter is a percentage which must be entered as a float. e.g. 0.5')
              
          def _getsizing(self, comminfo, cash, data, isbuy):
      
              position = self.broker.getposition(data)
      
              if not position:
                  size = math.floor((cash * self.p.risk) /data.close[0])
              else:
                  size = position.size
      
              return size
              
              
      startcash = 10000
             
              
              
      
      cerebro = bt.Cerebro()
      cerebro.addsizer(maxRiskSizer)
      cerebro.broker.setcommission(commission=0.001)
      data = customCSV(dataname='bitmex-ETHUSD-1m.csv')
      print(data)
      cerebro.broker.setcash(startcash)
      cerebro.adddata(data)
      cerebro.addstrategy(SmaCross)
      print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())
      cerebro.run()
      print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
      cerebro.plot(style='candle')
      

      Here is my sample data:

      ,Timestamp,Open,High,Low,Close,Volume
      0,1565528940000,210.8,210.8,210.8,210.8,9200.0
      1,1565529000000,210.8,210.8,210.8,210.8,18693.0
      2,1565529060000,210.8,210.8,210.75,210.75,210.0
      3,1565529120000,210.75,210.75,210.75,210.75,14900.0
      4,1565529180000,210.75,210.75,210.75,210.75,1000.0
      5,1565529240000,210.75,210.8,210.75,210.75,6320.0
      6,1565529300000,210.75,210.75,210.65,210.65,16310.0
      7,1565529360000,210.65,210.65,210.55,210.55,22421.0
      8,1565529420000,210.55,210.5,210.5,210.5,4624.0
      

      There are 100 records 0 - 99

      Feather BTC 1 Reply Last reply Reply Quote 0
      • Feather BTC
        Feather BTC @Feather BTC last edited by

        @Feather-BTC Another good note is this is minute OHLCV Data

        B 1 Reply Last reply Reply Quote 0
        • B
          backtrader administrators @Feather BTC last edited by

          @Feather-BTC said in BackTrader plots but does not calculate trades or profits what did I do wrong?:

          Another good note is this is minute OHLCV Data

          And have you tried telling the platform that detail? See Community - FAQ - Look for timeframe and compression

          Feather BTC 1 Reply Last reply Reply Quote 0
          • Feather BTC
            Feather BTC @backtrader last edited by

            @backtrader This worked, thank you , now I am just trying to get my time format to output the minutes/seconds of the trade so I can track duration lol, something to play with haha.

            1 Reply Last reply Reply Quote 0
            • B
              backtrader administrators last edited by

              https://www.backtrader.com/docu/timemgmt/

              1 Reply Last reply Reply Quote 0
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