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VWAP indicator - session/day based



  • Hello Everyone,

    Backtrader is a wonderful platform, I'm am very grateful to the author and the community.

    I was looking for vwap indicator and some implementations are already posted in this forum by @bigdavediode. Its a nice and crisp four line code, which calculates the Volume weighted average price for a given period.

    Problem

    I wanted to have a vwap which was specific to particular session ( I believe this is what al charting platforms are using ). Meaning when the session starts in the morning vwap period has to be 1 and increased there after for every new candle. ( For example 15 minutes candle data

    Time period
    9:00 1
    9:15 2
    9:30 3
    ..

    and so on.. and when next day/session starts period is reset and starts with 1 again. One need to calculate cumulative and volume and price.

    Approach

    First we need a flag to reset the period every session. This can be done using Timers. We also need to change the period within the indicator so that its dynamic. Luckily backtrader already had a framework dynamic indicators. We have to use renounce=False in cerebro otherwise it wont work.

    Working Code
    Im very new to Backtrader, please be kind if I made mistakes and Im sure code can be improved so much better

    '''
    Author: B. Bradford 
    Dynamic vwap: Rajan Prabu
    
    MIT License
    
    Copyright (c) B. Bradford
    
    Permission is hereby granted, free of charge, to any person obtaining a copy
    of this software and associated documentation files (the "Software"), to deal
    in the Software without restriction, including without limitation the rights
    to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
    copies of the Software, and to permit persons to whom the Software is
    furnished to do so, subject to the following conditions:
    
    The above copyright notice and this permission notice shall be included in all
    copies or substantial portions of the Software.
    
    That they contact me for shipping information for the purpose of sending a 
    local delicacy of their choice native to whatever region they are domiciled.
    
    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
    IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
    FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
    AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
    LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
    OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
    SOFTWARE.
    
    
    from __future__ import (absolute_import, division, print_function,
                            unicode_literals)
    import datetime  # For datetime objects
    import pandas as pd  # for reading data
    import backtrader as bt
    import backtrader.indicators as btind
    
    class vwap(bt.Indicator):
    
        ''' This indicator needs a timer to reset the period to 1 at every session start
            also it needs a flag in next section of strategy to increment the self._vwap_period 
            run cerebro with runonce=False as we need dynamic indicator'''
    
        plotinfo = dict(subplot=False)
    
        alias = ('VWAP', 'VolumeWeightedAveragePrice','vwap',)
        lines = ('VWAP','typprice','cumprice', 'cumtypprice',)
        plotlines = dict(VWAP=dict(alpha=1.0, linestyle='-', linewidth=2.0, color = 'magenta'))
    
        def __init__(self):
            self._vwap_period = 1
            
        def vwap_period(self, period):
            self._vwap_period = period
            
    
        def next(self):
            
            self.l.typprice[0] = ((self.data.close + self.data.high + self.data.low)/3) * self.data.volume
            self.l.cumtypprice[0] = sum(self.l.typprice.get(size=self._vwap_period), self._vwap_period)
            self.cumvol = sum(self.data.volume.get(size=self._vwap_period), self._vwap_period)
            self.lines.VWAP[0] = self.l.cumtypprice[0] / self.cumvol
    
            #super(vwap, self).__init__()
    
    # Create a Stratey
    class strat(bt.Strategy):
        params = dict( 
            vwap_period = 1,
            when = bt.timer.SESSION_START,
        )
    
        def __init__(self):
        
            self.vwap = vwap(self.data) # get VWAP 
    
            self.add_timer(
                    when=self.p.when,
                )
    
        def notify_timer(self, timer, when, *args, **kwargs):
            self.vwap_period = 1
            
        def next(self):
            
            ## Use the method insread of changing param
            self.vwap.vwap_period (self.vwap_period) 
    
            ##  print values for diagnostics
            txt = list()
            txt.append('{}'.format(len(self.data0)))
            txt.append('{}'.format(self.data.datetime.datetime(0)))
            txt.append('{}'.format(self.data.close[0]))
            txt.append('{}'.format(self.vwap[0]))
            txt.append('{}'.format(self.vwap_period))
            #print(', '.join(txt))  
    
            # Increment the Period
            self.vwap_period += 1
           
          
    ## Setup cerebro 
    cerebro = bt.Cerebro() 
    
    ## Add a strat
    cerebro.addstrategy (strat)
    
    ## input data file 
    data_file = 'Nifty_combined_contracts_10_min.csv'
    
    # Create a Data Feed and add to cerebro
    df = pd.read_csv(data_file, header=0,  index_col=0, parse_dates=True)
    data0 = bt.feeds.PandasData(dataname=df, \
        name = "nifty", \
        timeframe=bt.TimeFrame.Minutes, \
        compression=5, \
        sessionstart=datetime.time(9, 15), \
        sessionend=datetime.time(15, 30), \
        openinterest=-1, \
        fromdate=datetime.datetime(2020, 1, 1),\
        todate=datetime.datetime(2020, 1, 28)
        ) 
    
    # add data
    cerebro.adddata(data0)
    
    ## Run it with runonce=False 
    cerebro.run(runonce=False)
    
    # Plot the data
    cerebro.plot(style="candlestick")
    
    

    I have used some from @bigdavediode and modified it for the purpose ( I have included his license agreement on top ). In case you like and use the code please buy me a beer ;-) ( @Munich-DE )

    It would be very helpful to get comments and improvements. Thanks


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