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    valid= is not working for sell orders.

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    • Jinwook Jang
      Jinwook Jang last edited by

      Hello,

      I'm trying to submit LIMIT sell orders and I want them to be expired at the end of the day.
      I was trying to that by using this code. (I put "hours=1" to test code to see whether the order expires in one hour for now. )

      self.sell(price=self.position.price*1.1,exectype=bt.Order.Limit,valid=(datetime.datetime.now()+datetime.timedelta(hours=1)),size=self.position.size)

      But they are not expiring. Maybe it's related to TimeFrame. Maybe it's related to "runonce=False".

      Here is the full code.

      # -*- coding: utf-8 -*-
"""
Spyder Editor

This is a temporary script file.
"""

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 math

# Import the backtrader platform
import backtrader as bt

#Spyder plot problem. https://community.backtrader.com/topic/1911/cerebro-plot-does-not-work-with-anaconda-ipython/4
#import backtrader.plot
#import matplotlib
#matplotlib.use('QT5Agg')
# code
#cerebro.plot(iplot=False)

import backtrader.plot
import matplotlib
matplotlib.use('QT5Agg')

# Create a Cash Pool Indicator
# Dynamic indicators
# https://www.backtrader.com/blog/posts/2018-02-06-dynamic-indicator/dynamic-indicator/
class CashPool(bt.Indicator):
    lines = ('cash_pool',)

    def __init__(self):
        #print('CashPool Indicator: __init__')
        #setting to zero for now. 
        self._cashpool = 0
        self._tradeopen = False

    #Indicating whether there is a open position.
    def tradeopen(self,yesno):
        #print('CashBalance Indicator: tradeopen')
        self._tradeopen = yesno
        
    def setcashbalance(self,cashpool):
        #print('CashBalance Indicator: setting cash pool')
        self._cashpool = cashpool

    def next(self):
        #print('CashPool Indicator: next')
        if self._tradeopen:
            self.lines.cash_pool[0] = self.lines.cash_pool[-1] 
            #print('Cash Pool (tradeopen) %.2f' % self.lines.cash_pool[0])
        else :
            self.lines.cash_pool[0] = self._cashpool
            #print('Cash Pool (tradeopen=no) %.2f' % self.lines.cash_pool[0])


            
            
# Create a Stratey

class IB_v1(bt.Strategy):
    params = (
    ('division', 30.0),
    ('printlog', False),
    )
    
    def log(self, txt, dt=None):
        ''' Logging function fot this strategy'''
        dt = dt or self.datas[0].datetime.datetime(0)
        #vol = self.datas[0].volume
        print('%s, %s' % (dt.isoformat(), txt))

    def __init__(self):
        print('strategy init')
        # Keep a reference to the "close" line in the data[0] dataseries
        self.dataclose = self.datas[0].close

        # To keep track of pending orders
        self.order = None

        # creating CashBalance indicator. 
        # This keeps track of the balance. 
        self.cp = CashPool()
        
        #setting cash balance
        #The cash is set from the main program. 
        self.cp.setcashbalance(self.broker.getcash())
        
        #Two different buying target
        #one at less than average. 
        #one at below 1.05*average
        self.buytarget_avg = 0
        self.buytarget_aboveavg = 0

    def notify_order(self, order):
        if order.status in [order.Submitted, order.Accepted]:
            # Buy/Sell order submitted/accepted to/by broker - Nothing to do
            print("orders submitted/accepted")
            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' % order.executed.price)
                self.log('BUY EXECUTED size, %.2f' % order.executed.size)
                self.log('Average price %.2f' % self.position.price)
            elif order.issell():
                self.log('SELL EXECUTED, %.2f' % order.executed.price)
                self.log('SELL EXECUTED size, %.2f' % order.executed.size)

            self.bar_executed = len(self)

        elif order.status in [order.Canceled, order.Margin, order.Rejected]:
            self.log('Order Canceled/Margin/Rejected')

        # Write down: no pending order
        self.order = None
        if self.position.size == 0:
            #print('%.2f' % self.position)
            print('size %.2f' % self.position.size)
            print('price %.2f' % self.position.price)
            #self.cp.tradeopen(self.position.size, self.broker.getcash())

    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:
            
            #Check wether you can do the IB
            if self.cp[0]/self.params.division/2 >= self.dataclose[-1]:
                #print("yes! we can do this")
                
              
                #At 3:00(15:00) EST check the price of the target. 
                if self.data.datetime.time() == datetime.time(15,00):
                    print("yes! we are doing this.")
                    self.log('Close, %.2f' % self.dataclose[0])
                    #print('cnt %.2f' % math.ceil(self.cp[0]/self.dataclose[0]/self.params.division) )
                    self.log('BUY submitting, %.2f' % math.ceil(self.cp[0]/self.dataclose[0]/self.params.division))
                    #print('price %.2f' % self.dataclose[0])
                    self.buy(size=math.ceil(self.cp[0]/self.dataclose[0]/self.params.division))
           
        # Ok. now we are starting. 
        else:
           #At 3:00(15:00) EST check the price of the target. 
           if self.data.datetime.time() == datetime.time(15,00): 
               #Buy some shares.
               if self.dataclose[0] <= self.position.price:
                   #buy x/2 amount if the price is below average
                   self.buy(size=math.ceil(self.cp[0]/self.dataclose[0]/self.params.division/2))
                   self.log('BUY submitting, %.2f' % math.ceil(self.cp[0]/self.dataclose[0]/self.params.division/2))
               elif self.dataclose[0] <= self.position.price*1.05:
                   #buy x/2 amount if the price is below 1.05*average
                   self.buy(size=math.floor(self.cp[0]/self.dataclose[0]/self.params.division/2))
                   self.log('BUY submitting, %.2f' % math.floor(self.cp[0]/self.dataclose[0]/self.params.division/2))
               else:
                   print("Not buying this time.")
                   
           #Now we are selling shares if the price is above 10% of average purchase price. 
           #I'm putting order at 9:30AM
           #this is hourly data. 9:30 does not work. 
           #It seems bt.Oder.DAY does not work. Use "0" instead. 
           if self.data.datetime.time()  == datetime.time(9,00):
               #print("putting a sell order")
               #print("current position %d" % self.getposition().size)
               if self.position.size > 0:
                   self.sell(price=self.position.price*1.1,exectype=bt.Order.Limit,valid=(datetime.datetime.now()+datetime.timedelta(hours=1)),size=self.position.size)
                   #self.log('SELL submitting, %.2f' % self.position.price*1.1)
                   self.log('SELL submitting, %.2f' % self.position.size)
            
                    #if self.dataclose[0] <
                #self.buy(size=math.ceil(self.cp[0]/self.dataclose[-1]/self.params.division/2),price=self.dataclose[0])
                #self.buy(size=math.floor(self.cp[0]/self.dataclose[-1]/self.params.division/2),price=self.dataclose[-1]*1.05)
"""
            # Not yet ... we MIGHT BUY if ...
            if self.dataclose[0] < self.dataclose[-1]:
                    # current close less than previous close

                    if self.dataclose[-1] < self.dataclose[-2]:
                        # previous close less than the previous close

                        # BUY, BUY, BUY!!! (with default parameters)
                        self.log('BUY CREATE, %.2f' % self.dataclose[0])

                        # Keep track of the created order to avoid a 2nd order
                        self.order = self.buy()
"""
#        else:
"""
            # Already in the market ... we might sell
            if len(self) >= (self.bar_executed + 5):
                # SELL, SELL, SELL!!! (with all possible default parameters)
                self.log('SELL CREATE, %.2f' % self.dataclose[0])

                # Keep track of the created order to avoid a 2nd order
                self.order = self.sell()
"""
        

if __name__ == '__main__':
    # Create a cerebro entity
    # To create a dynamic indicator "runonce=Fale" is required. 
    cerebro = bt.Cerebro(runonce=False)

    # Add a strategy
    cerebro.addstrategy(IB_v1)

    # Datas are in a subfolder of the samples. Need to find where the script is
    # because it could have been called from anywhere
    modpath = os.getcwd()
    datapath = os.path.join(modpath, 'data/TQQQ/TQQQ_1min.txt')
    #datapath = 'C:/Users/jinwo/OneDrive/BackTrader/data/TQQQ/TQQQ_1hour_sample.txt'
    
    
    # Create a Data Feed
    data = bt.feeds.GenericCSVData(
        dataname=datapath,
        # Do not pass values before this date
        fromdate=datetime.datetime(2021, 8, 2),
        # Do not pass values before this date
        todate=datetime.datetime(2021, 9, 1),
        # Do not pass values after this date
        openinterest = -1,
        #This is required to have non-daily data.
        #There is no hourly time frame
        #https://community.backtrader.com/topic/309/hourly-bars/4?_=1639874160786
        timeframe=bt.TimeFrame.Minutes,
        #compression = 60,
        reverse=False)

    # Add the Data Feed to Cerebro
    cerebro.adddata(data)

    # Set our desired cash start
    cerebro.broker.setcash(10000.0)

    # Add a FixedSize sizer according to the stake
    cerebro.addsizer(bt.sizers.FixedSize, stake=10)

    # Set the commission
    cerebro.broker.setcommission(commission=0.0)

    # 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())

    # Plot the result
    cerebro.plot(iplot=False,style='candlestick')
      Jinwook Jang 1 Reply Last reply Reply Quote 0
      • Jinwook Jang
        Jinwook Jang @Jinwook Jang last edited by

        @jinwook-jang I think there is a bug. I copied the one of the example from the Quickstart. (It's plotting example.) I only changed a few lines to test Limit order with "valid=". It's clear the sell orders does not expire.

        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.plot
import matplotlib
matplotlib.use('QT5Agg')

# Create a Stratey
class TestStrategy(bt.Strategy):
    params = (
        ('maperiod', 15),
    )

    def log(self, txt, dt=None):
        ''' Logging function fot this strategy'''
        dt = dt or self.datas[0].datetime.datetime(0)
        print('%s, %s' % (dt.isoformat(), txt))

    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

        # Add a MovingAverageSimple indicator
        self.sma = bt.indicators.SimpleMovingAverage(
            self.datas[0], period=self.params.maperiod)

        # Indicators for the plotting show
        bt.indicators.ExponentialMovingAverage(self.datas[0], period=25)
        bt.indicators.WeightedMovingAverage(self.datas[0], period=25,
                                            subplot=True)
        bt.indicators.StochasticSlow(self.datas[0])
        bt.indicators.MACDHisto(self.datas[0])
        rsi = bt.indicators.RSI(self.datas[0])
        bt.indicators.SmoothedMovingAverage(rsi, period=10)
        bt.indicators.ATR(self.datas[0], plot=False)

    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')

        # Write down: no pending order
        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[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:

            # Not yet ... we MIGHT BUY if ...
            if self.dataclose[0] > self.sma[0]:

                # BUY, BUY, BUY!!! (with all possible default parameters)
                self.log('BUY CREATE, %.2f' % self.dataclose[0])

                # Keep track of the created order to avoid a 2nd order
                self.order = self.buy()

        else:

            if self.dataclose[0] < self.sma[0]:
                # SELL, SELL, SELL!!! (with all possible default parameters)
                self.log('SELL CREATE, %.2f' % self.dataclose[0])

                # Keep track of the created order to avoid a 2nd order
                #self.order = self.sell()
                self.order = self.sell(price=self.position.price*1.1,exectype=bt.Order.Limit,valid=datetime.datetime.now() + datetime.timedelta(minutes=30),size=self.position.size)


if __name__ == '__main__':
    # Create a cerebro entity
    cerebro = bt.Cerebro()

    # Add a strategy
    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
    modpath = os.path.dirname(os.path.abspath(sys.argv[0]))
    datapath = os.path.join(modpath, 'data/yfinance/TQQQ/TQQQ.csv')

    # Create a Data Feed
    data = bt.feeds.YahooFinanceCSVData(
        dataname=datapath,
        # Do not pass values before this date
        fromdate=datetime.datetime(2021, 7, 2),
        # Do not pass values before this date
        todate=datetime.datetime(2021, 12, 10),
        # Do not pass values after this date
        sessionend=datetime.time(17, 30),
        reverse=False)

    # Add the Data Feed to Cerebro
    cerebro.adddata(data)

    # Set our desired cash start
    cerebro.broker.setcash(100000.0)

    # Add a FixedSize sizer according to the stake
    cerebro.addsizer(bt.sizers.FixedSize, stake=10)

    # Set the commission
    cerebro.broker.setcommission(commission=0.0)

    # 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())

    # Plot the result
    cerebro.plot(iplot=False,style='candlestick')
        Jinwook Jang 1 Reply Last reply Reply Quote 0
        • Jinwook Jang
          Jinwook Jang @Jinwook Jang last edited by

          @jinwook-jang I think I found the problem. I think it's my code. datetime.datetime.now() is giving wrong expiration date.

          1 Reply Last reply Reply Quote 1
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