Signals are not generating on intraday one minute data

Ramesh Gangappa

Wanted to generate cross over signals on one minute data from csv file.
Used panda dataframe to extract the data.

Need help

Thanks
Ramesh

backtrader

Unbelievable as it may seem ... one cannot quote where your error is ... because quoting images is impossible.

But if you look at the chart you will see that the data is 1-Day which means you haven't told the platform (hence the broker also not) that your data is 1-Minute

Read: Backtrader Community - FAQ - timeframe/compression - https://community.backtrader.com/topic/381/faq

Ramesh Gangappa

Thanks a lot, now data is set to 1-Minute.
Signals are generating but it is displaying out of the boundary, how can I set signal position near to price or cross over.

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 backtrader.feeds as btfeeds
import pandas as pd
import random
import json


# Import the backtrader platform
import backtrader as bt


class PandasData(btfeeds.DataBase):

  params = (
    ('fromdate', datetime.datetime(2019, 12, 6)),
    ('todate', datetime.datetime(2019, 12, 10)),
    ('nullvalue', 0.0),
    ('dtformat', ('%Y-%m-%dT%H:%M:%S%z')),
    #('tmformat', ('%H.%M.%S')),
    ('timeframe', bt.TimeFrame.Minutes),
    ('datetime', 0),
    ('open', 1),
    ('high', 2),
    ('low', 3),
    ('close', 4),
    ('volume', 5),
    ('openinterest', -1)
) 

# 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.date(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()


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, './BANKNIFTY19DECFUT.csv')

    dataframe = pd.read_csv(datapath,
                                skiprows=0,
                                header=0,
                                parse_dates=True,
                                index_col=0)
    
    data = bt.feeds.PandasData(dataname=dataframe,
                        name='BANKNIFTY',
                        fromdate=datetime.datetime(2019, 12, 6),
                        todate=datetime.datetime(2019, 12, 9),

                        timeframe=bt.TimeFrame.Minutes, compression=1,
                        sessionstart=datetime.time(9, 0), sessionend=datetime.time(16, 0)
    )
    print(dataframe)
    # Add the Data Feed to Cerebro
    cerebro.adddata(data)

    # Broker
    cerebro.broker = bt.brokers.BackBroker(**eval('dict(' + args.broker + ')'))


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

    # Add a FixedSize sizer according to the stake
    cerebro.addsizer(bt.sizers.FixedSize, stake=1)

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

    #print(cerebro.broker.getposition(data=None, broker=None))
    # 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(start=datetime.date(2019, 12, 6), end=datetime.date(2019, 12, 10))

backtrader

@Ramesh-Gangappa said in Signals are not generating on intraday one minute data:

Signals are generating but it is displaying out of the boundary

No. They are being displayed according to the default configuration (there has to be one) and your data has a low variability, which doesn't cope well with the defaults.

@Ramesh-Gangappa said in Signals are not generating on intraday one minute data:

how can I set signal position near to price or cross over.

You read this and disable the default configuration (stdstats=True) and manually add the BuySell observer with your desired configuration (i.e.: no distance to execution price)

Docs - Observers and Statistics - https://www.backtrader.com/docu/observers-and-statistics/observers-and-statistics/

Or you change the plotting configuration to let the observer influence the y-axis scale

Docs - Plotting - https://www.backtrader.com/docu/plotting/plotting/ - See plotylimited