I travel internationally and need the ability to run Backtrader strategies from anywhere (where there's Internet access ;-) Does anyone have any recent experience simply running Backtrader strategies on a Chromebook under Crostini???
Speed is not a concern, connectivity to brokers and data feeds are.
All strategy development work will be done on another platform.
Unless I get some negative feedback from someone I'll probably try it and report back on this thread.
Thanks,
For code/output blocks: Use ``` (aka backtick or grave accent) in a single line before and after the block. See: http://commonmark.org/help/
Y
Latest posts made by Yulem
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Running Backtrader on a Chromebook under Crostini?posted in General Code/Help
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RE: Final SELL order not created in Quickstart Examplesposted in General Discussion
Sorry, the code is what is reproduced in the Quickstart examples, exactly, except for the code I included.
Here's the output:. . . 2020-06-23, Close, 157.42 2020-06-23, BUY CREATE, 157.42 2020-06-24, BUY EXECUTED, Price: 157.91, Cost: 1579.10, Comm 0.00 2020-06-24, Close, 153.15 2020-06-24, SELL CREATE, 153.15 2020-06-25, SELL EXECUTED, Price: 155.77, Cost: 1579.10, Comm 0.00 2020-06-25, OPERATION PROFIT, GROSS -21.40, NET -21.40 2020-06-25, Close, 155.00 2020-06-26, Close, 151.40 2020-06-29, Close, 153.62 2020-06-30, Close, 155.89 2020-06-30, BUY CREATE, 155.89 2020-07-01, BUY EXECUTED, Price: 158.04, Cost: 1580.40, Comm 0.00 2020-07-01, Close, 156.80 2020-07-02, Close, 157.42 . . . 2020-08-25, Close, 173.74 2020-08-26, Close, 175.31 2020-08-27, Close, 175.73 2020-08-28, Close, 176.95 Final Portfolio Value: 100528.34Here's the Quickstart example:
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 # 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, 'data/Sector ETFs/VTI.csv') # Create a Data Feed data = bt.feeds.GenericCSVData( dataname=datapath, # Do not pass values before this date fromdate=datetime.datetime(2019, 1, 1), # Do not pass values before this date todate=datetime.datetime(2020, 8, 31), # Do not pass values after this date reverse=False, #Fix DateTime format dtformat= '%Y-%m-%d', close = 6) # 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() -
Final SELL order not created in Quickstart Examplesposted in General Discussion
I'm learning Backtrader by following the examples in Quickstart Guide.
The only modifications I've made to the examples are in the data feed and broker.setcash (increased to cover orders). The problem is that in all the examples up through "Customizing the Strategy: Parameters " everything works as I expect and matches the example outputs (except for values since I'm using a different data set).
When I test the "Adding an indicator" code it generates a BUY order but no SELL order is generated upon exit leaving me with an open position. I believe the logic is to generate a SELL using the final day's CLOSE value which makes sense and is what I saw in the previous examples. What am I missing???
Below are the changes to the data feed that I made.# 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/Sector ETFs/VTI.csv') # Create a Data Feed data = bt.feeds.GenericCSVData( dataname=datapath, # Do not pass values before this date fromdate=datetime.datetime(2019, 1, 1), # Do not pass values before this date todate=datetime.datetime(2020, 8, 31), # Do not pass values after this date reverse=False, #Fix DateTime format dtformat= '%Y-%m-%d', close = 6)``` code_textThanks for your help in advance.