Fixed upgrading matplotlib to 3.2.0
For code/output blocks: Use ``` (aka backtick or grave accent) in a single line before and after the block. See: http://commonmark.org/help/
Best posts made by Dallascat
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RE: Getting "Traceback" errors and ImportError from matplotlibposted in General Code/Help
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RE: Calculate EMA on the median ((high+low/2)) ?posted in General Code/Help
@run-out said in Calculate EMA on the median ((high+low/2)) ?:
To get a line for ema as you ask...
self.myema = bt.ind.EMA((self.datas[0].high / self.datas[0].low) /2 )Thanks, so I am getting an error:
"....bt.indicators.ExponentialMovingAverage((self.datas[0].high / self.data[0].low) /2, period=100)
AttributeError: 'float' object has no attribute 'low' "Original code for the EMA: bt.indicators.ExponentialMovingAverage(self.datas[0], period=100)
Updated to do the median: bt.indicators.ExponentialMovingAverage((self.datas[0].high / self.data[0].low) /2, period=100)
and getting that error.
Thanks for your help!
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RE: Calculate EMA on the median ((high+low/2)) ?posted in General Code/Help
@ab_trader Thanks for all your help here and a few other posts! !
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RE: Cancelling Bracket order following closing of the main sideposted in General Code/Help
@run-out Awesome thanks! I will make those changes this weekend and get back!
Latest posts made by Dallascat
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RE: Cancelling Bracket order following closing of the main sideposted in General Code/Help
@run-out If not too busy, have you had a chance to look at my code? TY!
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RE: Cancelling Bracket order following closing of the main sideposted in General Code/Help
@run-out Sure, I did get rid of the error, but not sure if I am doing the list right or not (I assume NOT, lol) because it runs, but only triggers two trades at the beginning then nothing. Thanks Again
import backtrader as bt from datetime import datetime class Strategy(bt.Strategy): def log(self, txt, dt=None): """ Logging function fot this strategy""" dt = dt or self.data.datetime[0] if isinstance(dt, float): dt = bt.num2date(dt) print("%s, %s" % (dt.date(), txt)) def __init__(self): # Keep a reference to the "close" line in the data[0] dataseries self.bar_executed = len(self) self.dataclose = self.datas[0].close # Create an order list self.o_li = list() # To keep track of pending orders and buy price/commission self.order = [] self.buyprice = None self.buycomm = None # Add EMA and TRIX self.ema = bt.indicators.ExponentialMovingAverage((self.datas[0].high + self.datas[0].low) / 2, period=100, plotname="EMAMid") self.trix = bt.indicators.TRIX(self.datas[0], period=5, plot=True) self.atr = bt.indicators.ATR(period=100, movav=bt.indicators.MovAv.Exponential) 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.Canceled, order.Margin]: if order.isbuy(): self.log("BUY FAILED, Cancelled or Margin") self.log if order.status in [order.Completed, order.Canceled, order.Margin]: 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) # Cleans up the order list. if not order.alive() and order in self.o_li: self.o_li.remove(order) 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 global price, price_limit, price_stop self.log('ATR: %.2f' % (self.atr[0])) if self.position.size == 0 and len(self.o_li) == 0: if self.ema[0] >= self.ema[-1] and (self.trix[0] >= self.trix[-1]): price = self.data.close[0] price_limit = price + self.atr[0] price_stop = price - self.atr[0] self.order = self.buy_bracket( data=self.datas[0], size=None, exectype=bt.Order.Limit, plimit=price, stopprice=price_stop, stopexec=bt.Order.Stop, limitprice=price_limit, limitexec=bt.Order.Limit, ) if self.position.size == 0 and len(self.o_li) == 0: if self.ema[0] <= self.ema[-1] and (self.trix[0] <= self.trix[-1]): price = self.data.close[0] price_limit = price - self.atr[0] price_stop = price + self.atr[0] self.order = self.sell_bracket( data=self.datas[0], size=None, exectype=bt.Order.Limit, plimit=price, stopprice=price_stop, stopexec=bt.Order.Stop, limitprice=price_limit, limitexec=bt.Order.Limit, ) # Store orders in a list self.o_li = [o for o in self.order] self.log( "LONG BUY limit Targets: Buy {:8.2f}, Target {:8.2f}, Stop {:8.2f}".format( price, price_limit, price_stop ) ) if self.position.size > 0: if self.ema[0] <= self.ema[-1] or (self.trix[0] <= self.trix[-1]): print("Sell shares at {}".format(self.data.close[0])) self.close() self.o_li = list() if self.position.size < 0: if self.ema[0] >= self.ema[-1] or (self.trix[0] >= self.trix[-1]): print("Sell shares at {}".format(self.data.close[0])) self.close() self.o_li = list() if __name__ == '__main__': # Variable for our starting cash startcash = 100000 # Create a cerebro entity cerebro = bt.Cerebro() # Add a strategy cerebro.addstrategy(Strategy) # Create a Data Feed data = bt.feeds.YahooFinanceData(dataname='AAPL', fromdate=datetime(2019, 6, 1), todate=datetime(2020, 11, 9), buffered=True) # Add the Data Feed to Cerebro cerebro.adddata(data) # Set our desired cash start cerebro.broker.setcash(startcash) # Add a FixedSize sizer according to the stake cerebro.addsizer(bt.sizers.FixedSize, stake=50) # Set the commission cerebro.broker.setcommission(commission=0.0) # Add Analyzers: cerebro.addanalyzer(bt.analyzers.SharpeRatio, _name="mySharpe", riskfreerate=0.001) cerebro.addanalyzer(bt.analyzers.Returns, _name='returns') cerebro.addanalyzer(bt.analyzers.SQN, _name='sqn') # Print out the starting conditions print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue()) # Run over everything cerebro.run() portvalue = cerebro.broker.getvalue() pnl = portvalue - startcash # Print out the final result print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue()) print('Final Portfolio Value: ${}'.format(portvalue)) print('P/L: ${}'.format(pnl)) # Plot the results cerebro.plot(style='bar', bardown='grey', barup="0.75", volume=False, grid=False)
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RE: Cancelling Bracket order following closing of the main sideposted in General Code/Help
@run-out Thanks so much for your guidance! I'm still racking my brain against the well....is the error in
# To keep track of pending orders and buy price/commission self.order = [] self.buyprice = None self.buycomm = Noneor
# Clean up the order list. if not order.alive() and order in self.o_li: self.o_li.remove(order) # Write down: no pending order self.order = Noneor none of the above . LOL! Thanks again!!
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RE: Cancelling Bracket order following closing of the main sideposted in General Code/Help
@run-out I tried to implement your suggestions, I and I know I am doing something wrong with the list. I get an error :
"line 110, in next for o in self.order:
TypeError: 'NoneType' object is not iterable"Code:
from __future__ import (absolute_import, division, print_function, unicode_literals) from datetime import datetime import backtrader as bt # Create a Strategy class TestStrategy(bt.Strategy): 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 __init__(self): # Keep a reference to the "close" line in the data[0] dataseries self.bar_executed = len(self) self.dataclose = self.datas[0].close # Create an order list self.o_li = list() # To keep track of pending orders and buy price/commission self.order = [] self.buyprice = None self.buycomm = None # Add EMAs self.ema = bt.indicators.ExponentialMovingAverage((self.datas[0].high + self.datas[0].low) / 2, period=50) self.ema2 = bt.indicators.ExponentialMovingAverage((self.datas[0].high + self.datas[0].low) / 2, period=15) self.atr = bt.indicators.ATR(period=50, movav=bt.indicators.MovAv.Exponential) 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, order.Canceled, order.Margin]: if order.isbuy(): self.log( 'BUY EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f, Size %.2f' % (order.executed.price, order.executed.value, order.executed.comm, order.executed.size)) self.buyprice = order.executed.price self.buycomm = order.executed.comm else: # Sell self.log('SELL EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f, Size %.2f' % (order.executed.price, order.executed.value, order.executed.comm, order.executed.size)) self.bar_executed = len(self) elif order.status in [order.Canceled, order.Margin, order.Rejected]: self.log('Order Canceled/Margin/Rejected') # Clean up the order list. if not order.alive() and order in self.o_li: self.o_li.remove(order) # 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): # 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: if self.ema[0] >= self.ema[-1] and (self.ema2[0] >= self.ema2[-1]): price = self.data.close[0] price_limit = price + self.atr[0] price_stop = price - self.atr[0] self.order = self.buy_bracket( data=self.datas[0], size=None, exectype=bt.Order.Limit, plimit=price, stopprice=price_stop, stopexec=bt.Order.Stop, limitprice=price_limit, limitexec=bt.Order.Limit, ) if self.ema[0] <= self.ema[-1] and (self.ema2[0] <= self.ema2[-1]): price = self.data.close[0] price_limit = price - self.atr[0] price_stop = price + self.atr[0] self.order = self.sell_bracket( data=self.datas[0], size=None, exectype=bt.Order.Limit, plimit=price, stopprice=price_stop, stopexec=bt.Order.Stop, limitprice=price_limit, limitexec=bt.Order.Limit, ) if self.position.size > 0 and (self.ema[0] <= self.ema[-1] or (self.ema2[0] <= self.ema2[-1])): self.close() for o in self.order: self.cancel(o) if self.position.size < 0 and (self.ema[0] >= self.ema[-1] or (self.ema2[0] >= self.ema2[-1])): self.close() for o in self.order: self.cancel(o) if __name__ == '__main__': # Variable for our starting cash startcash = 100000 # Create a cerebro entity cerebro = bt.Cerebro() # Add a strategy cerebro.addstrategy(TestStrategy) # Create a Data Feed data = bt.feeds.YahooFinanceData(dataname='AAPL', fromdate=datetime(2019, 6, 1), todate=datetime(2020, 11, 9), buffered=True) # Add the Data Feed to Cerebro cerebro.adddata(data) # Set our desired cash start cerebro.broker.setcash(startcash) # Add a FixedSize sizer according to the stake cerebro.addsizer(bt.sizers.FixedSize, stake=50) # Set the commission cerebro.broker.setcommission(commission=0.0) # Add Analyzers: cerebro.addanalyzer(bt.analyzers.SharpeRatio, _name="mySharpe", riskfreerate=0.001) cerebro.addanalyzer(bt.analyzers.Returns, _name='returns') cerebro.addanalyzer(bt.analyzers.SQN, _name='sqn') # Print out the starting conditions print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue()) # Run over everything cerebro.run() portvalue = cerebro.broker.getvalue() pnl = portvalue - startcash # Print out the final result print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue()) print('Final Portfolio Value: ${}'.format(portvalue)) print('P/L: ${}'.format(pnl)) # Plot the results cerebro.plot(style='bar', bardown='grey', barup="0.75", volume=False, grid=False)
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RE: Cancelling Bracket order following closing of the main sideposted in General Code/Help
@run-out Awesome thanks! I will make those changes this weekend and get back!
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RE: Cancelling Bracket order following closing of the main sideposted in General Code/Help
Sorry, I don't know why it didn't markdown the whole code.
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RE: Cancelling Bracket order following closing of the main sideposted in General Code/Help
@run-out Sure, this is just a simple strategy for my learning purposes of BT and python:
`from future import (absolute_import, division, print_function,
unicode_literals)
from datetime import datetime
import backtrader as btCreate a Strategy
class TestStrategy(bt.Strategy):
params = (('order_pct', 0.95), ("buy_price_adjust", 0.0), ("buy_limit_adjust", 0.02), ("buy_stop_adjust", 0.02))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 __init__(self): # Keep a reference to the "close" line in the data[0] dataseries self.bar_executed = len(self) self.dataclose = self.datas[0].close # Create an order list self.o_li = list() # To keep track of pending orders and buy price/commission self.order = None self.buyprice = None self.buycomm = None # Add EMA and TRIX self.ema = bt.indicators.ExponentialMovingAverage((self.datas[0].high + self.datas[0].low) / 2, period=50, plotname="EMAMid") self.ema2 = bt.indicators.ExponentialMovingAverage((self.datas[0].high + self.datas[0].low) / 2, period=15, plotname="EMAMid") self.atr = bt.indicators.ATR(period=50, movav=bt.indicators.MovAv.Exponential) # Indicators for plotting bt.indicators.ExponentialMovingAverage(self.datas[0], period=50) 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, order.Canceled, order.Margin]: if order.isbuy(): self.log( 'BUY EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f, Size %.2f' % (order.executed.price, order.executed.value, order.executed.comm, order.executed.size)) self.buyprice = order.executed.price self.buycomm = order.executed.comm else: # Sell self.log('SELL EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f, Size %.2f' % (order.executed.price, order.executed.value, order.executed.comm, order.executed.size)) self.bar_executed = len(self) elif order.status in [order.Canceled, order.Margin, order.Rejected]: self.log('Order Canceled/Margin/Rejected') # Clean up the order list. if not order.alive() and order in self.o_li: self.o_li.remove(order) # 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): # 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: if self.ema[0] >= self.ema[-1] and (self.ema2[0] >= self.ema2[-1]): price = self.data.close[0] * (1.0 - self.p.buy_price_adjust) price_limit = price + self.atr[0] price_stop = price - self.atr[0] self.long_buy_order = self.buy_bracket( data=self.datas[0], size=None, exectype=bt.Order.Limit, plimit=price, stopprice=price_stop, stopexec=bt.Order.Stop, limitprice=price_limit, limitexec=bt.Order.Limit, ) if self.ema[0] <= self.ema[-1] and (self.ema2[0] <= self.ema2[-1]): price = self.data.close[0] * (1.0 - self.p.buy_price_adjust) price_limit = price - self.atr[0] price_stop = price + self.atr[0] self.short_sell_order = self.sell_bracket( data=self.datas[0], size=None, exectype=bt.Order.Limit, plimit=price, stopprice=price_stop, stopexec=bt.Order.Stop, limitprice=price_limit, limitexec=bt.Order.Limit, ) if self.position.size > 0 and (self.ema[0] <= self.ema[-1] or (self.ema2[0] <= self.ema2[-1])): self.close() if self.position.size < 0 and (self.ema[0] >= self.ema[-1] or (self.ema2[0] >= self.ema2[-1])): self.close()if name == 'main':
# Variable for our starting cash
startcash = 100000# Create a cerebro entity cerebro = bt.Cerebro() # Add a strategy cerebro.addstrategy(TestStrategy) # Create a Data Feed data = bt.feeds.YahooFinanceData(dataname='AAPL', fromdate=datetime(2019, 6, 1), todate=datetime(2020, 11, 9), buffered=True) # Add the Data Feed to Cerebro cerebro.adddata(data) # Set our desired cash start cerebro.broker.setcash(startcash) # Add a FixedSize sizer according to the stake cerebro.addsizer(bt.sizers.FixedSize, stake=50) # Set the commission cerebro.broker.setcommission(commission=0.0) # Add Analyzers: cerebro.addanalyzer(bt.analyzers.SharpeRatio, _name="mySharpe", riskfreerate=0.001) cerebro.addanalyzer(bt.analyzers.Returns, _name='returns') cerebro.addanalyzer(bt.analyzers.SQN, _name='sqn') # Print out the starting conditions print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue()) # Run over everything cerebro.run() portvalue = cerebro.broker.getvalue() pnl = portvalue - startcash # Print out the final result print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue()) print('Final Portfolio Value: ${}'.format(portvalue)) print('P/L: ${}'.format(pnl)) # Plot the results cerebro.plot(style='bar', bardown='grey', barup="0.75", volume=False, grid=False)`
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RE: Cancelling Bracket order following closing of the main sideposted in General Code/Help
@run-out I am still fairly new to BT and python. Basically there are 3 signals generated - long, short or out. I have just learned on how to put in brackets if I want to use a PT and SL. But there are times when none of those gets hit and a signal to get out of the position hits (goes flat) and that leaves the PT and SL open if I use the brackets. So I assume I need to do it another way (issue PT and SL separately, and have them cancelled when the position == 0) instead of the brackets, unless there was a way to cancel the brackets if I went flat. Make sense?
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RE: Cancelling Bracket order following closing of the main sideposted in General Code/Help
Hi @Rumen-Nenov...did you get this figured out? I am at a similar junction you were when you wrote this. Thanks!
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RE: How to import/read CSV data?posted in General Code/Help
@vladisld Thanks for your help! Figured it out....feel a little dumb, still a n00b with BT :-)