Bonsoir, je suis encore en train d'apprendre à utiliser la libraire Backtrader et mon code ne possède pas de réelle problème en soit mais ne m'affiche pas les résultats espérés.
J'ai mis une stratégie banale qui se base sur le croisement d'un SMA (période = 20) avec un autre SMA (période = 200).
Je vous explique le but: lorsque le SMA de 20 croise le SMA de 200 en venant du haut (crossdown), un ordre de vente doit être exécuté, et inversement, lorsque le SMA de 20 croise le SMA de 200 en venant du bas (crossup), un ordre d'achat doit être exécuté.
Et mon problème et que les achats et ventes ne sont pas exécutés selon cette stratégie, car en regardant le moment du crossup ou du crossdown quasi aucun ordre n'est exécuté au bon moment.
Voilà mon code:
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', 20), ('printlog', True), ) def log(self, txt, dt=None, doprint=False): ''' Logging function fot this strategy''' if self.params.printlog or doprint: 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) self.sma200 = bt.indicators.SimpleMovingAverage(self.datas[0], period=200) self.price = self.datas[0] self.crossup = bt.indicators.CrossUp(self.sma, self.sma200) self.crossdown = bt.indicators.CrossDown(self.sma, self.sma200) 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.crossup: balance = float(self.broker.getcash()) tp = 0.02 * balance / (0.002 * self.price) sl = 0.01 * balance / (0.002 * self.price) long_sl_price = self.price * (1 - sl) long_tp_price = self.price * (1 + tp) # 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_bracket(limitprice=long_tp_price, stopprice=long_sl_price, exectype=bt.Order.Market, price=self.price) elif self.crossdown: balance = float(self.broker.getcash()) tp = 0.02 * balance / (0.002 * self.price) sl = 0.01 * balance / (0.002 * self.price) short_sl_price = self.price * (1 + sl) short_tp_price = self.price * (1 - tp) self.order = self.sell_bracket(limitprice=short_tp_price, stopprice=short_sl_price, exectype=bt.Order.Market, price=self.price) else: self.order = None else: if self.order: return def stop(self): self.log('(MA Period %2d) Ending Value %.2f' % (self.params.maperiod, self.broker.getvalue()), doprint=True) if __name__ == '__main__': # Create a cerebro entity cerebro = bt.Cerebro() # Add a strategy strats = cerebro.optstrategy( TestStrategy, maperiod=range(10, 31)) # 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, '../../datas/orcl-1995-2014.txt') # Create a Data Feed cerebro = bt.Cerebro() cerebro.addstrategy(TestStrategy) data = bt.feeds.GenericCSVData( dataname='BTCUSDT_15m.csv', fromdate=datetime.datetime(2021, 7, 1), todate=datetime.datetime(2021, 8, 1), datetime=0, open=1, high=2, low=3, close=4, volume=5, openinterest=-1 ) # Add the Data Feed to Cerebro cerebro.adddata(data) # Set our desired cash start cerebro.broker.setcash(1000.0) # Add a FixedSize sizer according to the stake cerebro.addsizer(bt.sizers.FixedSize, stake=0.002) # Set the commission cerebro.broker.setcommission(commission=0.0) # Run over everything cerebro.run(maxcpus=1) cerebro.plot(style='candlestick')

Et voici aussi une image du graph avec entouré en vert là où un achat aurait dû être créé et en rouge inversement :

Pour ceux qui sont familiers avec cette librairie, merci d'avance pour vos réponses.