@Adis-Ojeda this is because there are no tests, so there is this error.

nevermind got it to work. Thanks guys for your patience and helping me out.

As stated in the past in the previous thread, no access to VIX and no intention of having it. If it works for you...

Thanks for bearing with, I added cerebro.broker.setcommission(leverage=100) now everything works how I want it. Thanks.

@tianjixuetu I met this situation again ,and I find that the reason is that the first data may lose some bar,so,it should run many times to wait the some data to this datetime.

I had a similar problem and resolved by canceling the pending order every and then recreating it. This way there's no "weekend problem" when the order for next day is more than one day ahead. ''' def next(self): self.cancel(self.order) ... if not self.position: self.order = self.buy(price = buy_price, exectype = bt.Order.Limit) else: self.order = self.close(price = sell_price, exectype = bt.Order.Limit) '''

@ab_trader , I discovered your good tool backtrader_addons & start using it. I found a 'ZeroDivisionError: float division by zero' bug when there is no trade in a test. Below are the stacktrace for your reference. Traceback (most recent call last): File "C:/Users/john/PycharmProjects/Backtrader/venv/Include/IBPaperTrade.py", line 83, in <module> strats = cerebro.run(tradehistory=True) # for trade_list File "C:\Users\john\PycharmProjects\Backtrader\venv\lib\site-packages\backtrader\cerebro.py", line 1127, in run runstrat = self.runstrategies(iterstrat) File "C:\Users\john\PycharmProjects\Backtrader\venv\lib\site-packages\backtrader\cerebro.py", line 1301, in runstrategies TestStrategy, Bracket, 2020-06-04-030233, Strategies execution completed 0 trade with self.broker.cash=7788592.0392 and self.broker.getvalue()=7788591.99 strat._stop() File "C:\Users\john\PycharmProjects\Backtrader\venv\lib\site-packages\backtrader\strategy.py", line 486, in _stop analyzer._stop() File "C:\Users\john\PycharmProjects\Backtrader\venv\lib\site-packages\backtrader\analyzer.py", line 200, in _stop self.stop() File "C:\Users\john\PycharmProjects\Backtrader\venv\lib\site-packages\backtrader_addons-0.18.10-py3.6.egg\backtrader_addons\analyzers\limited_test_report.py", line 80, in stop self.rpt['win_percent'] = 100.0 * win_percent / len(trades) ZeroDivisionError: float division by zero

The csv data sources have had a couple of lines changed to make sure that even if someones decides to re-resample a daily timeframe to daily again, some days will not be missed.

There is no need for logic there and that's why there is none. The entry order (aka main side) is protected automatically with a stop-loss side and a take-profit side (the high/low side depends on the direction entry), which are only active if the entry order is executed. Once the stop-loss/take-profit sides become active, the execution of any of them automatically cancels the other. If you decide to exit the market with an unrelated order, you have to manually cancel any of the sides (the other will be cancelled automatically) as in self.cancel(order_stop_loss_side) # this automatically cancels the take-profit side too

@hiep-pham said in How is Getvalue() Calculated?: After spending a fair amount of time to make sense the relationship between order.executed.value vs (self.broker.getvalue() There isn't a relationship even if you look for one. One is for the order and the other is for the position. You can link them mentally, but they are not meant to be related. @hiep-pham said in How is Getvalue() Calculated?: that order.executed.value is the value of the current order position using the opening price of the NEXT period This is WRONG and this has nothing to do with broker.getvalue() order.executed.value is related to the execution price. If the execution price happens to be the opening price fine, but your definition is plainly wrong. @hiep-pham said in How is Getvalue() Calculated?: self.broker.getvalue() use the close price of the CURRENT period When you are in next, prices have already happened. The only price which can be used to calculate the last (and hence current) value is the last price, i.e.: the close

Thanks @backtrader. That will cover most cases. Maybe the SAREXT indicator should also be added? In my case I'm working with a very large datasheet so to avoid performance issues I've coded something like: def next(self): self.psar0._lookback = min(100, len(self.data0)) so I have a "dynamic" _lookback from 1 to 100 And why 100?... newbie here! just by observation, it seems to be a good value to calculate a real ParabolicSAR value.

@Wayne-Filkins perfect

@ab_trader I copied and tried optunity's 'grid search' option. What I found is that the searching term between parameter values are decided by num_evals. (High num_evals => 1..2..3..n/ Low num_evals => 1..5..10..n) That's why grid search is faster than the theory.

@backtrader Very nice! One step closer to the quality of R's Quantstrat package. Will test it soon

In my particular case line._plotvalue = False helps. Thanks for flexible solution!

@backtrader Here is the link to the new post: link text

Not at the moment

@jacob said in Indicator using multi datafeed: operate only on overlapping bar: this is a great workaround for this issue/bug. This is not a workaround. It is clearly stated in the FAQ: Community - FAQ The system cannot know which timeframe/compression your data feed has unless you tell the system.

@ab_trader @backtrader Thank you for your advises. I try to use BarReplayer_Open , but I can not understand how to use it. So I use cerebro.broker.set_coc(True), and I can get hopeful output. I put code and output in following. ・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 import backtrader.analyzers as btanalyzers import math import pandas as pd import talib import numpy as np PARAMS = ( ('maperiod', 15), #moving average period ('period', 15), # ('willperiod', 14), #moving average period ('sizer', None), ) class TestStrategy(bt.Strategy): params = PARAMS 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.order = self.order_target_percent(target=0.1) self.buyprice = None self.buycomm = None self.sma = bt.indicators.SimpleMovingAverage(self.datas[0], period=self.params.maperiod) 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 enougth cash 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) # 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 # 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() class LongOnly(bt.Sizer): params = (('stake', 1),) def _getsizing(self, comminfo, cash, data, isbuy): if isbuy: divide = math.floor(cash/data.close[0]) # divide = math.floor(cash/data.open[1]) self.p.stake = divide # print(self.p.stake) # print(math.floor(cash/data.close[0])) return self.p.stake # Sell situation position = self.broker.getposition(data) if not position.size: return 0 # do not sell if nothing is open return self.p.stake if __name__ == '__main__': cerebro = bt.Cerebro() # Add a strategy cerebro.addstrategy(TestStrategy) # Add Sizer cerebro.addsizer(LongOnly) # cerebro.broker.set_coc(True) # because it could have been called from anywhere modpath = os.path.dirname(os.path.abspath(sys.argv[0])) datapath = os.path.join('datas/orcl-1995-2014.txt') # Create a Data Feed data = bt.feeds.YahooFinanceCSVData( dataname=datapath, # Do not pass values before this date fromdate=datetime.datetime(2000, 1, 1), # Do not pass values before this date todate=datetime.datetime(2000, 12, 31), # Do not pass values after this date reverse=False) # Add the Data Feed to Cerebro cerebro.adddata(data) # Set our desired cash start cerebro.broker.setcash(100000.0) # In order to buy on open you may want to # bt.filters.BarReplayer_Open(data) cerebro.broker.set_coc(True) # 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() ・Output Starting Portfolio Value: 100000.00 2000-01-25, BUY CREATE, 26.61 2000-01-26, BUY EXECUTED, Price: 26.61, Cost: 99973.77, Comm 0.00 2000-01-27, SELL CREATE, 24.43 2000-01-28, SELL EXECUTED, Price: 24.43, Cost: 99973.77, Comm 0.00 2000-01-28, OPERATION PROFIT, GROSS -8190.26, NET -8190.26 2000-02-02, BUY CREATE, 25.61 2000-02-03, BUY EXECUTED, Price: 25.61, Cost: 91786.24, Comm 0.00 2000-02-18, SELL CREATE, 27.61 2000-02-22, SELL EXECUTED, Price: 27.61, Cost: 91786.24, Comm 0.00 2000-02-22, OPERATION PROFIT, GROSS 7168.00, NET 7168.00 2000-02-22, BUY CREATE, 27.97 2000-02-23, BUY EXECUTED, Price: 27.97, Cost: 98957.86, Comm 0.00 2000-03-30, SELL CREATE, 36.98 2000-03-31, SELL EXECUTED, Price: 36.98, Cost: 98957.86, Comm 0.00 2000-03-31, OPERATION PROFIT, GROSS 31877.38, NET 31877.38 2000-04-06, BUY CREATE, 38.75 2000-04-07, BUY EXECUTED, Price: 38.75, Cost: 130820.00, Comm 0.00 2000-04-11, SELL CREATE, 36.48 2000-04-12, SELL EXECUTED, Price: 36.48, Cost: 130820.00, Comm 0.00 2000-04-12, OPERATION PROFIT, GROSS -7663.52, NET -7663.52 2000-04-18, BUY CREATE, 37.22 2000-04-19, BUY EXECUTED, Price: 37.22, Cost: 123160.98, Comm 0.00 2000-04-19, SELL CREATE, 35.16 2000-04-20, SELL EXECUTED, Price: 35.16, Cost: 123160.98, Comm 0.00 2000-04-20, OPERATION PROFIT, GROSS -6816.54, NET -6816.54 2000-04-27, BUY CREATE, 36.45 2000-04-28, BUY EXECUTED, Price: 36.45, Cost: 116348.40, Comm 0.00 2000-05-04, SELL CREATE, 35.01 2000-05-05, SELL EXECUTED, Price: 35.01, Cost: 116348.40, Comm 0.00 2000-05-05, OPERATION PROFIT, GROSS -4596.48, NET -4596.48 2000-05-05, BUY CREATE, 36.22 2000-05-08, BUY EXECUTED, Price: 36.22, Cost: 111774.92, Comm 0.00 2000-05-08, SELL CREATE, 34.10 2000-05-09, SELL EXECUTED, Price: 34.10, Cost: 111774.92, Comm 0.00 2000-05-09, OPERATION PROFIT, GROSS -6542.32, NET -6542.32 2000-05-15, BUY CREATE, 36.31 2000-05-16, BUY EXECUTED, Price: 36.31, Cost: 105226.38, Comm 0.00 2000-05-18, SELL CREATE, 34.45 2000-05-19, SELL EXECUTED, Price: 34.45, Cost: 105226.38, Comm 0.00 2000-05-19, OPERATION PROFIT, GROSS -5390.28, NET -5390.28 2000-05-30, BUY CREATE, 34.98 2000-05-31, BUY EXECUTED, Price: 34.98, Cost: 99832.92, Comm 0.00 2000-06-22, SELL CREATE, 38.43 2000-06-23, SELL EXECUTED, Price: 38.43, Cost: 99832.92, Comm 0.00 2000-06-23, OPERATION PROFIT, GROSS 9846.30, NET 9846.30 2000-06-26, BUY CREATE, 38.99 2000-06-27, BUY EXECUTED, Price: 38.99, Cost: 109678.87, Comm 0.00 2000-06-27, SELL CREATE, 38.78 2000-06-28, SELL EXECUTED, Price: 38.78, Cost: 109678.87, Comm 0.00 2000-06-28, OPERATION PROFIT, GROSS -590.73, NET -590.73 2000-06-28, BUY CREATE, 39.11 2000-06-29, BUY EXECUTED, Price: 39.11, Cost: 109077.79, Comm 0.00 2000-06-29, SELL CREATE, 38.13 2000-06-30, SELL EXECUTED, Price: 38.13, Cost: 109077.79, Comm 0.00 2000-06-30, OPERATION PROFIT, GROSS -2733.22, NET -2733.22 2000-06-30, BUY CREATE, 39.64 2000-07-03, BUY EXECUTED, Price: 39.64, Cost: 106354.12, Comm 0.00 2000-07-03, SELL CREATE, 37.81 2000-07-05, SELL EXECUTED, Price: 37.81, Cost: 106354.12, Comm 0.00 2000-07-05, OPERATION PROFIT, GROSS -4909.89, NET -4909.89 2000-07-20, BUY CREATE, 36.84 2000-07-21, BUY EXECUTED, Price: 36.84, Cost: 101457.36, Comm 0.00 2000-07-21, SELL CREATE, 35.57 2000-07-24, SELL EXECUTED, Price: 35.57, Cost: 101457.36, Comm 0.00 2000-07-24, OPERATION PROFIT, GROSS -3497.58, NET -3497.58 2000-07-25, BUY CREATE, 35.83 2000-07-26, BUY EXECUTED, Price: 35.83, Cost: 97959.22, Comm 0.00 2000-07-27, SELL CREATE, 35.39 2000-07-28, SELL EXECUTED, Price: 35.39, Cost: 97959.22, Comm 0.00 2000-07-28, OPERATION PROFIT, GROSS -1202.96, NET -1202.96 2000-07-31, BUY CREATE, 35.45 2000-08-01, BUY EXECUTED, Price: 35.45, Cost: 96743.05, Comm 0.00 2000-08-01, SELL CREATE, 34.48 2000-08-02, SELL EXECUTED, Price: 34.48, Cost: 96743.05, Comm 0.00 2000-08-02, OPERATION PROFIT, GROSS -2647.13, NET -2647.13 2000-08-03, BUY CREATE, 36.51 2000-08-04, BUY EXECUTED, Price: 36.51, Cost: 94086.27, Comm 0.00 2000-09-08, SELL CREATE, 40.81 2000-09-11, SELL EXECUTED, Price: 40.81, Cost: 94086.27, Comm 0.00 2000-09-11, OPERATION PROFIT, GROSS 11081.10, NET 11081.10 2000-09-28, BUY CREATE, 38.42 2000-09-29, BUY EXECUTED, Price: 38.42, Cost: 105155.54, Comm 0.00 2000-09-29, SELL CREATE, 37.13 2000-10-02, SELL EXECUTED, Price: 37.13, Cost: 105155.54, Comm 0.00 2000-10-02, OPERATION PROFIT, GROSS -3530.73, NET -3530.73 2000-10-19, BUY CREATE, 34.30 2000-10-20, BUY EXECUTED, Price: 34.30, Cost: 101630.90, Comm 0.00 2000-10-30, SELL CREATE, 29.82 2000-10-31, SELL EXECUTED, Price: 29.82, Cost: 101630.90, Comm 0.00 2000-10-31, OPERATION PROFIT, GROSS -13274.24, NET -13274.24 2000-11-17, BUY CREATE, 27.17 2000-11-20, BUY EXECUTED, Price: 27.17, Cost: 88384.01, Comm 0.00 2000-11-20, SELL CREATE, 23.34 2000-11-21, SELL EXECUTED, Price: 23.34, Cost: 88384.01, Comm 0.00 2000-11-21, OPERATION PROFIT, GROSS -12458.99, NET -12458.99 2000-11-30, BUY CREATE, 24.99 2000-12-01, BUY EXECUTED, Price: 24.99, Cost: 75919.62, Comm 0.00 2000-12-14, SELL CREATE, 25.93 2000-12-15, SELL EXECUTED, Price: 25.93, Cost: 75919.62, Comm 0.00 2000-12-15, OPERATION PROFIT, GROSS 2855.72, NET 2855.72 2000-12-15, BUY CREATE, 26.93 2000-12-18, BUY EXECUTED, Price: 26.93, Cost: 78770.25, Comm 0.00 2000-12-20, SELL CREATE, 26.88 2000-12-21, SELL EXECUTED, Price: 26.88, Cost: 78770.25, Comm 0.00 2000-12-21, OPERATION PROFIT, GROSS -146.25, NET -146.25 2000-12-21, BUY CREATE, 27.82 2000-12-22, BUY EXECUTED, Price: 27.82, Cost: 78619.32, Comm 0.00 2000-12-29, SELL CREATE, 27.41 Final Portfolio Value: 77478.72

I don't know the size because I use order_target_percent.