It should be runonce=True plays the tricks in my previous backtest :(

Lexar, having a minute bar from 10:59 go back in time to generate a result at 10:00 is a good way to make a system that won't work.

Awesome!

@ab_trader great call, dude! I didn't know about this StopLimit order Thank you very much!

@ab_trader You were right , I needed to access it like: self.datas[0].datetime.time(0)

@vladisld Thank you! So is compression only used when resampling data? not when reading first from the csv?

this is not a backtrader issue, but mostly a btoandav20 issue or something with your strategy. do you store the position size somewhere? but without some workable code I cannot help you that much with your issues.

@run-out alright... I think I got it! class Win_Buy(bt.Strategy): params = (("period", 5),) 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): self.risk = 0.01 self.diff = self.data - self.data(-1) self.win_record = self.data(0) > self.data(-1) self.prob_win = bt.ind.SumN(self.win_record, period=self.p.period) self.prob_loss = self.p.period - self.prob_win self.wins = bt.ind.SumN( bt.If(self.diff >= 0, self.diff, 0), period=self.p.period) self.losses = bt.ind.SumN( bt.If(self.diff <0, -self.diff,0), period=self.p.period) self.avg_win = bt.DivByZero(self.wins, self.prob_win, 0) self.avg_loss = bt.DivByZero(self.losses, self.prob_loss, 0) self.avg_risk = bt.ind.Average(self.data.close*self.risk, period=self.p.period) def next(self): self.dsharpe = self.avg_win[0] / (self.avg_risk[0]) if self.dsharpe > 1: # previous close less than the previous close # BUY, BUY, BUY!!! (with all possible default parameters) self.log('BUY CREATE, %.2f' % self.data[0]) self.buy() else: pass With Prints... 2018-01-09, c 24.37 diff 0.02, winr 1.00, pwin 3.00, ploss 2.00, wins 0.25, plosses 0.14, avg_win 0.08, avg_loss 0.07, avg_risk 0.24, DSHAREP 0.34 2018-01-10, c 24.25 diff -0.12, winr 0.00, pwin 2.00, ploss 3.00, wins 0.12, plosses 0.26, avg_win 0.06, avg_loss 0.09, avg_risk 0.24, DSHAREP 0.25 2018-01-11, c 24.32 diff 0.07, winr 1.00, pwin 2.00, ploss 3.00, wins 0.09, plosses 0.26, avg_win 0.05, avg_loss 0.09, avg_risk 0.24, DSHAREP 0.18 2018-01-12, c 24.34 diff 0.02, winr 1.00, pwin 3.00, ploss 2.00, wins 0.11, plosses 0.18, avg_win 0.04, avg_loss 0.09, avg_risk 0.24, DSHAREP 0.15 2018-01-15, c 24.40 diff 0.06, winr 1.00, pwin 4.00, ploss 1.00, wins 0.17, plosses 0.12, avg_win 0.04, avg_loss 0.12, avg_risk 0.24, DSHAREP 0.17 2018-01-16, c 24.31 diff -0.09, winr 0.00, pwin 3.00, ploss 2.00, wins 0.15, plosses 0.21, avg_win 0.05, avg_loss 0.11, avg_risk 0.24, DSHAREP 0.21 2018-01-17, c 24.35 diff 0.04, winr 1.00, pwin 4.00, ploss 1.00, wins 0.19, plosses 0.09, avg_win 0.05, avg_loss 0.09, avg_risk 0.24, DSHAREP 0.20 Does this seem right? Also if I just wanted to use DSharpe as a bt.Indicator would i just change the class from Strategy to Indicator? and the purchase metrics?

Can you include the error message please?

I fixed the issue with oanda broker. It will now assume, there is no stopside

@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

https://mrjbq7.github.io/ta-lib/func_groups/pattern_recognition.html Here you go. Since ta lib is supported you should be able to use them with ta lib in backtrader

Oh alright. I am using Dave Vallance bt-ccxt-store, it must be there the problem lies I know bitmex only delivers ohlc candles of 1m through their api. I was wondering if you could loop to get the live price faster/the last candle but then I know thats where to look for that solution. Thank you, for the response!

@J-T from your code examples, it is not clear what you are doing. in a strategy, you could do the following: self.sizer = btoandav20.sizers.OandaV20Risk(risk_percents=2, stoploss=10) print(self.sizer.getsizing(data=self.data0, isbuy=True)) which will work, when data is a oanda feed

@AlfredSisley said in Adding InfluxDB Datafeeds: Are you surprised by how long it takes me to run my simple skeleton backtests given my hardware? Hard to tell, can't directly compare with my local results. Usually I'm backtesting a single ticker at a time, so my mileage may vary. What's your timing for backtesting a single ticker for, say 5 - 10 years of 1 or 5 minutes bars ?

there is no need to call self.notify_order() in the next(). in order to avoid an error with bar_executed you need to operate with it only if the position exists. otherwsie use of bar_executed is meaningless. also don't post pictures, but text; please read the note about backticks on top of the page.

BT has built in 'Highest' and 'Lowest' indicators that will do this for you. https://www.backtrader.com/docu/indautoref/#highest https://www.backtrader.com/docu/indautoref/#lowest For a long time I used it wrong a received inconsistent results. This structure works for me now: import backtrader as bt import backtrader.indicators as bt.ind class TheStrategy(bt.Strategy): params = ( ('highperiod_0', 60), ('lowperiod_0', 60), ) def __init__(self): self.highest = highest = bt.ind.Highest(self.data, period=self.p.highperiod_0, plot=True, subplot=False) self.lowest = lowest = bt.ind.Lowest(self.data, period=self.p.lowperiod_0, plot=True, subplot=False) def next(self): #LONG POSITION: Breakout high when self.data.close > self.highest self.buy() #SHORT POSITION: Breakout low when self.data.close() < self.lowest self.sell You need to set the period for the number of bars you want to find the highest/lowest data for. Once you have this static high/low working, try using a dynamic indicator for something a little more complex: https://www.backtrader.com/blog/posts/2018-02-06-dynamic-indicator/dynamic-indicator/

Will sharing my trading data set Help ??

@vladisld right, everything is now fixed. I really apprexiate your help.

I found this helpful https://backtest-rookies.com/2020/05/09/backtrader-portfolio-rebalancing-with-alpha-vantage/ Thanks SJ