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Hourly indicator with intraday strategy doesnt trade
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I'm creating a strategy that i want it to use 1m or 5m candles to trade -to make it more realistic-.
Trades will happen if price touches from above to 1h and 4h Vidya lines.Problem is if i use 30m or 1h datafeeds to buy or sell it trades. But smaller timeframes like 1m and 5m creates lesser trades.
I couldnt find the source of the problem.
Below the full code and some result examples with different used timeframes.What can be the problem?
Start date: 01.01.2021
End date: 01.06.2021import backtrader as bt import backtrader.analyzers as btanalyzers from Vidya import Vidya import math from PrintAnalyzers import printTradeAnalysis, printSQN from utils import size_by_percent from get_binance_data import get_data TF1 = '5m' TF2 = '1h' class VidyaTouchStrategy(bt.Strategy): params = dict(profit_percent=10, stop_loss_percent=5, cash_percent=10, oneplot=True) 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.startcash = self.broker.getvalue() self.inds = dict() self.orders = dict() self.winning_trades = 0 self.losing_trades = 0 for i, d in enumerate(self.datas): dn = d._name if "TF1" not in dn: self.inds[d] = dict() self.inds[d]['vidya100'] = self.vidya100 = Vidya( d, period=21) if i > 0: if self.p.oneplot: d.plotinfo.plotmaster = self.datas[0] def next(self): for i, d in enumerate(self.datas): dt, dn = self.datetime.date(), d._name # Get time and stock code if "TF1" not in dn: is_not_last = len(self) < len(d.high.array) - 3 pos = self.getposition(d).size stop_loss = self.getposition(d).price * \ (1 - self.p.stop_loss_percent / 100) if self.getposition(d).price else None take_profit = self.getposition(d).price * \ (1 + self.p.profit_percent / 100) if self.getposition(d).price else None touched_above = self.inds[d]['vidya100'].vidya[1] if is_not_last and self.inds[ d]['vidya100'].touched_above[1] else None orders = self.broker.get_orders_open() # is_same_order = any(s.price == touched_above for s in orders) is_order = len(orders) > 0 if not is_order: if not pos: # Not in the market, you can buy if touched_above and not math.isnan(touched_above): stake_size = size_by_percent( percent=self.p.cash_percent, current_price=touched_above, current_cash=self.broker.get_cash()) self.buy(data=d, size=stake_size, exectype=bt.Order.Limit, price=touched_above, ) # take profit elif pos and is_not_last and take_profit <= d.high[0]: self.close(data=d) elif pos and is_not_last and take_profit <= d.high[1]: self.close(data=d, exectype=bt.Order.Limit, price=take_profit, ) # stoploss elif pos and is_not_last and stop_loss >= d.low[0]: self.close(data=d) elif pos and is_not_last and stop_loss >= d.low[1]: self.close(data=d, exectype=bt.Order.Limit, price=stop_loss, ) def notify_trade(self, trade): dt = self.data.datetime.date() if trade.isclosed: print('#######{} {} price {} Closed: PnL Gross {}, Net {}#######\n'.format( dt, trade.data._name, round(trade.price, 2), round(trade.pnl, 2), round(trade.pnlcomm, 2))) if round(trade.pnlcomm, 2) > 0: self.winning_trades += 1 else: self.losing_trades += 1 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 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)) else: # Sell self.log('SELL EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' % (order.executed.price, order.executed.value, order.executed.comm)) # elif order.status in [order.Canceled, order.Margin, order.Rejected]: # self.log('Order Canceled/Margin/Rejected') def stop(self): pnl = round(self.broker.getvalue() - self.startcash, 2) print('Profit Percent: {} Stop-loss Percent: {} Final PnL: {}'.format( self.p.profit_percent, self.p.stop_loss_percent, pnl, )) print( f"Total Trades: {self.winning_trades + self.losing_trades}\n Winning Trades: {self.winning_trades} \n Losing Trades: {self.losing_trades}") tickers = [ 'BTCUSDT', # 'ETHUSDT', # 'ADAUSDT', # 'LINKUSDT', # 'SOLUSDT', # 'ZILUSDT', ] for ticker in tickers: cerebro = bt.Cerebro() df = get_data(ticker, TF1) data = bt.feeds.PandasData( dataname=df, timeframe=bt.TimeFrame.Minutes, compression=1) cerebro.adddata(data, name=ticker+"TF1") df2 = get_data(ticker, TF2) data2 = bt.feeds.PandasData(dataname=df2) cerebro.adddata(data2, name=ticker+"TF2") cerebro.addstrategy(VidyaTouchStrategy) cerebro.broker.setcash(100000) cerebro.broker.setcommission(commission=0.001) cerebro.addobserver(bt.observers.Trades) cerebro.addobserver(bt.observers.BuySell) cerebro.addanalyzer(btanalyzers.SharpeRatio, _name="sharpe") cerebro.addanalyzer(btanalyzers.TradeAnalyzer, _name="trade") back = cerebro.run(stdstats=False) print(cerebro.broker.getvalue()) printTradeAnalysis(back[0].analyzers.trade.get_analysis()) print(back[0].analyzers.sharpe.get_analysis()) cerebro.plot(style='candle')Result for 5m and 1h timeframes:
Total trades: 1every time pre_load consume time :12.597188472747803 2021-01-10, BUY EXECUTED, Price: 35919.11, Cost: 10000.00, Comm 10.00 2021-01-11, SELL EXECUTED, Price: 37237.67, Cost: 10000.00, Comm 10.37 #######2021-01-11 BTCUSDTTF2 price 35919.11 Closed: PnL Gross 367.09, Net 346.72####### Profit Percent: 10 Stop-loss Percent: 5 Final PnL: 346.72Result for 15m and 1h timeframes:
Total trades: 6every time pre_load consume time :5.127857685089111 2021-01-10, BUY EXECUTED, Price: 35919.11, Cost: 10000.00, Comm 10.00 2021-01-11, SELL EXECUTED, Price: 37237.67, Cost: 10000.00, Comm 10.37 #######2021-01-11 BTCUSDTTF2 price 35919.11 Closed: PnL Gross 367.09, Net 346.72####### 2021-01-15, BUY EXECUTED, Price: 35228.91, Cost: 10034.67, Comm 10.03 2021-01-20, SELL EXECUTED, Price: 34875.87, Cost: 10034.67, Comm 9.93 #######2021-01-20 BTCUSDTTF2 price 35228.91 Closed: PnL Gross -100.56, Net -120.53####### 2021-01-25, BUY EXECUTED, Price: 32764.47, Cost: 10022.62, Comm 10.02 2021-01-26, SELL EXECUTED, Price: 32062.32, Cost: 10022.62, Comm 9.81 #######2021-01-26 BTCUSDTTF2 price 32764.47 Closed: PnL Gross -214.79, Net -234.62####### 2021-01-29, BUY EXECUTED, Price: 32041.32, Cost: 9999.16, Comm 10.00 2021-01-29, SELL EXECUTED, Price: 35245.45, Cost: 9999.16, Comm 11.00 #######2021-01-29 BTCUSDTTF2 price 32041.32 Closed: PnL Gross 999.92, Net 978.92####### 2021-01-29, BUY EXECUTED, Price: 34028.14, Cost: 10097.05, Comm 10.10 2021-01-31, SELL EXECUTED, Price: 32862.65, Cost: 10097.05, Comm 9.75 #######2021-01-31 BTCUSDTTF2 price 34028.14 Closed: PnL Gross -345.83, Net -365.68####### 2021-05-19, BUY EXECUTED, Price: 33725.16, Cost: 10060.48, Comm 10.06 Profit Percent: 10 Stop-loss Percent: 5 Final PnL: 1551.55Result for 1m and 1h timeframes:
Total trades: 0every time pre_load consume time :50.99492526054382 Profit Percent: 10 Stop-loss Percent: 5 Final PnL: 0.0 -
Start date: 01.01.2019
End date: 01.06.2021Result for 30m and 1h timeframes:
Total trades: 2every time pre_load consume time :17.86236882209778 2019-01-10, BUY EXECUTED, Price: 3819.86, Cost: 10000.00, Comm 10.00 2019-01-10, SELL EXECUTED, Price: 3726.32, Cost: 10000.00, Comm 9.76 #######2019-01-10 BTCUSDTTF2 price 3819.86 Closed: PnL Gross -244.87, Net -264.63####### 2019-01-20, BUY EXECUTED, Price: 3590.40, Cost: 9973.54, Comm 9.97 2019-01-28, SELL EXECUTED, Price: 3479.01, Cost: 9973.54, Comm 9.66 #######2019-01-28 BTCUSDTTF2 price 3590.4 Closed: PnL Gross -309.42, Net -329.06####### Profit Percent: 10 Stop-loss Percent: 5 Final PnL: -593.69