Indicators/Strategies/Analyzers

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  How to create pyfolio round trip tearsheet?
  • Arun Lama  

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  @run-out said in How to create pyfolio round trip tearsheet?: e value Hi @run-out I tried the QuantStats repo with your strategy, but I had an error: Traceback (most recent call last): File "main.py", line 14, in <module> print(backtest(crypto)) File "/Users/benjamincherion/Desktop/backtesting-cryptos/backtest.py", line 66, in backtest print(qs.stats.sharpe(analyzer)) File "/Users/benjamincherion/Library/Python/3.7/lib/python/site-packages/quantstats/stats.py", line 234, in sharpe returns = _utils._prepare_returns(returns, rf, periods) File "/Users/benjamincherion/Library/Python/3.7/lib/python/site-packages/quantstats/utils.py", line 200, in _prepare_returns elif data.min() >= 0 and data.max() > 1: AttributeError: 'dict' object has no attribute 'min' the output of your strategy (to inject in QuantStats) is the following one: { datetime.datetime(2020, 4, 29, 0, 0): (100000.0, 100000.0), datetime.datetime(2020, 4, 29, 4, 0): (100000.0, 100000.0), ... datetime.datetime(2020, 8, 1, 0, 0): (811.8994327605933, 110828.6750226959) } is it possible to provide an example ? Thanks a lot !
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  Bitcoin trading strategy
  • Levent Yilmaz  

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  Hey @jeff-lee would love to get some feedback on the trading logic? Would really appreciate your insight. def __init__(self): self.dataclose = self.datas[0].close self.datavolume = self.datas[0].volume self.datalow = self.datas[0].low self.sma_veryfast = btind.MovingAverageSimple(self.dataclose, period=10) self.sma_fast = btind.MovingAverageSimple(self.dataclose, period=20) self.sma_mid = btind.MovingAverageSimple(self.dataclose, period=50) self.sma_slow = btind.MovingAverageSimple(self.dataclose, period=100) self.sma_veryslow = btind.MovingAverageSimple(self.dataclose, period=200) # BollingerBandsWidth = upperband - lowerband/middleband. self.bbw = BollingerBandsW() self.boll = btind.BollingerBands(self.dataclose) self.std = btind.StdDev(self.bbw.l.bbw, period=100) self.lines_bbw = (self.boll.l.top - self.boll.l.bot) / self.boll.l.mid self.volatility_level = VolatilityLevel() self.low_volatility_level = self.volatility_level.l.VLI_fast < self.volatility_level.l.VLI_slow self.high_volatility_level = self.volatility_level.l.VLI_fast > self.volatility_level.l.VLI_slow self.extreme_volatility_level = self.bbw.l.bbw > self.volatility_level.l.VLI_top self.vol_condition = (btind.MovingAverageSimple(self.datavolume, period=10) > btind.MovingAverageSimple(self.datavolume, period=50)) self.crossdown_boll_top = bt.ind.CrossDown(self.dataclose, self.boll.top) self.crossup_boll_bot = bt.ind.CrossUp(self.dataclose, self.boll.bot) self.highest_high = btind.Highest(self.dataclose, period=20) self.low_of_last_candle = self.datalow[0] self.close_of_price = self.dataclose[0] self.stop_win = None self.stop_loss = None self.order = None @staticmethod def get_params(): return dict() def notify_order(self, order): if order.status in [order.Submitted, order.Accepted]: return if order.status == order.Completed: if order.isbuy(): self.stop_loss = self.stop_loss if self.stop_loss else 0.05 * self.dataclose[-1] take_profit = order.executed.price * (1.0 + self.stop_loss) sl_ord = self.sell(exectype=bt.Order.Stop, price=order.executed.price * (1.0 - self.stop_loss)) sl_ord.addinfo(name="Stop") tkp_ord = self.buy(exectype=bt.Order.Limit, price=take_profit) tkp_ord.addinfo(name="Prof") if self.stop_win: self.sell(price=(order.executed.price * (1 + self.stop_win)), exectype=bt.Order.Limit) self.order = None def _next(self): if self.order: return if self.crossdown_boll_top and self.vol_condition: if self.close_of_price > self.sma_fast: if self.bbw.bbw < self.volatility_level.l.VLI_top: if self.low_volatility_level: if self.sma_mid > self.sma_veryslow: self.buy() else: self.buy() elif self.sma_slow > self.sma_veryslow: self.buy() self.stop_loss = self.low_of_last_candle if self.crossup_boll_bot and self.vol_condition: self.close() self.stop_loss = None self.stop_win = None portfolio_value = self.broker.get_value() trade_profit = self.broker.get_value([self.data]) / portfolio_value if trade_profit > 0.03: self.stop_win = 0.01 elif trade_profit > 0.20: self.stop_win = 0.15 elif trade_profit > 0.25: self.stop_win = 0.20 elif trade_profit > 0.30: self.stop_win = 0.25 elif trade_profit > 0.35: self.stop_win = 0.30 elif trade_profit > 0.40: self.stop_win = 0.35 if self.crossup_boll_bot and self.vol_condition: self.sell() self.stop_loss = self.highest_high
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  How to pass a list of dicts to optstrategy?
  • soulmachine  

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  @ab_trader Good idea, I'll try it, thanks!
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  How to handle multi-products with different date range?
  • nash_hk  

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  @ab_trader Not sure if this is an issue since I did this a long time ago.... But when i was putting in stocks for an asx200 analysis going back a long time, some of the stocks didn't have data either at the beginning or the end. I had to at the time use pandas to fill in the beginning and ends with zeros before passing this into backtrader. Again, I was pretty green with backtrader then so not sure if this practice is necessary or not.
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  ZigZag based on Close Prices
  • Martin Bouhier  

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  @Martin-Bouhier said in ZigZag based on Close Prices: Input("Reversal",0,100,5); Hi Martin, I would suspect that you're either not using the same input data (ie. a moving average or smoother that is smaller and finer in the Metastock formula) or that the "percentage" input involves specifying a retracement perhaps before it counts as a peak or valley in that zig zag routine. Also I'm curious to know what the 5 in the "reversal" params specifies. I don't like that python version. If there are repeated values at a peak, for example such as 200, 201, 201, 199, then it's possible for the code to entirely miss a peak. Good luck.
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  Share my implementation of the trend following strategy in the book "Following the trend" by Andreas Clenow
  • soulmachine  

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  Typo: alias = ('ClenowTrendFollowing',)
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  Issues in run a strategy
  • Pedro Ivo Paulo da Conceição  

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  @Pedro-Ivo-Paulo-da-Conceição said in Issues in run a strategy: i'm new here and learning how to use this lib. I would recommend you to start with the Quickstart Guide and samples in the Docs in this case, not with the fancy complex solutions of advanced coders.
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  Execute an order at a particular price
  • Sajil Nair  

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  In real life orders are executed by certain rules, bt simulates real life at its best. I've already gave you a link to types of orders, here is another link to Docs - Orders - Creation/Execution. You can choose type of order which will give you desirable results.
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  Use the EMA for ATR instead of the SmoothMovingAverage ?
  • Dallascat  

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  Yes, thank you!!
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  Possible to pass and return a dataframe to a strategy?
  • mapesd  

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  @mapesd Hey, Just to provide an example, strategy1 = cerebro.run() st = strategy1[0] # To return something back from the strategy - df = st.params.results # Will return your df back. st.params.midmaperiod # will return back 20 and so on.
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  Why buy/sell orders are not issued
  • Rok Petric  

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  @Eduardo-De-La-Garza I don't think so.
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  Event driven backtest issue
  • Tsz Chun Leung  

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  Thank you very much run-out. I think it helps!
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  Custom Indicator RVI; float division by zero
  • Paul Park  

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  Thank you, thats exactly what I needed. Didn't realize backtrader had this function.
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  Differing CCI Outputs bta-lib vs Backtrader.Indicators
  • jonrogers6  

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  No one has replied

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  Sharpe ratio with seconds-resolution data
  • benmercerdev  

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  There's a current thread on this topic here
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  Disable plotting backtrader.indicator.PivotPoint
  • servantfox  

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  Did you try this? The indicator will try to automatically plo to the non-resampled data. To disable this behavior use the following during construction: _autoplot=False
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  Get Highest and Lowest value of first 15 Minutes data
  • avinash  

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  @Eduardo-De-La-Garza said in Get Highest and Lowest value of first 15 Minutes data: Can you explain that line of code? When would they not be different?Thanks! One minute date, checking for new date at the beginning of the day. :)
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  How to use two CommissionInfo inside a strategy?
  • soulmachine  

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  @soulmachine said in How to use two CommissionInfo inside a strategy?: Since data has only one name, so it's not possible to apply multiple commission fees? You're probably right. AFAIK a single commission could be specified per data name or default. As @run-out correctly mentioned - you may develop your custom commission scheme.
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  SQN indicator for regime shifts
  • Jens Halsberghe  

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  @Jens-Halsberghe But in next(), you get a single OHLC bar which is a plain Python object, you can use math.log in def next()
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  Problem with crossovers
  • Sajil Thamban  

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  There is no mistake, so no need to fix anything. Crossover is registered by bt at the time when it can be registered in real life.