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Rebalancing at the end of the month with timers
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I would like to rebalance on the last trading day of each month.
With timers, I'm not able to achieve this with just the "monthdays" parameter, since the day isn't fixed. So I thought about using the allow parameter to provide custom rules.
import calendar class EndOfMonth(object): def __call__(self, d): if d.day == calendar.monthrange(d.year, d.month)[1]: return True return FalseWhile I'm able to get the last day of the month this way, it doesn't work as desired since the timer callback isn't called on weekends and more importantly, holidays (because my data feeds simply don't have these dates included). This results in the monthly rebalance to be ignored for certain months.
If I could somehow know in advance that the current day is the last available day of the month, by looking at next available date in the data feed, that might work, although the data feed doesn't seem to be passed as an argument to the callback.
Does anyone know how to approach this problem? Thanks!
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You may try to use the TradingCalendar class, supplied with backtrader. It has a last_monthday method that returns true if a given trading day is a last trading day of the month.
More docs here: https://www.backtrader.com/docu/tradingcalendar/tradingcalendar/
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Thank you, that might do the trick. Although I can't quite figure out how to call the instance of the calendar inside a Strategy. Could you elaborate?
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I've got it working, here's some boilerplate code:
class EndOfMonth(object): def __init__(self, cal): self.cal = cal def __call__(self, d): if self.cal.last_monthday(d): return True return False class AssetAllocation(bt.Strategy): params = ( ('cal', None), ) def __init__(self): self.add_timer( when=bt.Timer.SESSION_START, allow=EndOfMonth(self.p.cal), ) if __name__ == '__main__': # Create a cerebro entity cerebro = bt.Cerebro() cal = bt.TradingCalendar() cerebro.addcalendar(cal) # Add a strategy cerebro.addstrategy(AssetAllocation, cal=cal)Thanks again.
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How is the above class called? I am looping through multiple symbols, and this is my final call, i'm trying to liquidate at 3:50:
if EndOfMonth and d.datetime.time() > datetime.time(15, 50) and not self.liquidated: # self.liquidate(pos_size, d) self.close(data=d, size=pos_size) self.liquidated = True print("liquidating: " + d._name + " " + str(pos_size) + " shares ")depending on how I call/implement this, I get one of 2 different errors, either it says
TypeError: init() missing 1 required positional argument: 'cal'or it says:
last_monthday() missing 1 required positional argument: 'day'.
I'm pretty stuck, any recommendations? The boilerplate is a good start but I'm totally lost now.
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This is my full strategy file, and below here is the file that is running cerebro.
Strategy:
class EndOfMonth(object): """ https://community.backtrader.com/topic/2278/rebalancing-at-the-end-of-the-month-with-timers https://www.backtrader.com/docu/tradingcalendar/tradingcalendar/ """ def __init__(self, cal): self.cal = cal def __call__(self, d): print(str(d)) if self.cal.last_monthday(d): return True # todo does this even need to return true? and false below? return False class EpicRiseCross(bt.Strategy): """Buys when the current candlestick is above the parabosil sar indicator (PSAR). Sells when the candlestick is below the psar. Has a 5% stop-loss, shaves half the position if its in profit and more than 3 bars have passed.""" # list of parameters which are configurable for the strategy params = dict(startime="09:30", totime="16:00", stop_loss=5, cal=None) # todo def __init__(self): cal = bt.TradingCalendar self.psar = dict() self.sell_half = False self.cal = bt.TradingCalendar() self.buy_bar = None self.buy_bar_check = None self.liquidated = False self.add_timer( when=bt.Timer.SESSION_START, allow=EndOfMonth(cal), ) # TODO end of month liquidate # todo do we define the self.p.cal somehow? try: self.starttime = datetime.datetime.strptime(self.p.startime, "%H:%M") self.totime = datetime.datetime.strptime(self.p.totime, "%H:%M") for i, elm in enumerate(self.datas): if 'benchmark' in self.datas[i]._name: continue self.psar[i] = bt.ind.PSAR(self.datas[i], period=2, af=0.02, afmax=0.2) # parabolic sar self.psar[i].plotlines.psar.markersize = 10.0 # self.psar[i].plotlines.psar.width = 50.0 self.psar[i].plotlines.psar.color = 'blue' except Exception as e: print(e) def logdata(self): txt = ['{}'.format(len(self)), '{}'.format(self.data.datetime.datetime(0).isoformat()), '{:.2f}'.format(self.data.open[0]), '{:.2f}'.format(self.data.high[0]), '{:.2f}'.format(self.data.low[0]), '{:.2f}'.format(self.data.close[0]), '{:.2f}'.format(self.data.volume[0]), # todo add current date? # '{:.2f}'.format(self.data.date[0]) ] # print(','.join(txt)) def notify_data(self, data, status, *args, **kwargs): """Called when the status of the data has changed, is it delayed/live/disconnected.""" print('*' * 5, 'DATA NOTIF:', data._getstatusname(status), *args) if status == data.LIVE: self.data_live = True def notify_order(self, order): """Any time an order is submitted this is called, also called on order updates.""" if order.status == order.Completed: buysell = 'BUY ' if order.isbuy() else 'SELL' txt = '{} {} @ {} {} {}'.format(buysell, order.executed.size, order.executed.price, (bt.num2date(order.executed.dt,tz=pytz.timezone("America/New_York"))),order.info.addinfo) print(txt) # print("Buying: " + str(d.datetime.time()) + " Qty: " + str(pos_size)) # current time def next(self): """Primary function that executes trades.""" self.logdata() # Loop through all symbols for i, d in enumerate(self.datas): # pos_size gets the position size, if 0 not in position, pos_size is pos_quantity""" pos_size = self.getposition(d).size if not pos_size: # not in the market if d.close[0] > self.psar[i].psar[0]: # if fast crosses slow to the upside self.sell_half = False self.buy(data=d) # buy shares # print(d._name) symbol name self.buy_bar = int(len(self)) # buy_bar sets the bar number that makes the purchase self.buy_bar_check = self.buy_bar + 3 # buy_bar_check is 3 positions later for selling half # todo the above buy_bar seems to be wrong, should we move it like pycharm recommends? # TODO should the below elif be indented? elif d.close[0] < self.psar[i].psar[0]: # and pos_size # in the market & cross to the downside self.close(data=d, size=pos_size) # sell shares print("Cross down sell: " + str(d.datetime.time()) + " Qty: " + str(pos_size)) # current time else: """Sell half of the position after 3 or more bars, then stop-loss if % is hit""" if pos_size: # check if in position # todo ADDED >= 0, this seems to have helped if len(self) >= self.buy_bar_check and not self.sell_half: # len(self) is the current bar # # print("Shaving 50% profits: " + str(d.datetime.time()) + " Qty: " + str(pos_size)) # current time self.sell(data=d, size=int(math.ceil(pos_size*0.5)), addinfo='shaving 50%') self.sell_half = True # entry price self, self.getposition(d).price is the avg share buy price stop_price = float(self.getposition(d).price) * (1.0 - (float(self.p.stop_loss)/100.00)) if d.close[0] <= stop_price: # d.close[0] i think this is the close price for EOD print("Stop Loss : " + str(d.datetime.time()) + " Qty: " + str(pos_size)) # current time self.close(data=d, size=pos_size) # todo this sells all shares on the last trading day of te month with the liquidate() function. # if self.cal.last_monthday(d.datetime.date()) and not self.liquidated: if EndOfMonth and d.datetime.time() > datetime.time(15, 50) and not self.liquidated: # self.liquidate(pos_size, d) self.close(data=d, size=pos_size) self.liquidated = True print("liquidating: " + d._name + " " + str(pos_size) + " shares ") # def liquidate(self, pos_size, d): # """This sells all the shares on the last trading day of the month at 3:50 market time.""" # if d.datetime.time() > datetime.time(15, 50) and pos_size: # self.sell(size=pos_size, data=d) # print("Liquidate - Shares sold: " + str(pos_size) + " of shares " + str(d)) # Added stop method to get values through looping with maxcpus=1 - Walter def stop(self): """Called when the backtest is finished.""" try: self.value = round(self.broker.get_value(), 2) except Exception as e: exc_type, exc_obj, exc_tb = sys.exc_info() fname = os.path.split(exc_tb.tb_frame.f_code.co_filename)[1] print(exc_type, fname, exc_tb.tb_lineno) print(e) class EpicRiseStrategy(bt.Cerebro): """Runs the backtest, optimization and walk-forward optimization. Also handles getting the variables from the parameters in the web interface, is it doing real-time etc. If the rtbar is true then its running live.""" def __init__(self, symbol, budget, perc, barsize, bartype, fromdate, todate, slippage, commission, currency, realtime, port, backtesttype, stratparams, goal, optperiod, testperiod, filename, ): try: if backtesttype == "backtest": cerebro_class = CerebroHelper(symbol, budget, perc, barsize, bartype, fromdate, todate, slippage, commission, currency, realtime, port, stratparams, EpicRiseCross) elif backtesttype == "optimize": opt = Optimizer(symbol, budget, perc, barsize, bartype, fromdate, todate, slippage, commission, currency, stratparams, EpicRiseCross, goal) else: walkforwardopt = WalkForwardOptimizer(symbol, budget, perc, barsize, bartype, fromdate, todate, slippage, commission, currency, stratparams, EpicRiseCross, goal, optperiod, testperiod,) except Exception as e: exc_type, exc_obj, exc_tb = sys.exc_info() fname = os.path.split(exc_tb.tb_frame.f_code.co_filename)[1] print(exc_type, fname, exc_tb.tb_lineno) tb = traceback.format_exc() print(tb) print(str(e))bt cerebro helper file:
class CerebroHelper(bt.Cerebro): def __init__(self, symbol,budget,perc,barsize,bartype,fromdate,todate,slippage,commission,currency,realtime,port,stratparams,strategy ): cerebro = bt.Cerebro() # create a "Cerebro" engine instance params = json.loads(json.dumps(stratparams)) params = json.loads(params) # strip first and last quotes so its valid json # Backtest if symbol != '': # TODO Port # for val in sys.argv[1:]: # if (val == '-port'): # port = int(sys.argv[idx + 2]) # Strategy Params # todo added for calendar class, but also says to add cal=cal to cerebro.addstrategy(AssetAllocation, cal=cal) cal = bt.TradingCalendar() cerebro.addcalendar(cal) cerebro.addstrategy(strategy, **params) # Add the trading strategy # Broker Params cerebro.broker.setcash(float(budget)) print(float(budget)) cerebro.broker.set_slippage_perc(float(slippage) / 100) cerebro.broker.setcommission(float(commission) / 100) cerebro.addsizer(bt.sizers.PercentSizerInt, percents=int(perc)) # Create a data feed ibstore = bt.stores.IBStore(host='127.0.0.1', port=7496) rtbar = realtime if realtime: # Live Plotting cerebro.addanalyzer(BacktraderPlottingLive, barup='green', volume=False, lookback=200, port=port) rtbar = True cerebro.broker = ibstore.getbroker() # or cerebro.setbroker(...) webbrowser.open('http://localhost:' + str(port), new=0) else: cerebro.addanalyzer(BacktraderPlottingLive, barup='green', volume=False, lookback=200) # Metrics TODO only works with backtesting, need to get working live import importlib import inspect for name, cls in inspect.getmembers(importlib.import_module("backtrader.analyzers"), inspect.isclass): if name == "SharpeRatio": try: cerebro.addanalyzer(cls, timeframe=bt.TimeFrame.Minutes, compression=60) except Exception as e: continue elif name == "Calmar": try: cerebro.addanalyzer(cls, timeframe=bt.TimeFrame.Years) except Exception as e: continue elif name != "Analyzer" and 'Auto' not in name and 'Order' not in name and 'Time' not in name and 'Gross' not in name and 'Log' not in name and 'Position' not in name and name != 'range' and 'PyFolio' not in name and 'VWR' not in name and '_' not in name: try: cerebro.addanalyzer(cls) except Exception as e: continue # Custom analyzers try: cerebro.addanalyzer(tradelist.trade_list) # MAE MFE cerebro.addanalyzer(lvratio.lv_ratio) # LV Ratio except Exception as e: print(e) # Add for loop for barsize - Walter data = None for i in range(len(barsize)): stockkwargs = dict() print(rtbar) if rtbar: stockkwargs = dict(timeframe=bt.TimeFrame.TFrame(bartype), compression=int(barsize[i]), rtbar=True, # use RealTime 5 seconds bars historical=False, # only historical download live=True, # get data from.. backfill=False, backfill_start=False, tz=pytz.timezone('US/Eastern')) # get data from.. else: stockkwargs = dict(timeframe=bt.TimeFrame.TFrame(bartype), compression=int(barsize[i]), historical=True, # only historical download qcheck=0.5, # timeout in seconds (float) to check for events fromdate=datetime.datetime.strptime(fromdate, "%Y-%m-%d").date(), # get data from.. todate=datetime.datetime.strptime(todate, "%Y-%m-%d").date(), # get data from.. tz=pytz.timezone('US/Eastern')) # get data from.. if ',' in symbol: for s in symbol.split(','): data = ibstore.getdata(dataname=str(s) + '-STK-SMART-' + currency, **stockkwargs) if isinstance(data, pd.DataFrame) and not rtbar: dataframe = data # Cached Data data = bt.feeds.PandasData(dataname=dataframe, tz=pytz.timezone('US/Eastern')) if int(int(barsize[i])) >= 4 and (int(int(barsize[i])) != 5) and ( int(int(barsize[i])) != 10) and (int(int(barsize[i])) != 15) and ( int(int(barsize[i])) != 20) and (int(int(barsize[i])) != 30) and ( int(int(barsize[i])) != 60) and (int(int(barsize[i])) != 120): initdata = cerebro.resampledata(data, timeframe=bt.TimeFrame.Minutes, compression=1) initdata.plotinfo.plot = False cerebro.resampledata(data, timeframe=bt.TimeFrame.Minutes, compression=int(barsize[i]), name=s) else: data = ibstore.getdata(dataname=str(symbol) + '-STK-SMART-' + currency, **stockkwargs) if isinstance(data, pd.DataFrame) and not rtbar: dataframe = data # Cached Data data = bt.feeds.PandasData(dataname=dataframe, tz=pytz.timezone('US/Eastern')) if bartype == "Minutes" and int(int(barsize[i])) >= 4 and (int(int(barsize[i])) != 5) and ( int(int(barsize[i])) != 10) and (int(int(barsize[i])) != 15) and ( int(int(barsize[i])) != 20) and (int(int(barsize[i])) != 30) and ( int(int(barsize[i])) != 60) and (int(int(barsize[i])) != 120): compress = 1 if int(int(barsize[i])) % 5 == 0: compress = 5 if int(int(barsize[i])) % 10 == 0: compress = 10 if int(int(barsize[i])) % 15 == 0: compress = 15 if int(int(barsize[i])) % 20 == 0: compress = 20 if int(int(barsize[i])) % 30 == 0: compress = 30 if int(int(barsize[i])) % 60 == 0: compress = 60 if int(int(barsize[i])) % 120 == 0: compress = 120 initdata = cerebro.resampledata(data, timeframe=bt.TimeFrame.Minutes, compression=compress, name=symbol) initdata.plotinfo.plot = False print(symbol) cerebro.resampledata(data, timeframe=bt.TimeFrame.Minutes, compression=int(barsize[i]), name=symbol) try: cerebro.addanalyzer(RecorderAnalyzer) if not rtbar: # Benchmark Buy and Hold cerebro.addobserver(bt.observers.Benchmark, data=data, timeframe=bt.TimeFrame.Days) # Benchmark Buy and Hold S&P stockkwargs = dict(timeframe=bt.TimeFrame.TFrame(bartype), compression=int(barsize[i]), rtbar=False, # use RealTime 5 seconds bars historical=True, # only historical download fromdate=datetime.datetime.strptime(fromdate, "%Y-%m-%d").date(), # get data from.. todate=datetime.datetime.strptime(todate, "%Y-%m-%d").date(), # get data from.. tz=pytz.timezone('US/Eastern')) # get data from.. spdata = ibstore.getdata(dataname='SPY-STK-SMART-USD', **stockkwargs) if isinstance(spdata, pd.DataFrame) and not rtbar: dataframe = spdata # Cached Data spdata = bt.feeds.PandasData(dataname=dataframe, tz=pytz.timezone('US/Eastern')) # cerebro.adddata(spdata) else: # Only resample if we have to with weird bar sizes like 4 or 6, if not IB is giving it to us right away if bartype == "Minutes" and int(int(barsize[i])) >= 4 and (int(int(barsize[i])) != 5) and ( int(int(barsize[i])) != 10) and (int(int(barsize[i])) != 15) and ( int(int(barsize[i])) != 20) and (int(int(barsize[i])) != 30) and ( int(int(barsize[i])) != 60) and (int(int(barsize[i])) != 120): compress = 1 if int(int(barsize[i])) % 5 == 0: compress = 5 if int(int(barsize[i])) % 10 == 0: compress = 10 if int(int(barsize[i])) % 15 == 0: compress = 15 if int(int(barsize[i])) % 20 == 0: compress = 20 if int(int(barsize[i])) % 30 == 0: compress = 30 if int(int(barsize[i])) % 60 == 0: compress = 60 if int(int(barsize[i])) % 120 == 0: compress = 120 initdata = cerebro.resampledata(spdata, timeframe=bt.TimeFrame.Minutes, compression=compress) initdata.plotinfo.plot = False # cerebro.resampledata(spdata, timeframe=bt.TimeFrame.Minutes, compression=int(barsize[i]), # name='SPY-benchmark') # spdata.plotinfo.plot = False # Don't plot S&P500 candlesticks # cerebro.addobserver(bt.observers.Benchmark, # data=spdata, # timeframe=bt.TimeFrame.Days) cerebro.run(tz=pytz.timezone('US/Eastern')) # run it all # todo ERROR KeyError p = BacktraderPlotting(style='bar', barup='green', volume=False, lookback=200) cerebro.plot(p) else: cerebro.run(tz=pytz.timezone('US/Eastern')) # run it all except AttributeError as e: exc_type, exc_obj, exc_tb = sys.exc_info() fname = os.path.split(exc_tb.tb_frame.f_code.co_filename)[1] print(exc_type, fname, exc_tb.tb_lineno) tb = traceback.format_exc() print(tb) print(str(e)) except Exception as e: exc_type, exc_obj, exc_tb = sys.exc_info() fname = os.path.split(exc_tb.tb_frame.f_code.co_filename)[1] print(exc_type, fname, exc_tb.tb_lineno) tb = traceback.format_exc() print(tb) print(str(e)) # self.start(symbol, True)
