[BUG]Optimize trading strategies with automated grid search

microplc commented 2 years ago

Problem description

Example

from fastquant import backtest
from fastquant import get_stock_data
df = get_stock_data("JFC", "2018-01-01", "2019-01-01")
print(df.head())
res = backtest("smac", df, fast_period=range(15, 30, 3), slow_period=range(40, 55, 3), verbose=False)
print(res[['fast_period', 'slow_period', 'final_value']].head())

[*100%***] 1 of 1 completed

1 Failed download:

JFC: Data doesn't exist for startDate = 1514736000, endDate = 1546272000 close dt
2018-01-03 255.4 2018-01-04 255.0 2018-01-05 255.0 2018-01-08 256.0 2018-01-09 255.8

ValueError Traceback (most recent call last) ~\AppData\Local\Temp/ipykernel_11872/3110964883.py in 3 df = get_stock_data("JFC", "2018-01-01", "2019-01-01") 4 print(df.head()) ----> 5 res = backtest("smac", df, fast_period=range(15, 30, 3), slow_period=range(40, 55, 3), verbose=False) 6 print(res[['fast_period', 'slow_period', 'final_value']].head())

~\AppData\Local\Programs\Python\Python39\lib\site-packages\fastquant\backtest\backtest.py in backtest(strategy, data, commission, init_cash, plot, fractional, verbose, sort_by, sentiments, strats, return_history, return_plot, channel, symbol, allow_short, short_max, figsize, multi_line_indicators, data_class, data_kwargs, plotkwargs, fig, **kwargs) 236 print("=============================================") 237 print("Plotting backtest for optimal parameters ...") --> 238 , fig = backtest( 239 strategy, 240 data,

~\AppData\Local\Programs\Python\Python39\lib\site-packages\fastquant\backtest\backtest.py in backtest(strategy, data, commission, init_cash, plot, fractional, verbose, sort_by, sentiments, strats, return_history, return_plot, channel, symbol, allow_short, short_max, figsize, multi_line_indicators, data_class, data_kwargs, plot_kwargs, fig, **kwargs) 204 # clock the start of the process 205 tstart = time.time() --> 206 stratruns = cerebro.run() 207 208 # clock the end of the process

~\AppData\Local\Programs\Python\Python39\lib\site-packages\backtrader\cerebro.py in run(self, **kwargs) 1125 # let's skip process "spawning" 1126 for iterstrat in iterstrats: -> 1127 runstrat = self.runstrategies(iterstrat) 1128 self.runstrats.append(runstrat) 1129 if self._dooptimize:

~\AppData\Local\Programs\Python\Python39\lib\site-packages\backtrader\cerebro.py in runstrategies(self, iterstrat, predata) 1291 self._runonce_old(runstrats) 1292 else: -> 1293 self._runonce(runstrats) 1294 else: 1295 if self.p.oldsync:

~\AppData\Local\Programs\Python\Python39\lib\site-packages\backtrader\cerebro.py in _runonce(self, runstrats) 1693 1694 for strat in runstrats: -> 1695 strat._oncepost(dt0) 1696 if self._event_stop: # stop if requested 1697 return

~\AppData\Local\Programs\Python\Python39\lib\site-packages\backtrader\strategy.py in _oncepost(self, dt) 303 304 self.lines.datetime[0] = dt --> 305 self._notify() 306 307 minperstatus = self._getminperstatus()

~\AppData\Local\Programs\Python\Python39\lib\site-packages\backtrader\strategy.py in _notify(self, qorders, qtrades) 611 for analyzer in itertools.chain(self.analyzers, self._slave_analyzers): 612 analyzer._notify_cashvalue(cash, value) --> 613 analyzer._notify_fund(cash, value, fundvalue, fundshares) 614 615 def add_timer(self, when,

~\AppData\Local\Programs\Python\Python39\lib\site-packages\backtrader\analyzer.py in _notify_fund(self, cash, value, fundvalue, shares) 162 child._notify_fund(cash, value, fundvalue, shares) 163 --> 164 self.notify_fund(cash, value, fundvalue, shares) 165 166 def _notify_trade(self, trade):

~\AppData\Local\Programs\Python\Python39\lib\site-packages\backtrader\analyzers\drawdown.py in notify_fund(self, cash, value, fundvalue, shares) 91 if not self._fundmode: 92 self._value = value # record current value ---> 93 self._maxvalue = max(self._maxvalue, value) # update peak value 94 else: 95 self._value = fundvalue # record current value

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

Expected behavior

Environment

platform (e.g. Linux, OSX, Windows):
fastquant version (e.g. 0.1.3.17)
installation method (e.g. pip, conda, source):

YASHGUPTA2611 commented 2 years ago

is your query resolved?? Please help me, i'm also stuck while optimizing my strategy

mikeejazmines commented 2 years ago

Hi @microplc , this can be fixed by adding plot=False Plot will cause errors given that the result will be the final returns of multiple strategies as seen below

So plotting will cause an error. The new backtest line should be:

res = backtest("smac", df, fast_period=range(15, 30, 3), slow_period=range(40, 55, 3), verbose=False, plot=False) and it should work

@YASHGUPTA2611 let me know if this fixes your issue as well. if not, please share your code block

YASHGUPTA2611 commented 2 years ago

@microplc Thanks for the reply and yeah it works. Thank You

mikeejazmines commented 2 years ago

Happy to help @YASHGUPTA2611 !

@microplc let me know if this fixes your case as well

YASHGUPTA2611 commented 2 years ago

Yes. it worked. ThankYou!

mikeejazmines commented 2 years ago

Closing issue as fix is provided above. Please comment if issue persists

enzoampil / fastquant