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Hello -
Using the example code in the documentation, I've successfully created strategies such as a SMA crossover or RSI crossover, for example:
# Do as much initial computation as possible
def init(self):
self.rsi = self.I(ta.rsi, pd.Series(self.data.Close), self.rsi_window)
# Step through bars one by one
# Note that multiple buys are a thing here
def next(self):
if crossover(self.rsi, self.upper_bound):
self.position.close()
elif crossover(self.lower_bound, self.rsi):
self.buy()
That works great.
However, I seem to be unable to create one based on the Stochastic oscillator and I'm getting a "Indicators must return (optionally a tuple of) numpy.arrays of same length as data " error message.
Here is my strategy:
class StochOsc(Strategy):
upper_bound = 70
lower_bound = 30
window = 14
# Do as much initial computation as possible
def init(self):
self.stoch = self.I(ta.stoch, pd.Series(self.data.High), pd.Series(self.data.Low), pd.Series(self.data.Close),
k=self.window,d=self.window,smooth_k=self.window)
# Step through bars one by one
def next(self):
if crossover(self.stoch, self.upper_bound):
self.position.close()
elif crossover(self.lower_bound, self.stoch):
self.buy()# Do as much initial computation as possible
I then execute my strategy:
`bt = Backtest(price, StochOsc, cash=10_000, commission=.002)
stats = bt.optimize(upper_bound=range(65, 95, 1),
lower_bound=range(25,35,1),
maximize=optim_func,
constraint=lambda param: param.lower_bound < param.upper_bound)`
Upon executing the code in init it throws the above error.
I can't seem to find any examples of using ta.stoch with backtesting.py so any help would be appreciated. I can't figure out a solution based on that error message.
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