Hi together,

I struggle around and need help: How can I use signals from indicators, like from the InvestorSentimentSurveyAlphaModel?

I guess, that I should extend the "Update" area with some kind of signal; but in addition to that: How could I use that signal afterwards for deciding "buying stocks or not"?

Thank you very much in advance!

class InvestorSentimentSurveyAlphaModel(AlphaModel): def __init__(self, algorithm): ## Add Quandl data for AAII Investor Sentiment Survey self.bullBearSpread = algorithm.AddData(QuandlData, 'AAII/AAII_SENTIMENT',Resolution.Daily).Symbol def Update(self, algorithm, data): insights = [] # Return if no data if not data.ContainsKey(self.bullBearSpread): return insights # This Alpha model uses the Bull-Bear spread from AAII Investor Sentiment Data. # A Bull-Bear spread is the difference in percentage between bullish investors and the percentage of bearish investors. # A positive Bull-Bear spread might be a leading indicator that predicts an equity market rally. # Similarly, a negative Bull-Bear spread might be a leading indicator that predicts an equity market selloff. return insights def OnSecuritiesChanged(self,algorithm,changes): ## The Quandl Symbol, self.bullBearSpread, will appear in changes.AddedSecurities pass class QuandlData(PythonQuandl): def __init__(self): ## Retrieve the data from the the Quandl object, specifying the data field used on Quandl self.ValueColumnName = "BULL-BEAR SPREAD"

 

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