![]() In addition, the material offers no opinion with respect to the suitability of any security or specific investment. The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by Quantopian. May want to implement in a notebook first to view the results and verify they are doing what you want. The pandas documentation has some examples. You will need to specify the weighting decay as desired. One can also do something similar but using daily pipeline data and the ExponentialWeightedMovingAverage factor ( ). # The exponentially weighted coefficient of variation # adjust the weighting with any of the ewm parameters as desiredĮwma = hist_spy.ewm(span=1).mean().iat One can get exponentially weighted values by using the pandas ewmmethod ( ).
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