So let's say I have two factors, A and B. I want to do:
(A.rank() + B.rank()).zscore()
The problem is that because there's a lot more NaNs in B than in A, the ranks for B are always smaller. How do make it so the ranks are comparable? i.e the top rank for both factors will always be the same. Is there some way I can filter out NaNs, maybe by keeping only the stocks that have no NaNs for every factor and then ranking? Thanks!
Certainly the 'cleanest' way to ensure you are ranking equally is to do as suggested and filter out any securities with a nan value in either A or B. This would create the same 'pool' of securities for each factor. The ranks then would be more comparable. This could be done something like this
a_and_b_are_finite = A.isfinite() & B.isfinite()
(A.rank(method='max', mask=a_and_b_are_finite) + B.rank(method='max', mask=a_and_b_are_finite)).zscore()
It's a good practice to use the isfinite() method rather than notnan() with zscores and ranks. Infinite values don't always play nicely with these methods so best to filter those out too. Using the mask parameter in this way will only rank those securities that have 'rankable' or finite values. Also note the use of the method parameter. This determines how tied values are handled. The default is 'ordinal' where each security is given a distinct rank, corresponding to the order that the values occur. The order is typically just by SID. Not very meaningful. Moreover, the values are probably independent. If two are the same then they should be assigned the same rank? My preference is to use the 'max' method. For info on the various options check out the scipy rankdata docs.
Good luck.
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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.
In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.
