If one wished to screen a universe of stocks based on the SQLAlchemy morningstar query method, but combine an additional filter that involved a custom computation (for example ATR) on which to screen stocks further, how might this be implemented? Is there an order of operation regarding these two different methods of filtering a universe of stocks? Thanks for any feedback
Hi Brandon,
You can import certain fields from the Morningstar fundamental data as datasets into your pipeline. You can then add them as custom factors, and rank and filter securities based on these factors. See this example the calculates market cap using shares_outstanding and filters on this value.
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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.