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Analyzing Pipeline Performance In Depth

A few weeks ago, we put out a call to our user base asking for examples of algorithms using the Pipeline API that were running slowly. Our primary goals were to:

  1. Better understand whether our users were effectively using Pipelines.
  2. Better understand where the underlying Pipeline infrastructure was encountering bottlenecks.

We received several helpful submissions, which we ran through an internal benchmarking harness to analyze where time was being spent, both in user code and in Quantopian code. We learned a lot from this experience, and I wanted to share some of our results. The attached notebook includes a summary of some of our findings as well as a detailed analysis of two of the submitted algorithms. Hopefully this provides an interesting view into our some of our development process.

-Scott

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Disclaimer

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.

3 responses

Have Quantopian ExponentialWeightedMovingAverage and ExponentialWeightedMovingStdDev been already deployed to Quantopian ?

Hi Scott, I can see they are available, thanks!

An example algo using these new factors can be found here. It's the algo that was the basis for the performance profiling that Scott explains in the attached notebook earlier in this thread.

Disclaimer

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.