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New Video: Learn from the Experts Ep 3: Building Sector-Specific Factors with Leo

In this video, Quantopian community member Leo M walks through his algorithm creation process with Quantopian’s Dr. Thomas Wiecki. This video starts with a short interview about Leo’s background in the ad-tech space and continues with Leo walking through an example algorithm he created on Quantopian.

With a background in computer science and an affinity for mathematics and problem solving, Leo shows how he’s put his skills to use on the Quantopian platform. He also gives an explanation of the reasoning behind his decisions, allowing you to walk away with a better understanding of how financial algorithms work and a starting point for creating your own.

Check out our latest challenge here, where you can test out your skills and submit for a chance to win cash prizes or an opportunity to get your factor licensed.

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7 responses

Attached is the notebook I used.

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This notebook can be used to measure factor correlations. Combining factors around different dimensions provides lower correlation and results in higher sharpe ratio and a more robust combined factor.

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The paper that I discussed in the video: "Quality Minus Junk: Clifford S. Asness, Andrea Frazzini, and Lasse H. Pedersen"

Other papers that have references to a lot of factors (in the appendix section at the end)
1) "Factor Momentum Everywhere∗ Tarun Gupta and Bryan Kelly"
2) "Taming the Factor Zoo: A Test of New Factors - Guanhao Feng, Stefano Giglio, Dacheng Xiu"

I find these factors a good starting point for experimentation in the research environment as discussed in the video.

Thank you for the interview, @Leo M and @Thomas Wiecki. It's very inspiring! "what you learn from your own research is more valuable to you than someone else's". Couldn't agree more. All the best in your endeavors.

thank you very much!

Thanks Leo and Thomas. Very instructive and helpful!

Thank for sharing your thoughts with the community. As a newbie on this platform, I actually did not understand how you were able to build your algos to minimize risk and increasing sharpe by tailoring the different factors to the different sectors in which they do well.

My guess would be, you try a bunch of factors, check the returns on the different sectors using Alphalens. And then you combine factors that perform well in different sectors?