There are different ways to estimate it, depending on the factor. Simplest is factors like industry or country exposure where the entries can be 0/1 depending on whether the stock is in that industry/country or not.
A few things that I didn't cover yesterday when I talked about equity factor models (it's a huge area and it's impossible to more than scrape the surface)
A few people in the DMs asking about equity factor models so here's a short explainer.
— macrocephalopod (@macrocephalopod) February 2, 2021
Let's make it a concrete problem -- you are the risk manager at a big multi-manager hedge fund with ~100 sub-PMs each of whom has a portfolio of 10-50 stocks, long and short.
There are different ways to estimate it, depending on the factor. Simplest is factors like industry or country exposure where the entries can be 0/1 depending on whether the stock is in that industry/country or not.
Now you have a set of linear equations on each day, and you can solve the linear equations to get the vector of factor returns for each day using the normal equation - pic.twitter.com/YwVkUzSM69
— macrocephalopod (@macrocephalopod) February 2, 2021
It varies depending on the application. The simplest models would have just a few, maybe the market factor plus a couple of others that you care about (think about Fama-French 3 factor or 5 factor model) but it will normally be more.
Yes -- you hear a lot about the well known ones like value, momentum quality etc but there are hundreds of others which are widely known in academia and industry and thousands of proprietary in-house factors.
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Tying Marvel’s stable of pulp-fiction heroes to a real place — New York — served a counterbalance to the sometimes gravity-challenged action and the improbability of the stories. That was just what Stan Lee wanted. https://t.co/rDosqzpP8i
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I wish I had this... — don't excuse yourself. Forget about what you can't and focus on what you can.
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BTW this was an update of one of the previous tweets. And I'm continuing this thread today!
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