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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)


1. How do you get the exposure matrix Xt?

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.

Some exposures can be estimated by linear regression on historical data, if you already have a time series which approximates the factor returns. E.g. exposure to the market factor (beta) is estimated this way, by regressing each stock against the S&P 500 (or some other index)

This also works for "macro" factors e.g. you can estimate exposures for each stock to commodity prices, exchange rates, interest rates, GDP or inflation surprises etc by regressing stock returns against the relevant historical time series.

Finally you can have exposures which are heuristically derived from other observable data about the stock, e.g. accounting data, analyst reports, past price movements etc. In this case you find some metric which measures the factor you care about (e.g. price to earnings) and
Thread of some posts about diversity & inclusion I've written over the years. I still stand behind these.

(I'm resharing bc a few folks are suggesting Jeremy's CoC experience ➡️ partially our fault for promoting diversity, we should change our values, etc. Nope!)

1/

Math & CS have been my focus since high school/the late 90s, yet the sexism & toxicity of the tech industry drove me to quit. I’m not alone. 40% of women working in tech leave. (2015)

https://t.co/NGNSxnnAdt 2/

Superficial, showy efforts at diversity-washing are more harmful than doing nothing at all. Research studies confirm this (2015)

https://t.co/1t6T4LKqiA 3/

The primary reason women leave the tech industry is because they are treated unfairly, underpaid, less likely to be fast-tracked, and not given a fair chance to advance. (2016)

https://t.co/NkVc5Yseo9 4/

Diversity Crisis in AI, 2016 (written the week we publicly launched fast ai, this has been a core value from the start): https://t.co/hejGQTHGwU

Diversity Crisis in AI, 2017 edition: https://t.co/Owwt8C14yh 5/