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Even more interestingly, if you are not just a risk manager but a quant equity pm, you can take expectations and get a model for the expected return (or alpha) of each stock in terms of the expected returns on each factor --pic.twitter.com/JflXE3Qj8V
If you're doing this you would normally treat some factors as "risk" factors which have zero expectation (i.e. you want to hedge them to minimise risk) and some factors as "alpha" factors which have positive expectation, as well as risk --
you want exposure to the alpha factors, but you want *more* exposure to the ones which have higher expected return given the risk, and your factor model gives you a structured way to express that.
The vector of alphas, and the stock covariance matrix, are the key inputs to a portfolio optimizer (along with transaction costs, financing costs, position and turnover constraints, risk constraints etc). One particularly important fact is that portfolio optimizers are
known to behave *really* badly (recommending nonsense portfolios) when there is noise in the covariance matrix. You get noise when you try to estimate too many parameters from too little data, so using a factor model to reduce the number of parameters to estimate
is a critical step to take before you even consider using a portfolio optimizer (or some other method of reducing noise, but a factor model is the most common).
Lots of directions to take this but I think that's enough for now. There are many others who know a lot about this -- let me know if I missed anything important @choffstein @alphaarchitect @CliffordAsness?
I answered some follow-up questions herehttps://twitter.com/macrocephalopod/status/1356915582050979841?s=20 …
And more on how this might be used at a big multi-manager "pod shop" hedge fund here --https://twitter.com/macrocephalopod/status/1357089641548111872?s=20 …
They’re different (but related) problems. A quant equity pm cares about finding factors with high alpha relative to their risk. A risk manager at a pod shop cares about finding factors with high risk but relatively low alpha, to hedge them and maximise exposure to the
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