Vivek Viswanathan - Quant Equity in China (S4E10)
Flirting with Models
How to Explain Under Performance in a Machine Learning Environment
The last type of factor timing that i've seen is regime switzing models. I personally have not seen this work in contests of timi they can build amazing back tests, but seem to turn into random number generators ex post. Most regime switching models i see are 90 % confident there in one regime or the other. And then you infer conditional expect o returns based on those regime states. They're way to over confident, and thus they can result in bad decision make.
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