Program details - Day 3


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What are the advantages of separating modeling and estimation in LFM’s?
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Systematic condition for non-parametric regression LFM’s
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The geometry of random variables – expectation covariance ellipsoid
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Interpretation of the loadings in LFM’s
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Does lack of interpretability of PCA make it less applicable than regression LFM’s?
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Real-world application of regression LFM’s
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PCA vs systematic-idiosyncratic LFM’s
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Conditional expectation as best predictor
(*) only mentioned in class, all details provided in the ARPM Lab
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