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As a matter of fact, Assumption 2 is natural. It is Assumption 1 that needs justification. Strictly speaking Assumption 2 is not an assumption. It is simply a corollary of the regression of $X$ against $F$. In the language of linear algebra, it is the decomposition of vector space of all $X$ into the subspace spanned by $F$ and its orthogonally ...


3

The assumptions from factor models tend to be similar to the assumptions that you see in regression. The first assumption is pretty straightforward, errors are uncorrelated with mean zero. I wouldn't say that it necessarily means that all risk factors have been captured. However, for the purposes of using the factor model, it is basically assuming that ...


2

There's always a balance between model complexity and interpretability. Of course, it'll be great if we can perfectly capture the comovement of all the bonds in the deliverable basket, but that would require the volatilities of all the bond's yields and the correlations amongst all these bonds as well -- it's not easy to come up with reliable assumptions for ...



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