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Variable Selection for Portfolio Choice YACINE AT-SAHALIA and MICHAEL W. BRANDT*
 

Summary: Variable Selection for Portfolio Choice
YACINE AT-SAHALIA and MICHAEL W. BRANDT*
ABSTRACT
We study asset allocation when the conditional moments of returns are partly
predictable. Rather than first model the return distribution and subsequently char-
acterize the portfolio choice, we determine directly the dependence of the optimal
portfolio weights on the predictive variables. We combine the predictors into a
single index that best captures time variations in investment opportunities. This
index helps investors determine which economic variables they should track and,
more importantly, in what combination. We consider investors with both expected
utility ~mean variance and CRRA! and nonexpected utility ~ambiguity aversion
and prospect theory! objectives and characterize their market timing, horizon ef-
fects, and hedging demands.
THERE IS BY NOW AMPLE EVIDENCE in the literature that the means, variances,
covariances, and higher order moments of stock and bond returns are time-
varying and predictable. However, it has proven difficult to translate this evi-
dence of predictability into practical portfolio advice because the different
moments of returns, which in turn determine the optimal portfolio weights,
are typically predicted by different sets of economic variables. Perhaps
because of this difficulty with modeling the conditional return distribution,

  

Source: At-Sahalia, Yacine - Program in Applied and Comptutational Mathematics & Department of Economics, Princeton University

 

Collections: Mathematics