Suppose that we are searching for the maximum of many unknown and analytically untractable quantities or, say, the "best alternative" among several candidates. If our decision is based on historical or simulated data there is some sort of selection bias and it is not evident if our choice is...

"This book is refreshing, innovative and important for several reasons. Perhaps most importantly, it attempts to reconcile game theory with one-person decision theory by viewing a game as a collection of one-person decision problems. As natural as this approach may seem, it is hard to find game...

Traditional portfolio optimization has been often criticized since it does not account for estimation risk. Theoretical considerations indicate that estimation risk is mainly driven by the parameter uncertainty regarding the expected asset returns rather than their variances and covariances....

In this paper, we derive two shrinkage estimators for the global minimum variance portfolio that dominate the traditional estimator with respect to the out-of-sample variance of the portfolio return. The presented results hold for any number of observations d + 2 and number of assets d 4. The...

In the context of modern portfolio theory, we compare the out-of-sample performance of 8 investment strategies which are based on statistical methods with the out-of-sample performance of a family of trivial strategies. A wide range of approaches is considered in this work, including the...