Using a Bayesian time‐varying beta model, we explore how the systematic risk exposures of hedge funds vary over time conditional on some exogenous variables that managers are assumed to use in changing their trading strategies. In such a setting, we impose a structure on fund returns, betas...

All the financial practitioners are working in incomplete markets full of unhedgeable risk-factors. Making the situation worse, they are only equipped with the imperfect information on the relevant processes. In addition to the market risk, fund and insurance managers have to be prepared for...

Among the 5,000 equity mutual funds in the world, more than 80 percent belong to some fund family. A fund family is a group of mutual funds supervised by the same investment group. Despite the prevalence of the family organization, previous literature, when evaluating mutual fund performance,...

We solve two optimal stopping problems whose payoff functions are the maximum and the minimum of two state variables driven by the Ornstein-Uhlenbeck processes. We consider a class of problems where we obtain analytical solutions. Furthermore, by making use of the analytical results we study...

This paper investigates dynamic correlations both across commodities and between commodities and traditional assets, such as equities and government bonds, using the Regime Switching Dynamic Correlation (RSDC) model. There are three major findings. First, results from correlations both across...

For the popular mean-variance portfolio choice problem in the case without a risk-free asset, we develop a new portfolio strategy to mitigate estimation risk. We show that in both calibrations and real datasets, optimally combining the sample global minimum variance portfolio with a sample...

Determining the optimal mix of assets in the context of a portfolio construction involves “smart” forecasts of asset returns as well as good estimates of the asset return variances and covariances. Typically, sample moments are used as best estimates of the population moments. Several...

We analyze the introduction of a diversification constraint into the portfolio optimization program. We show that such a constraint is equivalent to an unconstrained portfolio optimization program with a change of the sample covariance matrix by another matrix obtained as the sum of the sample...

The formulation of the Black-Litterman model as a Bayesian mixed estimation approach allows for computing the posterior expected returns taking into account the views of investor on future returns. When the views turn out to be wrong, the resulting portfolio may lead to losses. Sometimes, it may...

DeMiguel et al. (2009) report that naive diversification dominates mean-variance optimization in out-of-sample asset allocation tests. Our analysis suggests that this is largely due to their research design, which focuses on portfolios that are subject to high estimation risk and extreme...