The estimation of the inverse covariance matrix plays a crucial role in optimal portfolio choice. We propose a new estimation framework that focuses on enhancing portfolio performance. The framework applies the statistical methodology of shrinkage directly to the inverse covariance matrix using...

Portfolio theories are meant to provide a method for managing assets and constructing portfolios. Meanwhile, the mean-variance technique has been heavily criticized by some academics, and its application to real estate portfolio is questionable (Cheng and Liang, 2000). Indeed, the mean-variance...

It is well known that non-normality plays an important role in asset and risk management. However, handling a large number of assets has long been a challenge due to the curse of dimensionality. We describe a statistical technique, which we call Moment Component Analysis (MCA), that extends...

We implement a long-horizon static and dynamic portfolio allocation involving a risk-free and a risky asset. This model is calibrated at a quarterly frequency for ten European countries. We also use maximum-likelihood estimates and Bayesian estimates to account for parameter uncertainty. We find...

The use of mixture distributions for modeling asset returns has a long history in finance. New methods of demonstrating support for the presence of mixtures in the multivariate case are provided. The use of a two-component multivariate normal mixture distribution, coupled with shrinkage via a...

The paper proposes a framework for large-scale portfolio optimization which accounts for all the major stylized facts of multivariate financial returns, including volatility clustering, dynamics in the dependency structure, asymmetry, heavy tails, and nonellipticity. It introduces a so-called...

This paper analyzes the expected life-time utility and the hedging demands in an exchange only, representative agent general equilibrium under incomplete information. We derive an expression for the investor's expected life-time utility, and analyze his hedging demands for intertemporal changes...

It is well known that the class of strong (Generalized) AutoRegressive Conditional Heteroskedasticity (or GARCH) processes is not closed under contemporaneous aggregation. This paper provides the dynamics followed by the aggregate process when the individual persistence parameters are drawn from...

Ambiguity aversion in dynamic models is motivated by the presence of unknown time-varying features, which agents do not understand and cannot theorize about. We analyze the consequences of this assumption for economic agents and model builders, who typically need to estimate a model, e.g., to...