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...

In this paper we explore the use of Genetic Algorithms (GA) to calibrate seasonal BVAR models. In this way, the mechanistic use of seasonal adjustment procedures is avoided, since seasonality becomes a structural, basic and explicit part of the BVAR model. At the same time, the use of GA allows...

Dynamic treatment regimes are treatment allocations tailored to heterogeneous individuals. The optimal dynamic treatment regime is a regime that maximizes counterfactual welfare. We introduce a framework in which we can partially learn the optimal dynamic regime from observational data, relaxing...

The paper examines the performance of four multivariate volatility models, namely CCC, VARMA-GARCH, DCC and BEKK, for the crude oil spot and futures returns of two major benchmark international crude oil markets, Brent and WTI, to calculate optimal portfolio weights and optimal hedge ratios, and...

Ethanol has been the subject of intense debate following the adoption of the Energy Policy Act of 2005 (EPAct) which established that the gasoline supply in the United States (U.S.) must contain 10% ethanol. This work seeks to identify hedging ratios using dynamic multivariate GARCH to best...

This paper presents a dynamic factor model in which the extracted factors and shocks are given a clear economic interpretation. The economic interpretation of the factors is obtained by means of a set of over-identifying loading restrictions, while the structural shocks are estimated following...

This paper presents a dynamic factor model in which the extracted factors and shocks are given a clear economic interpretation. The economic interpretation of the factors is obtained by means of a set of over-identifying loading restrictions, while the structural shocks are estimated following...

This article shows how sparse solutions can be generated in parametric portfolio selection methods. Sparse mean-variance optimization procedures can be applied after the translation of parametric weight estimates into implied mean return estimates. The results of our empirical analysis suggest...

We propose a new approach that allows for incorporating qualitative views, such as ordering information, into estimates of future asset returns within the Black-Litterman model. We develop a mathematical framework and numerical computation methods for this setting. We find importance sampling to...