possible portfolios constructed from a set of assets. We justify block bootstrap approaches to achieve valid inference in a … results show that the bootstrap procedure performs well in finite samples. The empirical application reveals that the Fama and …

, we perform simulations leading to the conclusion that, under classical estimation, model risk bias dominates estimation …This paper investigates model risk issues in the context of mean-variance portfolio selection. We analytically and … risk bias. Finally, we suggest a diagnostic tool to warnthe analyst of the presence of extreme returns that have an …

. We compare EIS-based ML estimation with QML estimation based on the Kalman filter. We find that EIS-ML estimation is more …

distribution is normal under the null hypothesis, and a consistent bootstrap is available to get simulation based critical values …

This paper focuses on the robust Effcient Method of Moments (EMM) estimation of a general parametric stationary process …

application to nonparametric estimation of an Engel curve. …