Bayesian Model Averaging (BMA) has recently been discussed in the financial literature as an effective way to account for model uncertainty. In this paper we compare BMA to a new model uncertainty framework introduced by Yang (2004), called Aggregate Forecasting Through Exponential Reweighting,...

This empirical study analyzes market and currency risk premia during financial and political crises within the theoretical framework of the international asset pricing model of Adler and Dumas (1983). The econometric specification extends the multivariate GARCH approach of De Santis and Gerard...

Driven by the rise in computational power, it has become popular to measure integrated variance with high-frequency squared returns. Though the squared return is a natural choice as a variance estimate, it is not the most efficient one for a given interval length. Extreme-value based estima-...

This paper develops a new estimation procedure for characteristic-based factor models of security returns. We treat the factor model as a weighted additive nonparametric regression model, with the factor returns serving as time-varying weights, and a set of univariate non-parametric functions...

We develop a tailor made semiparametric asymmetric kernel density estimator for the estimation of actuarial loss distributions. The estimator is obtained by transforming the data with the generalized Champernowne distribution initially fitted to the data. Then the density of the transformed data...

We cionsider semiparmetric assymetric kernel density estimators when the unkonwn density has support on [0,∞). We provide a unifying framework which contains assymmetric kernel versions of several semiparametric density estimators considered previously in the literature. This framework allows...

We shed new light on the negative relationship between real stock returns or real interest rates and (i) ex post inflation, (ii) expected inflation, (iii) unexpected inflation and (iv) changes in expected inflation. Using the structural vector autoregression methodology, we propose a...

Driven by the rise in computational power, it has become popular to measure integrated variance with high-frequency squared returns. Though the squared return is a natural choice as a variance estimate, it is not the most efficient one for a given interval length. Extreme-value based estimators...

Bayesian Model Averaging (BMA) has recently been discussed in the financial literature as an effective way to account for model uncertainty. In this paper we compare BMA to a new model uncertainty framework introduced by Yang (2004), called Aggregate Forecasting Through Exponential Reweighting,...