This paper applies LINEX loss functions to forecasting nonlinear functions of variance. We derive the optimal one-step-ahead LINEX forecast for various volatility models using data transformations such as ln(y2t) where yt is the return of the asset. Our results suggest that the LINEX loss...

The determination of the values of stocks, bonds, options, futures, and derivatives is done by the scientific process of asset pricing, which has developed dramatically in the last few years due to advances in financial theory and econometrics. This book covers the science of asset pricing by...

This article investigates the modelling of style returns in the United States and the returns to style 'tilts' based on forecasts of enhanced future style returns. We use hidden Markov model to build our forecasts for data from 1975 to 1998. We do not include more recent observations as the...

This paper applies Bayesian variable selection methods from the statistics literature to give guidance in the decision to include/omit factors in a global (linear factor) stock return model. Once one has accounted for country and sector, it is possible to see which style or styles best explains...

In this paper, we propose the average <italic>F</italic>-statistic for testing linear asset pricing models. The average pricing error, captured in the statistic, is of more interest than the <italic>ex post</italic> maximum pricing error of the multivariate <italic>F</italic>-statistic that is associated with extreme long and short positions and...