The single index model is a generalization of the linear regression model with E(y|x) = g, whereg is an unknown function. The model provides a flexible alternative to the linear regression modelwhile providing more structure than a fully nonparametric approach. Although the fitting of single...

An improved AIC-based criterion is derived for model selection in general smoothing-basedmodeling, including semiparametric models and additive models. Examples areprovided of applications to goodness-of-fit, smoothing parameter and variable selectionin an additive model and semiparametric...

This article introduces covariance regression analysis for a p-dimensional response vector. The proposed method explores the regression relationship between the p-dimensional covariance matrix and auxiliary information. We study three types of estimators: maximum likelihood, ordinary least...

In multivariate analysis, the covariance matrix associated with a set of variables of interest (namely response variables) commonly contains valuable information about the dataset. When the dimension of response variables is considerably larger than the sample size, it is a non-trivial task to...

In linear regression models with high dimensional data, the classical z-test (or t-test) for testing the significance of each single regression coefficient is no longer applicable. This is mainly because the number of covariates exceeds the sample size. In this paper, we propose a simple and...

This paper proposes a new index to extract forward-looking information from security prices and infer market participants' expectations of future earnings. The index, called market-adapted earnings (MAE), utilizes stock returns and fundamental accounting signals to estimate market expectations...

In extreme value statistics, the tail index is an important measure to gauge the heavy-tailed behavior of a distribution. Under Pareto-type distributions, we employ the logarithmic function to link the tail index to the linear predictor induced by covariates, which constitutes the tail index...

We employ a statistical criterion (out-of-sample hit rate) and a financial market measure (portfolio performance) to compare the forecasting accuracy of three model selection approaches: Bayesian information criterion (BIC), model averaging, and model mixing. While the more recent approaches of...