The purpose of this paper is to serve as a guide for students' use of actual data for risk and return calculations. The study of stock return risk has been of interest to investors and academics for several decades. Early discussion of the “mean-variance framework” described the rationale...

In this paper we propose exact likelihood-based mean-variance efficiency tests of the market portfolio in the context of Capital Asset Pricing Model (CAPM), allowing for a wide class of error distributions which include normality as a special case. These tests are developed in the framework of...

In this paper we propose exact likelihood-based mean-variance efficiency tests of the market portfolio in the context of Capital Asset Pricing Model (CAPM), allowing for a wide class of error distributions which include normality as a special case. These tests are developed in the framework of...

Based on the Partial Distribution (Feng Dai, 2001), a new model to price an asset (MPA) is given. Going a step further, this paper puts forward the Multivariate Partial Distribution (MPD) for the first time. By use of MPD, we could gain a new kind of model for pricing the group assets (MPGA), in...

We propose exact simulation-based procedures for: (i) testing mean-variance efficiency when the zero-beta rate is unknown, and (ii) building confidence intervals for the zero-beta rate. On observing that this parameter may be weakly identified, we propose LR-type statistics as well as...

This paper analyzes the finite-sample performance of the two-pass (TP) estimators of factor risk prices when betas have high cross-sectional correlations (Multicollinear) and when betas have small cross-sectional variations (Invariant). Our Monte Carlo simulations, calibrated using actual...

This paper examines the asymptotic and finite sample properties of the two-pass cross-sectional regressions estimators, when the factors and the asset returns are conditionally heteroskedastic and/or autocorrelated. Using a minimum distance approach, we derive heteroskedasticity- and/or...

We investigate the factor exposure of smart beta ETFs under model uncertainty using Bayesian variable selection. We find that smart beta ETFs have exposures to several factors, including size, value, momentum, quality, volatility/low beta, and dividend yield. The average return contribution of...