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

In this paper, we propose several finite-sample specification tests for multivariate linear regressions (MLR). We focus on tests for serial dependence and ARCH effects with possibly non-Gaussian errors. The tests are based on properly standardized multivariate residuals to ensure invariance to...

In this paper we propose a multivariate regression based assessment of the multifactor model first developed by Fama and French (1993). We study mean-variance efficiency and spanning, as well as factor relevance. In particular, we assess the relative contribution of the factors in accounting for...

Usual inference methods for stable distributions are typically based on limit distributions. But asymptotic approximations can easily be unreliable in such cases, for standard regularity conditions may not apply or may hold only weakly. This paper proposes finite-sample tests and confidence sets...

Exact inference methods are proposed for asset pricing models with unobservable risk-free rates and coskewness; specifically, the Quadratic Market Model (QMM) which incorporates the effect of asymmetry of return distribution on asset valuation. In this context, exact tests are appealing given...

Purpose – The purpose of this paper is to examine financial integration across North American stock markets from January 1984 to December 2003. Design/methodology/approach – The paper uses an arbitrage pricing theory framework. The risk factors considered are the three Fama and French...