Weak convergence of non-stationary multivariate marked processes with applications to martingale testing

Juan Carlos Escanciano

Journal of Multivariate Analysis, 2007, vol. 98, issue 7, 1321-1336

Abstract: This paper establishes the weak convergence of a class of marked empirical processes of possibly non-stationary and/or non-ergodic multivariate time series sequences under martingale conditions. The assumptions involved are similar to those in Brown's martingale central limit theorem. In particular, no mixing conditions are imposed. As an application, we propose a test statistic for the martingale hypothesis and we derive its asymptotic null distribution. Finally, a Monte Carlo study shows that the asymptotic results provide good approximations for small and moderate sample sizes. An application to the S&P 500 is also considered.

Keywords: Marked; empirical; processes; Weak; convergence; Martingale; hypothesis; Non-stationary; time; series (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (13)

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