We revisit the Kolmogorov-Smirnov and Cramér-von Mises goodness-of-fit (GoF) tests and propose a generalization to identically distributed, but dependent uni-variate random variables. We show that the dependence leads to a reduction of the "effective" number of independent observations. The...

We compare more than 1000 different volatility models in terms of their fit to the historical ISE-100 Index data and their forecasting performance of the conditional variance in an out-of-sample setting. Exponential GARCH model of Nelson (1991) with “constant mean, t-distribution, one lag...

This paper considers spot variance path estimation from datasets of intraday high frequency asset prices in the presence of diurnal variance patterns, jumps, leverage effects and microstructure noise. We rely on parametric and nonparametric methods. The estimated spot variance path can be used...

This paper considers spot variance path estimation from datasets of intraday high frequency asset prices in the presence of diurnal variance patterns, jumps, leverage effects and microstructure noise. We rely on parametric and nonparametric methods. The estimated spot variance path can be used...

This paper first examines the efficiency of the UK covered warrants market by adopting a stochastic dominance (SD) approach to examine market efficiency. Our empirical analyses reveal that neither covered warrants nor the underlying shares stochastically dominate each other, which implies that...

This paper develops methodology for nonparametric estimation of a polarization measure due to Anderson (2004) and Anderson, Ge, and Leo (2006) based on kernel estimation techniques. We give the asymptotic distribution theory of our estimator, which in some cases is nonstandard due to a boundary...

We develop a practical and novel method for inference on intersection bounds, namely bounds defined by either the infimum or supremum of a parametric or nonparametric function, or equivalently, the value of a linear programming problem with a potentially infinite constraint set. Our approach is...

Goodness of fit tests based on sup-norm statistics of empirical processes have nonstandard limiting distributions when the null hypothesis is composite-that is, when parameters of the null model are estimated. Several solutions to this problem have been suggested, including the calculation of...

We develop a test of equality between two dependence structures estimated through empirical copulas. We provide inference for independent or paired samples. The multiplier central limit theorem is used for calculating p-values of the Crameacute;r-von Mises test statistic. Finite sample properties...

Employing the “small-bandwidth” asymptotic framework of Cattaneo, Crump, and Jansson (2009), this paper studies the properties of several bootstrap-based inference procedures associated with a kernel-based estimator of density-weighted average derivatives proposed by Powell, Stock, and...