'Detecting Asymmetries in Observed Linear Time Series and Unobserved Disturbances' - Abstract

Detecting Asymmetries in Observed Linear Time Series and Unobserved Disturbances

Jeong-Ryeol Kim
Stefan Mittnik
Institute of Statistics and Econometrics
Christian Albrechts University at Kiel

Svetlozar T. Rachev
Department of Statistics and Applied Probability
University of California at Santa Barbara


Pages 131-143

Abstract

This paper investigates the problem of testing for the symmetry of linear time series driven by asymmetric innovations. In particular, we examine the performance of alternative symmetry tests when innovations are fat tailed. Among the tests considered, only the test based on the tail estimator of the spectral measure yields satisfactory results in the presence of fat-tailed innovations.

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