Test for tail index constancy of GARCH innovations based on conditional volatility

Moosup Kim and Sangyeol Lee ()
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Moosup Kim: APEC Climate Center
Sangyeol Lee: Seoul National University

Annals of the Institute of Statistical Mathematics, 2019, vol. 71, issue 4, No 9, 947-981

Abstract: Abstract This study considers the problem of testing whether the tail index of the GARCH innovations undergoes a change according to the values of conditional volatilities. Special attention is paid to power-transformed and threshold generalized autoregressive conditional heteroscedasticity processes that can accommodate the GARCH family. We show that the proposed test asymptotically follows a functional of a standard Brownian motion under some regularity conditions. To evaluate our method, we carry out a simulation study and real data analysis using the return series of the Google stock price and DowJones index.

Keywords: Constancy test for tail index; Heavy-tailed distribution; Conditional volatility; GARCH model; PTTGARCH model (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10463-018-0669-6

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