Goodness-of-fit tests for parametric specifications of conditionally heteroscedastic models

M. Dolores Jiménez-Gamero (), Sangyeol Lee () and Simos G. Meintanis ()
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M. Dolores Jiménez-Gamero: University of Sevilla
Sangyeol Lee: Seoul National University
Simos G. Meintanis: National and Kapodistrian University of Athens

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2020, vol. 29, issue 3, No 4, 682-703

Abstract: Abstract We consider a goodness-of-fit test for certain parametrizations of conditionally heteroscedastic time series with unobserved components. Our test is quite general in that it can be employed to validate any given specification of arbitrary order and may even be invoked for testing not just GARCH models but also some related models such as autoregressive conditional duration models. The test statistic utilizes the characterization of Bierens (J Econom 20:105–134, 1982) and may be written down in a convenient closed-form expression. Consistency of the test is proved, and the asymptotic distribution of the test statistic under the null hypothesis is studied. Since this distribution depends on unknown quantities, two bootstrap resampling schemes are investigated and compared in order to approximate critical points and actually carry out the test. Finite-sample results are presented as well as applications of the proposed procedures to real data from the financial markets.

Keywords: GARCH model; Goodness-of-fit test; Bierens characterization; Conditional duration model; Weighted bootstrap; 62G10; 62G20 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s11749-019-00676-0

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