A non-linear time series approach to modelling asymmetry in stock market indexes |
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Authors: | Alessandra Amendola Giuseppe Storti |
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Institution: | (1) Dipartimento di Scienze Economiche e Statistiche, Università di Salerno, Via Ponte Don Melillo, 84084 Fisciano (SA), Italy |
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Abstract: | In this paper we analyse the performances of a novel approach to modelling non-linear conditionally heteroscedastic time series
characterised by asymmetries in both the conditional mean and variance. This is based on the combination of a TAR model for
the conditional mean with a Constrained Changing Parameters Volatility (CPV-C) model for the conditional variance. Empirical
results are given for the daily returns of the S&P 500, NASDAQ composite and FTSE 100 stock market indexes. |
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Keywords: | Constrained Changing Parameters Volatility model TAR Leverage effect EM algorithm |
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