A non-linear time series approach to modelling asymmetry in stock market indexes

Alessandra Amendola () and Giuseppe Storti ()
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Giuseppe Storti: Università di Salerno

Statistical Methods & Applications, 2002, vol. 11, issue 2, No 6, 216 pages

Abstract: 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.

Keywords: Constrained Changing Parameters Volatility model; TAR; Leverage effect; EM algorithm (search for similar items in EconPapers)
Date: 2002
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Citations: View citations in EconPapers (4)

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Working Paper: A NON LINEAR TIME SERIES APPROACH TO MODELLING ASYMMETRY IN STOCK MARKET INDEXES (2000)
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DOI: 10.1007/BF02511487

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