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Modeling Heavy-Tailed Stock Index Returns Using the Generalized Hyperbolic Distribution

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  • Necula, Ciprian

    () (Academy of Economic Studies, Bucharest)

Abstract

In the present study, we estimate the parameters of the Generalized Hyperbolic Distribution for a series of stock index returns including the Romanian BETC and indexes from other two Eastern European countries, Hungary and the Czech Republic. Using different econometric techniques, we investigate whether the estimated Generalized Hyperbolic Distribution is an appropriate approximation for the empirical distribution computed by non-parametric kernel econometric methods. The main finding of the analysis is that the probability density function of the estimated Generalized Hyperbolic Distribution represents a very close approximation (at least up to the 4th order term) of the empirical probability distribution function.

Suggested Citation

  • Necula, Ciprian, 2009. "Modeling Heavy-Tailed Stock Index Returns Using the Generalized Hyperbolic Distribution," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 6(2), pages 118-131, June.
  • Handle: RePEc:rjr:romjef:v:6:y:2009:i:2:p:118-131
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    Cited by:

    1. Marcel Wollschlager & Rudi Schafer, 2015. "Impact of non-stationarity on estimating and modeling empirical copulas of daily stock returns," Papers 1506.08054, arXiv.org.
    2. Andrei ANGHEL & Dalina DUMITRESCU & Cristiana TUDOR, 2015. "Modeling Portfolio Returns On Bucharest Stock Exchange Using The Fama-French Multifactor Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 22-46, March.
    3. Kaiping Wang, 2014. "Modeling Stock Index Returns using Semi-Parametric Approach with Multiplicative Adjustment," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 65-75, December.
    4. Necula, Ciprian, 2010. "Modeling the Dependency Structure of Stock Index Returns using a Copula Function Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 93-106, September.

    More about this item

    Keywords

    Generalized Hyperbolic Distribution; heavy-tailed returns; non-parametric density estimation;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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