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Estimation of Asymmetric Stochastic Volatility Models for Stock-Exchange Index Returns

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  • María García Centeno
  • Román Mínguez Salido

Abstract

The objective of this paper is to put forward a new autoregressive asymmetric stochastic volatility model for modeling volatility and to compare results obtained for this model with an autoregressive stochastic model and another asymmetric volatility model, such as, asymmetric generalized autoregressive conditional heteroskedasticity model. The results obtained from the estimation by maximum likelihood have shown the volatility behavior is asymmetric in the majority of cases. This fact is better shown by the ARSVA model, than the rest of alternative models. Moreover, the ARSVA model is able to reproduce other stylized facts of such series, such as high kurtosis, no autocorrelation of returns, slow decreasing of the autocorrelation function of the squared returns and high persistence. Copyright International Atlantic Economic Society 2009

Suggested Citation

  • María García Centeno & Román Mínguez Salido, 2009. "Estimation of Asymmetric Stochastic Volatility Models for Stock-Exchange Index Returns," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 15(1), pages 71-87, February.
    • Handle: RePEc:kap:iaecre:v:15:y:2009:i:1:p:71-87:10.1007/s11294-008-9191-6
    DOI: 10.1007/s11294-008-9191-6
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    Cited by:

    1. Aityan, Sergey K. & Ivanov-Schitz, Alexey K. & Izotov, Sergey S., 2010. "Time-shift asymmetric correlation analysis of global stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(5), pages 590-605, December.
    2. Mao, Xiuping & Ruiz, Esther & Veiga, Helena, 2017. "Threshold stochastic volatility: Properties and forecasting," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1105-1123.

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    More about this item

    Keywords

    Leverage effect; Stochastic volatility; Stock returns; C22; C51;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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