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Estimation of Asymmetric Stochastic Volatility in Mean Models

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  • Antonis Demos

    (www.aueb.gr/users/demos)

Abstract

Here we investigate the estimation of asymmetric Autoregressive Stochastic Volatility models with possibly time varying risk premia. We employ the Indirect Inference estimation developed in Gallant and Tauchen (1996), with a first step estimator either the Generalized Quadratic ARCH or the Exponential GARCH. We employ Monte-Carlo simulations to compare the two first step models in terms of bias and root Mean Squared Error. We apply the developed methods for the estimation of an asymmetric autoregressive SV-M model to international stock markets excess returns.

Suggested Citation

  • Antonis Demos, 2023. "Estimation of Asymmetric Stochastic Volatility in Mean Models," DEOS Working Papers 2309, Athens University of Economics and Business.
    • Handle: RePEc:aue:wpaper:2309
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    Keywords

    Stochastic Volatility estimation asymmetry leverage indirect inference;

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