Egarch And Stochastic Volatility
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EGARCH and Stochastic Volatility
Author | : Jouchi Nakajima |
Publisher | : |
Total Pages | : 28 |
Release | : 2008 |
Genre | : Stochastic processes |
ISBN | : |
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"This paper proposes the EGARCH [Exponential Generalized Autoregressive Conditional Heteroskedasticity] model with jumps and heavy-tailed errors, and studies the empirical performance of different models including the stochastic volatility models with leverage, jumps and heavy-tailed errors for daily stock returns. In the framework of a Bayesian inference, the Markov chain Monte Carlo estimation methods for these models are illustrated with a simulation study. The model comparison based on the marginal likelihood estimation is provided with data on the U.S. stock index."--Author's abstract.
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