Some nonstandard stochastic volatility models and their estimation using structured hidden Markov models

Roland Langrock, Iain L. MacDonald and Walter Zucchini

Journal of Empirical Finance, 2012, vol. 19, issue 1, 147-161

Abstract: We introduce a number of nonstandard stochastic volatility (SV) models and examine their performance when applied to the series of daily returns on several stocks listed on the New York Stock Exchange. The nonstandard models under investigation extend both the observation process and the volatility-generating process of basic SV models. In particular, we consider dependent as well as independent mixtures of autoregressive components as the log-volatility process, and include in the observation equation a lower bound on the volatility. We also consider an experimental SV model that is based on conditionally gamma-distributed volatilities.

Keywords: State-space models; Mixture models; Financial time series; Forecasting; Pseudo-residuals; Backtesting (search for similar items in EconPapers)
JEL-codes: C13 C51 C53 (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (16)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:19:y:2012:i:1:p:147-161

DOI: 10.1016/j.jempfin.2011.09.003

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