The Analysis of Stochastic Volatility in the Presence of Daily Realised Measures

Siem Jan Koopman and Marcel Scharth
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Marcel Scharth: VU University Amsterdam

No 11-132/4, Tinbergen Institute Discussion Papers from Tinbergen Institute

Abstract: This discussion paper led to an article in the Journal of Financial Econometrics (2013). Volume 11, pages 76-115.

We develop a systematic framework for the joint modelling of returns and multiple daily realised measures. We assume a linear state space representation for the log realised measures, which are noisy and biased estimates of the log integrated variance, at least due to Jensen's inequality. We incorporate filtering methods for the estimation of the latent log volatility process. The endogeneity between daily returns and realised measures leads us to develop a consistent two-step estimation method for all parameters in our specification. This method is computationally straightforward even when the stochastic volatility model contains non-Gaussian return innovations and leverage effects. The empirical results reveal that measurement errors become significantly smaller after filtering and that the forecasts from our model outperforms those from a set of recently developed alternatives.

Keywords: Kalman filter; leverage; realised volatility; simulated maximum likelihood (search for similar items in EconPapers)
JEL-codes: C22 C58 (search for similar items in EconPapers)
Date: 2011-09-20
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Citations: View citations in EconPapers (3)

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Related works:
Journal Article: The Analysis of Stochastic Volatility in the Presence of Daily Realized Measures (2012)
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Persistent link: https://EconPapers.repec.org/RePEc:tin:wpaper:20110132

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