A Simple Model for Now-Casting Volatility Series
Jörg Breitung (breitung@statistik.uni-koeln.de) and
Christian Hafner
No 2016004, LIDAM Discussion Papers CORE from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)
Abstract:
Popular volatility models focus on the conditional variance given past observations, whereas the (arguably most important) information in the current observation is ignored. This paper proposes a simple model for now-casting volatilities based on a specific ARMA representation of the log-transformed squared returns that allows us to estimate current volatility as a function of current and past returns. The model can be viewed as a stochastic volatility model with perfect correlation between the two error terms. It is shown that the volatility nowcasts are invariant to this correlation and therefore the estimated volatilities coincide. An extension of our now-casting model is proposed that takes into account the so-called leverage effect. The alternative models are applied to estimate daily return volatilities from the S&P 500 stock price index.
Keywords: EGARCH; stochastic volatility; ARMA; realized volatility; leverage (search for similar items in EconPapers)
JEL-codes: C22 C58 (search for similar items in EconPapers)
Date: 2016-10-01
New Economics Papers: this item is included in nep-ets, nep-for, nep-ore and nep-rmg
References: Add references at CitEc
Citations: View citations in EconPapers (5)
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https://sites.uclouvain.be/core/publications/coredp/coredp2016.html (application/pdf)
Related works:
Journal Article: A simple model for now-casting volatility series (2016)
Working Paper: A simple model for now-casting volatility series (2016)
Working Paper: A simple model for now-casting volatility series (2016)
Working Paper: A simple model for now-casting volatility series (2016)
Working Paper: A simple model for now-casting volatility series (2015)
Working Paper: A simple model for now-casting volatility series (2014)
Working Paper: A simple model for now-casting volatility series (2014)
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