Forecasting Realized Volatility with Changes of Regimes

Giampiero Gallo () and Edoardo Otranto

No 2014_03, Econometrics Working Papers Archive from Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti"

Abstract: Realized volatility of financial time series generally shows a slow–moving average level from the early 2000s to recent times, with alternating periods of turmoil and quiet. Modeling such a pattern has been variously tackled in the literature with solutions spanning from long–memory, Markov switching and spline interpolation. In this paper, we explore the extension of Multiplicative Error Models to include a Markovian dynamics (MS-MEM). Such a model is able to capture some sudden changes in volatility following an abrupt crisis and to accommodate different dynamic responses within each regime. The model is applied to the realized volatility of the S&P500 index: next to an interesting interpretation of the regimes in terms of market events, the MS-MEM has better in–sample fitting capability and achieves good out–of–sample forecasting performances relative to alternative specifications.

Keywords: MEM; regime switching; realized volatility; volatility persistence; volatility forecasting (search for similar items in EconPapers)
JEL-codes: C22 C24 C58 (search for similar items in EconPapers)
Pages: 42 pages
Date: 2014-02, Revised 2014-02
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for, nep-ore and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://labdisia.disia.unifi.it/wp_disia/2014/wp_disia_2014_03.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:fir:econom:wp2014_03

Access Statistics for this paper

More papers in Econometrics Working Papers Archive from Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti" Viale G.B. Morgagni, 59 - I-50134 Firenze - Italy. Contact information at EDIRC.
Bibliographic data for series maintained by Fabrizio Cipollini ().