Stochastic conditonal range, a latent variable model for financial volatility

Fausto Galli

MPRA Paper from University Library of Munich, Germany

Abstract: In this paper we introduce a parameter driven model for the dynamics of range, the stochastic conditional range (SCR). We propose to estimate its parameters by Kalman filter, importance sampling and simulated maximum likelihood depending on the hypotheses on the distributional form of the innovations. The model is applied to a large subset of the S&P 500 components. A comparison with of its fitting and forecasting abilities with the CARR model shows that the new approach can provide an interesting alternative.

Keywords: Financial econometrics; range; volatility; importance sampling; indirect inference (search for similar items in EconPapers)
JEL-codes: C15 C5 C58 (search for similar items in EconPapers)
Date: 2014-02-28
New Economics Papers: this item is included in nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/54841/8/MPRA_paper_54841.pdf original version (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:pra:mprapa:54841

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().