NDLI: Analytical factor stochastic volatility modeling for portfolio allocation

Content Provider	IEEE Xplore Digital Library
Author	Nikolaev, N.Y. Smirnov, E.
Copyright Year	2012
Description	Author affiliation: Department of Computing, MICC-IKAT, Maastricht University, Maastricht 6200 MD, The Netherlands (Smirnov, E.) \|\| Department of Computing, Goldsmiths College, University of London, London SE14 6NW, United Kingdom (Nikolaev, N.Y.)
Abstract	This paper proposes a computationally efficient approach to estimation of factor stochastic volatility models using analytical formulae. Following the maximum likelihood principle there are obtained formulae for the evaluation of the parameters of the dynamic factor model, as well as for the parameters of the ingredient stochastic volatility processes. The approach uses the Hull-White stochastic volatility model to represent the common factors and the idiosyncratic factors. Empirical investigations show that this analytical factor stochastic volatility modeling generates plausible forecasts which are useful for portfolio selection.
Starting Page	1
Ending Page	8
File Size	331782
Page Count	8
File Format	PDF
ISBN	9781467318020
e-ISBN	9781467318037
e-ISBN	9781467318013
DOI	10.1109/CIFEr.2012.6327808
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-03-29
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computational modeling Loading Noise Stochastic processes Mathematical model Portfolios Load modeling
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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