Parameter Estimation for Nonlinear State-Space Models Using Particle Methods Combined with the EM Algorithm

Katarzyna Brzozowska-Rup () and Antoni Leon Dawidowicz ()
Additional contact information
Katarzyna Brzozowska-Rup: Kielce University of Technology, Poland
Antoni Leon Dawidowicz: Jagiellonian University, Cracow, Poland

Chapter 7 in FindEcon Monograph Series: Advances in Financial Market Analysis, 2011, vol. 9, pp 111-123 from University of Lodz

Abstract: In the next chapter (Chapter 7) Katarzyna Brzozowska-Rup and Antoni Leon Dawidowicz present particle filter approach which is a likelihood-based method of inference in nonlinear, non-Gaussian state-space models. In the simulation experiment this sequential Monte Carlo method has been combined with the Expectation-Maximization algorithm and applied to stochastic volatility models.

Keywords: Nonlinear state-space model; Particle filter; EM algorithm; Monte Carlo method (search for similar items in EconPapers)
JEL-codes: C01 E02 F00 G00 (search for similar items in EconPapers)
Date: 2011
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.repec.uni.lodz.pl/RePEc/files/findec/2011/2011_No_9_Ch_7.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:ann:findec:book:y:2011:n:09:ch:07:mon

Access Statistics for this chapter

More chapters in FindEcon Chapters: Forecasting Financial Markets and Economic Decision-Making from University of Lodz Contact information at EDIRC.
Bibliographic data for series maintained by Piotr Wdowiński ().