Linear and nonlinear filtering in mathematical finance: an overview

Authors:
Paresh Date
Affiliations:
Department of Mathematical Sciences, Brunel University, Uxbridge, Middlesex, United Kingdom
Venue:
ISTASC'09 Proceedings of the 9th WSEAS International Conference on Systems Theory and Scientific Computation
Year:
2009

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Abstract

This paper presents a brief overview of Kalman filtering and its applications in mathematical finance. Results of recent empirical studies with market data are presented for stochastic volatility modelling and yield curve modelling. The paper also outlines rigorous as well as heuristic approaches to filtering of nonlinear time series.