Article,

Filtering in Finance

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Wilmott Magazine, 2003 (3): 67--83 (2003)
DOI: 10.1002/wilm.42820030315

Abstract

In this article we present an introduction to various Filtering algorithms and some of their applications to the world of Quantitative Finance. We shall first mention the fundamental case of Gaussian noises where we obtain the well-known Kalman Filter. Because of common nonlinearities, we will be discussing the Extended Kalman Filter (EKF) as well as the Unscented Kalman Filter (UKF) similar to Kushner's Nonlinear Filter. We also tackle the subject of Non-Gaussian filters and describe the Particle Filtering (PF) algorithm. Lastly, we will apply the filters to the term structure model of commodity prices and the stochastic volatility model.

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