Particle Filtering

Michael Johannes () and Nicholas Polson ()
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Michael Johannes: Columbia University, Graduate School of Business
Nicholas Polson: University of Chicago, Graduate School of Business,

Chapter 44 in Handbook of Financial Time Series, 2009, pp 1015-1029 from Springer

Abstract: Abstract This chapter provides an overview of particle filters. Particle filters generate approximations to filtering distributions and are commonly used in non-linear and/or non-Gaussian state space models. We discuss general concepts associated with particle filtering, provide an overview of the main particle filtering algorithms, and provide an empirical example of filtering volatility from noisy asset price data.

Keywords: Particle Filter; State Space Model; Importance Sampling; Stochastic Volatility Model; Particle Approximation (search for similar items in EconPapers)
Date: 2009
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DOI: 10.1007/978-3-540-71297-8_44

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