Nonlinear Kalman Filtering in Affine Term Structure Models

Peter Christoffersen, Christian Dorion (), Kris Jacobs () and Lotfi Karoui ()
Additional contact information
Christian Dorion: HEC Montreal, Montreal, Quebec H3T 2A7, Canada
Kris Jacobs: C. T. Bauer College of Business, University of Houston, Houston, Texas 77204
Lotfi Karoui: Goldman, Sachs & Company, New York, New York 10282

Management Science, 2014, vol. 60, issue 9, 2248-2268

Abstract: The extended Kalman filter, which linearizes the relationship between security prices and state variables, is widely used in fixed-income applications. We investigate whether the unscented Kalman filter should be used to capture nonlinearities and compare the performance of the Kalman filter with that of the particle filter. We analyze the cross section of swap rates, which are mildly nonlinear in the states, and cap prices, which are highly nonlinear. When caps are used to filter the states, the unscented Kalman filter significantly outperforms its extended counterpart. The unscented Kalman filter also performs well when compared with the much more computationally intensive particle filter. These findings suggest that the unscented Kalman filter may be a good approach for a variety of problems in fixed-income pricing. This paper was accepted by Wei Xiong, finance .

Keywords: Kalman filtering; nonlinearity; term structure models; swaps; caps; particle filtering (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (37)

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http://dx.doi.org/10.1287/mnsc.2013.1870 (application/pdf)

Related works:
Working Paper: Nonlinear Kalman Filtering in Affine Term Structure Models (2014)
Working Paper: Nonlinear Kalman Filtering in Affine Term Structure Models (2012)
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:60:y:2014:i:9:p:2248-2268

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