DocumentCode
3256990
Title
Piecewise constant modeling and Kalman filter tracking of systematic market risk
Author
Rajbhandary, Triloke ; Xiao-Ping Zhang ; Fang Wang
Author_Institution
Dept. of Electr. & Comput. Eng., Ryerson Univ., Toronto, ON, Canada
fYear
2013
fDate
3-5 Dec. 2013
Firstpage
1144
Lastpage
1144
Abstract
In this paper, we present a new piecewise constant model to represent time-varying systematic risk, i.e., beta. We develop a new tracking algorithm for the new model based on modified Kalman filter that uses Bayes´ criteria. Empirical results show the superiority of our method over traditional random walk, mean reverting and moving window beta estimates.
Keywords
Bayes methods; Kalman filters; marketing; risk analysis; tracking filters; Bayes criteria; mean reverting estimates; modified Kalman filter tracking algorithm; moving window beta estimates; piecewise constant modeling; random walk; time-varying systematic market risk; Adaptation models; Computational modeling; Economics; Educational institutions; Equations; Kalman filters; Systematics;
fLanguage
English
Publisher
ieee
Conference_Titel
Global Conference on Signal and Information Processing (GlobalSIP), 2013 IEEE
Conference_Location
Austin, TX
Type
conf
DOI
10.1109/GlobalSIP.2013.6737107
Filename
6737107
Link To Document