Estimation of Equilibrium Term Structure Models: EKF and UKF Based Approaches

SU Yunpeng; YANG Baochen

Chinese︱Feedback︱Save this page

• Elaborating Academic Views 　　　　 • Exchanging Innovative Ideas
• Protecting Intellectual Properties 　　• Fast Sharing Science Papers

Sponsored by the Center for Science and Technology Development of the Ministry of Education
Supervised by Ministry of Education of the People's Republic of China

Home > Papers

Estimation of Equilibrium Term Structure Models: EKF and UKF Based Approaches

SU Yunpeng * #,YANG Baochen

College of Management and Economics, Tianjin University, Tianjin 300072

*Correspondence author

#Submitted by

Subject:

Funding: The Research Fund for the Doctoral Program of Higher Education （No.No. 20130032120013）, Humanity and Social Science Youth foundation of Ministry of Education of China （No.No. 11YJCZH147）, Supported by National Natural Science Foundation of China （No.No. 71501140）

Opened online:13 December 2016

Accepted by: none

Citation: SU Yunpeng,YANG Baochen.Estimation of Equilibrium Term Structure Models: EKF and UKF Based Approaches[OL]. [13 December 2016] http://en.paper.edu.cn/en_releasepaper/content/4712769

In a general framework, this paper introduces approaches of estimation for equilibrium models of term structure of interest rates based on the extended Kalman filter (hereafter EKF) and unscented Kalman filter (hereafter UKF). This paper treats the estimation of the equilibrium models as a nonlinear filtering problem, and adopts EKF and the UKF respectively to estimate the model via the maximum likelihood method. Using fourteen years of daily Canadian zero-coupon bond price data, we apply the estimator to Vasicek and Cox-Ingersoll-Ross models based on EKF and UKF respectively. It is found that the EKF-based algorithm offers generally the same performance with the UKF-based one in model estimation when the system is linear or weak linear and the Gaussian distribution assumption is satisfied. But when it comes to the strong nonlinear system with a non-Gaussian distribution, the UKF-based algorithm does a better job than the EKF-based one in model estimation. However the UKF-based algorithm is about 50% slower than the EKF-based one in actual computation, though it is regarded in literature that they both have the same order of computational complexity.

Keywords:financial engineering; Term structure of interest rates; Model estimation; Extended Kalman filter; Unscented Kalman filter; Maximum likelihood estimator

For this paper

● PDF (0B)
● Revision 0 　　
● Print this paper
● Recommend this paper to a friend
● Add to my favorite list

Saved Papers

Please enter a name for this paper to be shown in your personalized Saved Papers list

Tags

Add yours

Related Papers

Statistics

PDF Downloaded	49
Bookmarked	0
Recommend	0
Comments	Array

Submit your papers

Alert Name:
Alerting to:
Authentication email will be sent to your email address in 24 hours
Frequency:
Email Message Format:	Plain text Graphical(HTML)

Complete the form below and we will recommend the selected titles to your friends on your behalf. * Indicates a required field.
Your name*:
Your email address*:
Recipient's name*:
Recipient's email address*:
(multiple recipient's names and email addresses should be separated with semicolons)
Your comments:	I thought you would find the page(s) useful.

Your name:
Your email address:
Recipient's name:
Recipient's email address:
(multiple recipient's names and email addresses should be separated with semicolons)
Your comments:	I thought you would find this page useful.

Disclaimer: This message was sent to your friend using the "Send it to a friend" facility on the Sciencepaper Online’ WWW site, http://www.paper.edu.cn/en. The Sciencepaper Online is not responsible for the content of this email, and anything said in this email does not necessarily reflect the Sciencepaper Online's views.

	Check out RSS, or use RSS reader to subscribe this item

Saved Papers