Abstract

http://ssrn.com/abstract=231520
 
 

Citations



 


 



Applied Non-Parametric Regression Techniques: Estimating Prepayments on Fixed Rate Mortgage-Backed Securities


Michael LaCour-Little


California State University at Fullerton

Clark L. Maxam


Trailcrest Capital Advisors; Braddock Financial Corporation - Tabor Center

February 2000

OLIN-99-04

Abstract:     
We assess nonparametric kernel density regression as a technique for estimating mortgage loan prepayments - one of the key components in pricing highly volatile mortgage-backed securities and their derivatives. The highly non-linear and so-called "irrational" behavior of the prepayment function lends itself well to an estimator that is free of both functional and distributional assumptions. The technique is shown to exhibit superior out-of-sample predictive ability compared to both proportional hazards and proprietary practitioner models. Moreover, the best kernel model provides this improved predictive power utilizing a more parsimonious specification in terms of both data and covariates. We conclude that the technique may prove useful in other financial modeling applications, such as default modeling, and other derivative pricing problems where highly non-linear relationships and optionality exist.

JEL Classification: C14, G13, G21

working papers series


Not Available For Download

Date posted: June 22, 2000  

Suggested Citation

LaCour-Little, Michael and Maxam, Clark L., Applied Non-Parametric Regression Techniques: Estimating Prepayments on Fixed Rate Mortgage-Backed Securities (February 2000). OLIN-99-04. Available at SSRN: http://ssrn.com/abstract=231520

Contact Information

Michael LaCour-Little (Contact Author)
California State University at Fullerton ( email )
5133 Mihaylo Hall
Fullerton, CA 92834-6848
United States
657-278-4014 (Phone)
657-278-2161 (Fax)
Clark L. Maxam
Trailcrest Capital Advisors ( email )
6781 Nautique Circle
Larkspur, CO 80118
United States
Braddock Financial Corporation - Tabor Center ( email )
1200 17th Street, Suite 880
Denver, CO 80202
United States
Feedback to SSRN


Paper statistics
Abstract Views: 819

© 2014 Social Science Electronic Publishing, Inc. All Rights Reserved.  FAQ   Terms of Use   Privacy Policy   Copyright   Contact Us
This page was processed by apollo2 in 0.813 seconds