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San Diego State University

Fowler College of
Business Administration

Intellectual Contribution

Title
An evaluation of alternative methods used in the estimation of Gaussian term structure models
Author(s)
Juneja, J.
Type of Research
Peer-Reviewed Journal Articles
Date Published
2013, After July
Contribution Type
Discipline-based scholarship (basic research)
Contribution Category
C
Points
7
Publication Title
Review of Quantitative Finance and Accounting
Publisher
Springer
Location
USA
Digital Object Identifier
10.1007/s11156-013-0396-2
URL
http://link.springer.com/article/10.1007/s11156-013-0396-2/fulltext.html
Abstract
This paper provides an evaluation of five methods, proposed in the literature, for extracting factors used in the estimation of Gaussian affine term structure models. We assert that irrespective of the method used for extracting state variables, cross-sectional and serial correlations exist in measurement errors. However, using a simulation design which is consistent with the data, we show that parameter estimation using the Kalman filter and the model-free method are quite precise in the presence of serial and cross-sectional correlations in the error term, and, in the presence of different measurement errors, the Kalman filter demonstrates strong empirical tractability.