A re-examination of the empirical performance of the Longstaff and Schwartz two-factor term structure model using real yield data created by Robert Faff and Sirimon Treepongkaruna

By:

Faff, Robert [author]

Contributor(s):

Treepongkaruna, Sirimon [co-author]

Material type: Text

TextSeries: Australian journal of management ; Volume 38, number 2Los Angeles: Sage, 2013Content type:

text

Media type:

unmediated

Carrier type:

volume

ISSN:

0312-8962

Subject(s):

Longstff-Schwartz two-factor model -- Multi-country test -- Real yield data

LOC classification:

HD31 AUS

Online resources:

Click here to access online

Abstract: In this study, we apply the Longstaff and Schwartz (1992) two-factor term structure model to real yields across eight countries. As such, we improve on many prior studies that have inappropriately tested this formulation using nominal yield data. We use the generalized method of moments to test the cross-sectional restrictions imposed by the Longstaff and Schwartz model, as well as the Cox–Ingersoll–Ross one-factor model. Further, we compare the forecasting ability from both models. Our findings support the superiority of the two-factor model. We confirm general reliability of prior research in this area, despite the unfortunate reliance on nominal data in such earlier tests.

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Holdings
Item type	Current library	Call number	Vol info	Status	Notes	Date due	Barcode
Journal Article	Main Library - Special Collections	HD31 AUS (Browse shelf(Opens below))	Vol. 38, no.2 (pages333-352)	Not for loan	For in house use only

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In this study, we apply the Longstaff and Schwartz (1992) two-factor term structure model to real yields across eight countries. As such, we improve on many prior studies that have inappropriately tested this formulation using nominal yield data. We use the generalized method of moments to test the cross-sectional restrictions imposed by the Longstaff and Schwartz model, as well as the Cox–Ingersoll–Ross one-factor model. Further, we compare the forecasting ability from both models. Our findings support the superiority of the two-factor model. We confirm general reliability of prior research in this area, despite the unfortunate reliance on nominal data in such earlier tests.

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