Estimation of Affine Term Structure Models with Spanned or Unspanned Stochastic Volatility

61 Pages Posted: 15 Aug 2013 Last revised: 9 Apr 2017

See all articles by Drew Creal

Drew Creal

University of Chicago - Booth School of Business - Econometrics and Statistics

Jing Cynthia Wu

University of Notre Dame - Department of Economics; National Bureau of Economic Research (NBER)

Date Written: September 30, 2014

Abstract

We develop new procedures for maximum likelihood estimation of affine term structure models with spanned or unspanned stochastic volatility. Our approach uses linear regression to reduce the dimension of the numerical optimization problem yet it produces the same estimator as maximizing the likelihood. It improves the numerical behavior of estimation by eliminating parameters from the objective function that cause problems for conventional methods. We find that spanned models capture the cross-section of yields well but not volatility while unspanned models fit volatility at the expense of fitting the cross-section.

Keywords: affine term structure models, unspanned stochastic volatility, estimation

Suggested Citation

Creal, Drew and Wu, Jing Cynthia, Estimation of Affine Term Structure Models with Spanned or Unspanned Stochastic Volatility (September 30, 2014). Chicago Booth Research Paper No. 13-72. Available at SSRN: https://ssrn.com/abstract=2310258 or http://dx.doi.org/10.2139/ssrn.2310258

Drew Creal

University of Chicago - Booth School of Business - Econometrics and Statistics ( email )

Chicago, IL 60637
United States

Jing Cynthia Wu (Contact Author)

University of Notre Dame - Department of Economics ( email )

Notre Dame, IN 46556
United States

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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