Estimating affine multifactor term structure models using closed-form likelihood expansions

• 成果类型: Article
• 署名作者: Ait-Sahalia, Yacine; Kimmel, Robert L.
• 署名单位: Princeton University; National Bureau of Economic Research; Princeton University; Universite Catholique de Lille; EDHEC Business School
• 刊物名称: JOURNAL OF FINANCIAL ECONOMICS
• ISSN/ISSBN: 0304-405X
• DOI: 10.1016/j.jfineco.2010.05.004
• 发表日期: 2010
• 页码: 113-144
• 关键词: term structure; Multifactor; Interest rates; Affine; Closed-form maximum-likelihood

摘要

We develop and implement a technique for closed-form maximum likelihood estimation (MLE) of multifactor affine yield models. We derive closed-form approximations to likelihoods for nine Dai and Singleton (2000) affine models. Simulations show our technique very accurately approximates true (but infeasible) MLE. Using US Treasury data, we estimate nine affine yield models with different market price of risk specifications. MLE allows non-nested model comparison using likelihood ratio tests; the preferred model depends on the market price of risk. Estimation with simulated and real data suggests our technique is much closer to true MLE than Euler and quasi-maximum likelihood (QML) methods. (C) 2010 Elsevier B.V. All rights reserved.