动态期限结构模型的估计

IF 0.9 Q3 BUSINESS, FINANCE
G. Duffee, Richard Stanton
{"title":"动态期限结构模型的估计","authors":"G. Duffee, Richard Stanton","doi":"10.1142/S2010139212500085","DOIUrl":null,"url":null,"abstract":"We study the finite-sample properties of some of the standard techniques used to estimate modern term structure models. For sample sizes and models similar to those used in most empirical work, we reach three surprising conclusions. First, while maximum likelihood works well for simple models, it produces strongly biased parameter estimates when the model includes a flexible specification of the dynamics of interest rate risk. Second, despite having the same asymptotic efficiency as maximum likelihood, the small-sample performance of Efficient Method of Moments (a commonly used method for estimating complicated models) is unacceptable even in the simplest term structure settings. Third, the linearized Kalman filter is a tractable and reasonably accurate estimation technique, which we recommend in settings where maximum likelihood is impractical.","PeriodicalId":45339,"journal":{"name":"Quarterly Journal of Finance","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"149","resultStr":"{\"title\":\"Estimation of Dynamic Term Structure Models\",\"authors\":\"G. Duffee, Richard Stanton\",\"doi\":\"10.1142/S2010139212500085\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We study the finite-sample properties of some of the standard techniques used to estimate modern term structure models. For sample sizes and models similar to those used in most empirical work, we reach three surprising conclusions. First, while maximum likelihood works well for simple models, it produces strongly biased parameter estimates when the model includes a flexible specification of the dynamics of interest rate risk. Second, despite having the same asymptotic efficiency as maximum likelihood, the small-sample performance of Efficient Method of Moments (a commonly used method for estimating complicated models) is unacceptable even in the simplest term structure settings. Third, the linearized Kalman filter is a tractable and reasonably accurate estimation technique, which we recommend in settings where maximum likelihood is impractical.\",\"PeriodicalId\":45339,\"journal\":{\"name\":\"Quarterly Journal of Finance\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2012-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"149\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Quarterly Journal of Finance\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1142/S2010139212500085\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quarterly Journal of Finance","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1142/S2010139212500085","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 149

摘要

我们研究了一些用于估计现代期限结构模型的标准技术的有限样本性质。对于与大多数实证工作中使用的相似的样本量和模型,我们得出了三个惊人的结论。首先,虽然最大似然对简单模型很有效,但当模型包含利率风险动态的灵活规范时,它会产生强烈的偏差参数估计。其次,尽管具有与最大似然相同的渐近效率,但即使在最简单的期限结构设置中,有效矩量法(一种用于估计复杂模型的常用方法)的小样本性能也是不可接受的。第三,线性化卡尔曼滤波是一种易于处理且相当准确的估计技术,我们推荐在最大似然不切实际的情况下使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimation of Dynamic Term Structure Models
We study the finite-sample properties of some of the standard techniques used to estimate modern term structure models. For sample sizes and models similar to those used in most empirical work, we reach three surprising conclusions. First, while maximum likelihood works well for simple models, it produces strongly biased parameter estimates when the model includes a flexible specification of the dynamics of interest rate risk. Second, despite having the same asymptotic efficiency as maximum likelihood, the small-sample performance of Efficient Method of Moments (a commonly used method for estimating complicated models) is unacceptable even in the simplest term structure settings. Third, the linearized Kalman filter is a tractable and reasonably accurate estimation technique, which we recommend in settings where maximum likelihood is impractical.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Quarterly Journal of Finance
Quarterly Journal of Finance BUSINESS, FINANCE-
CiteScore
1.10
自引率
0.00%
发文量
0
期刊介绍: The Quarterly Journal of Finance publishes high-quality papers in all areas of finance, including corporate finance, asset pricing, financial econometrics, international finance, macro-finance, behavioral finance, banking and financial intermediation, capital markets, risk management and insurance, derivatives, quantitative finance, corporate governance and compensation, investments and entrepreneurial finance.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信