关于Diebold和Li预测结果稳健性的说明

A. Simonsen, João Marco Braga da Cunha
{"title":"关于Diebold和Li预测结果稳健性的说明","authors":"A. Simonsen, João Marco Braga da Cunha","doi":"10.2139/ssrn.3181355","DOIUrl":null,"url":null,"abstract":"The paper by Diebold and Li (2006) has become a benchmark in the yield curve forecasting literature, mostly owing to its excellent out-of-sample results. In this note we investigate the robustness of these outcomes in two different ways: (i) in terms of the arbitrary choices in their forecasting experimental design, and (ii) in updated samples up to 2015. In both cases, the fragility of their out-of-sample results became evident. In addition, we propose a novel decomposition method, which reveals that their positive results are unlikely to be caused by any intentionally built feature within their model. Overall, the evidence suggests that the forecasting ability of Dielbold and Li's model is questionable.","PeriodicalId":11495,"journal":{"name":"Econometric Modeling: Capital Markets - Forecasting eJournal","volume":"14 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Note on the Robustness of Diebold and Li's Forecasting Results\",\"authors\":\"A. Simonsen, João Marco Braga da Cunha\",\"doi\":\"10.2139/ssrn.3181355\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper by Diebold and Li (2006) has become a benchmark in the yield curve forecasting literature, mostly owing to its excellent out-of-sample results. In this note we investigate the robustness of these outcomes in two different ways: (i) in terms of the arbitrary choices in their forecasting experimental design, and (ii) in updated samples up to 2015. In both cases, the fragility of their out-of-sample results became evident. In addition, we propose a novel decomposition method, which reveals that their positive results are unlikely to be caused by any intentionally built feature within their model. Overall, the evidence suggests that the forecasting ability of Dielbold and Li's model is questionable.\",\"PeriodicalId\":11495,\"journal\":{\"name\":\"Econometric Modeling: Capital Markets - Forecasting eJournal\",\"volume\":\"14 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Econometric Modeling: Capital Markets - Forecasting eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3181355\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Econometric Modeling: Capital Markets - Forecasting eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3181355","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

Diebold和Li(2006)的论文之所以成为收益率曲线预测文献中的标杆,主要是因为其出色的样本外结果。在本文中,我们以两种不同的方式研究这些结果的稳健性:(i)在预测实验设计中的任意选择方面,以及(ii)在截至2015年的更新样本中。在这两种情况下,他们的样本外结果的脆弱性变得明显。此外,我们提出了一种新的分解方法,该方法揭示了他们的积极结果不太可能是由模型中任何故意构建的特征引起的。总的来说,证据表明Dielbold和Li的模型的预测能力是有问题的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Note on the Robustness of Diebold and Li's Forecasting Results
The paper by Diebold and Li (2006) has become a benchmark in the yield curve forecasting literature, mostly owing to its excellent out-of-sample results. In this note we investigate the robustness of these outcomes in two different ways: (i) in terms of the arbitrary choices in their forecasting experimental design, and (ii) in updated samples up to 2015. In both cases, the fragility of their out-of-sample results became evident. In addition, we propose a novel decomposition method, which reveals that their positive results are unlikely to be caused by any intentionally built feature within their model. Overall, the evidence suggests that the forecasting ability of Dielbold and Li's model is questionable.
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
自引率
0.00%
发文量
0
×
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