{"title":"为什么Cochrane-Piazzesi模型可以预测国债收益率?","authors":"Riccardo Rebonato , Ken Nyholm","doi":"10.1016/j.jempfin.2025.101650","DOIUrl":null,"url":null,"abstract":"<div><div>We explain why the Cochrane–Piazzesi (CP) model, which uses a single tent-shaped linear combination of forward rates, is so effective at predicting bond excess returns. By using a novel statistical test coupled with a popular resampling technique, first we rule out the possibility that the high predictability may be an artefact of in-sample overfitting. Then we find that, contrary to explanations proposed in the original CP paper, neither the specific tent shape of the factor loadings nor the four-to-five-year yield spread are essential for the model’s predictive power. Instead, our analysis suggests that the predictive power of the CP model lies in its ability to identify the cointegration relationship among the quasi-unit-root forward rate regressors needed to produce the stationary process of excess returns. To support this interpretation we show that cointegration relationships among forward rates directly provide strong predictors of excess returns, and we propose that the cointegration modes of attraction generate at least part of the excess returns. Our findings shed new light on the source of bond return predictability captured by the CP factor and highlight the link between cointegration properties and the dynamics of yields.<span><span><sup>1</sup></span></span></div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"84 ","pages":"Article 101650"},"PeriodicalIF":2.4000,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Why does the Cochrane–Piazzesi model predict treasury returns?\",\"authors\":\"Riccardo Rebonato , Ken Nyholm\",\"doi\":\"10.1016/j.jempfin.2025.101650\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>We explain why the Cochrane–Piazzesi (CP) model, which uses a single tent-shaped linear combination of forward rates, is so effective at predicting bond excess returns. By using a novel statistical test coupled with a popular resampling technique, first we rule out the possibility that the high predictability may be an artefact of in-sample overfitting. Then we find that, contrary to explanations proposed in the original CP paper, neither the specific tent shape of the factor loadings nor the four-to-five-year yield spread are essential for the model’s predictive power. Instead, our analysis suggests that the predictive power of the CP model lies in its ability to identify the cointegration relationship among the quasi-unit-root forward rate regressors needed to produce the stationary process of excess returns. To support this interpretation we show that cointegration relationships among forward rates directly provide strong predictors of excess returns, and we propose that the cointegration modes of attraction generate at least part of the excess returns. Our findings shed new light on the source of bond return predictability captured by the CP factor and highlight the link between cointegration properties and the dynamics of yields.<span><span><sup>1</sup></span></span></div></div>\",\"PeriodicalId\":15704,\"journal\":{\"name\":\"Journal of Empirical Finance\",\"volume\":\"84 \",\"pages\":\"Article 101650\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2025-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Empirical Finance\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0927539825000726\",\"RegionNum\":2,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Empirical Finance","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0927539825000726","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
Why does the Cochrane–Piazzesi model predict treasury returns?
We explain why the Cochrane–Piazzesi (CP) model, which uses a single tent-shaped linear combination of forward rates, is so effective at predicting bond excess returns. By using a novel statistical test coupled with a popular resampling technique, first we rule out the possibility that the high predictability may be an artefact of in-sample overfitting. Then we find that, contrary to explanations proposed in the original CP paper, neither the specific tent shape of the factor loadings nor the four-to-five-year yield spread are essential for the model’s predictive power. Instead, our analysis suggests that the predictive power of the CP model lies in its ability to identify the cointegration relationship among the quasi-unit-root forward rate regressors needed to produce the stationary process of excess returns. To support this interpretation we show that cointegration relationships among forward rates directly provide strong predictors of excess returns, and we propose that the cointegration modes of attraction generate at least part of the excess returns. Our findings shed new light on the source of bond return predictability captured by the CP factor and highlight the link between cointegration properties and the dynamics of yields.1
期刊介绍:
The Journal of Empirical Finance is a financial economics journal whose aim is to publish high quality articles in empirical finance. Empirical finance is interpreted broadly to include any type of empirical work in financial economics, financial econometrics, and also theoretical work with clear empirical implications, even when there is no empirical analysis. The Journal welcomes articles in all fields of finance, such as asset pricing, corporate finance, financial econometrics, banking, international finance, microstructure, behavioural finance, etc. The Editorial Team is willing to take risks on innovative research, controversial papers, and unusual approaches. We are also particularly interested in work produced by young scholars. The composition of the editorial board reflects such goals.