Why Does the Cieslak–Povala Model Predict Treasury Returns? A Reinterpretation

R. Rebonato, Takumi Hatano
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引用次数: 0

Abstract

This article presents a simple reformulation of the restricted Cieslak and Povala return-predicting factor, which retains by construction exactly the same (impressive) explanatory power as the original but affords an alternative and attractive interpretation. What determines the future returns, the new formulation shows, is a function of the distance of the yield-curve level and the slope not from a fixed reference level, but from a conditional one, determined by a function of the long-term inflation. The decomposition also allows a clear attribution of the predictive power of the Cieslak and Povala factor between the conditional level and slope deviations. The authors present new empirical evidence to show that, consistent with the interpretation they present, inflation surprises are powerful out-of-sample predictors of Treasury excess returns.
为什么Cieslak–Povala模型预测国债收益率?重新解读
本文对受限制的Cieslak和Povala回归预测因子进行了简单的重新表述,通过构建保留了与原始完全相同的(令人印象深刻的)解释力,但提供了另一种有吸引力的解释。新公式表明,决定未来收益的是收益率曲线水平与斜率之间距离的函数,而不是与固定参考水平之间的距离,而是与有条件的参考水平之间的距离,这一距离由长期通胀的函数决定。分解还允许对条件水平和斜率偏差之间的Cieslak和Povala因子的预测能力进行明确的归因。作者提出了新的经验证据,表明与他们的解释一致,通胀意外是美国国债超额回报的有力样本外预测指标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Fixed Income
Journal of Fixed Income Economics, Econometrics and Finance-Economics and Econometrics
CiteScore
1.10
自引率
0.00%
发文量
23
期刊介绍: The Journal of Fixed Income (JFI) provides sophisticated analytical research and case studies on bond instruments of all types – investment grade, high-yield, municipals, ABSs and MBSs, and structured products like CDOs and credit derivatives. Industry experts offer detailed models and analysis on fixed income structuring, performance tracking, and risk management. JFI keeps you on the front line of fixed income practices by: •Staying current on the cutting edge of fixed income markets •Managing your bond portfolios more efficiently •Evaluating interest rate strategies and manage interest rate risk •Gaining insights into the risk profile of structured products.
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