Trend and Cycle in the Yield Curve: A Procedure for Forecasting Recessions

Jacob Smith
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Abstract

This paper presents a new procedure for forecasting recessions utilizing short-term (slope) dynamics present in the yield curve. Building on a large body of literature chronicling the relationship between the shape of the yield curve and the business cycle, this paper employs Dynamic Nelson-Siegel modeling to define the level, slope, and curvature characteristics of the term structure through time. Given these dynamics, the trend and cycle are extracted using various decomposition techniques. It is shown that cycles present within the slope factor are very robust predictors of recessions, correctly identifying recessions as much as eighteen months in advance. A “Predictive Power Score” is developed to quantify the procedure’s performance. This score shows the superiority of the procedure over other common leading indicators including the yield spread.
收益率曲线的趋势和周期:预测衰退的程序
本文提出了一种利用收益率曲线中的短期(斜率)动态预测衰退的新方法。在大量记录收益率曲线形状与商业周期之间关系的文献基础上,本文采用动态尼尔森-西格尔模型来定义期限结构随时间变化的水平、斜率和曲率特征。给定这些动态,使用各种分解技术提取趋势和周期。研究表明,在斜率因子内出现的周期是非常可靠的衰退预测因子,可以提前18个月正确识别衰退。开发了“预测能力评分”来量化程序的性能。这个分数表明该程序优于其他常见的领先指标,包括收益率差。
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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