Information in the Term Structure: A Forecasting Perspective

• 成果类型: Article
• 署名作者: Doshi, Hitesh; Jacobs, Kris; Liu, Rui
• 署名单位: University of Houston System; University of Houston; Duquesne University
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2020.3715
• 发表日期: 2021
• 页码: 5255-5277
• 关键词: term structure; forecasting; Loss function; State variables; hidden factor

摘要

The existing literature finds that information not captured by traditional term structure factors helps predict excess bond returns. When estimating no-arbitrage affine term structure models, aligning in-sample and out-of-sample objective functions results in term structure factors that capture information that remains hidden from existing approaches. Specifically, the estimates of the third term structure factor radically differ and are related to the fourth principal component, which helps forecast bond returns. The new objective function leads to substantial improvements in forecasting performance. It also results in higher model term premiums and lower expected future short rates.