Are Bond Returns Predictable with Real-Time Macro Data?

52 Pages Posted: 23 Jan 2018 Last revised: 5 Mar 2019

See all articles by Dashan Huang

Dashan Huang

Singapore Management University - Lee Kong Chian School of Business

Fuwei Jiang

Central University of Finance and Economics (CUFE)

Guoshi Tong

Renmin University

Guofu Zhou

Washington University in St. Louis - John M. Olin Business School; China Academy of Financial Research (CAFR)

Date Written: March 2019

Abstract

We reaffirm the stylized fact that bond risk premia are time-varying with macroeconomic condition, even with real-time macro data instead of commonly used final revised data. While real-time data are noisier and render standard forecasts insignificant, we find that, with four efficient target-driven methods, they still contain enough information to predict bond returns significantly both in- and out-of-sample. The predictability can also yield substantial economic value to a mean-variance investor. Moreover, the factors extracted from real-time data predict future macroeconomic condition. Consistent with asset pricing theory, the predicted bond returns are countercyclical.

Keywords: Bond Return Predictability, Real Time Macro Data, Vintage, PCA, Big Data, Machine Learning

JEL Classification: C22, C53, G11, G12, G17

Suggested Citation

Huang, Dashan and Jiang, Fuwei and Tong, Guoshi and Zhou, Guofu, Are Bond Returns Predictable with Real-Time Macro Data? (March 2019). Asian Finance Association (AsianFA) 2018 Conference. Available at SSRN: https://ssrn.com/abstract=3107612 or http://dx.doi.org/10.2139/ssrn.3107612

Dashan Huang

Singapore Management University - Lee Kong Chian School of Business ( email )

50 Stamford Road
Singapore, 178899
Singapore

HOME PAGE: http://dashanhuang.weebly.com/

Fuwei Jiang

Central University of Finance and Economics (CUFE) ( email )

39 South College Road
Haidian District
Beijing, Beijing 100081
China

Guoshi Tong

Renmin University ( email )

59 Zhongguancun Street
Beijing, 100872
China

Guofu Zhou (Contact Author)

Washington University in St. Louis - John M. Olin Business School ( email )

Washington University
Campus Box 1133
St. Louis, MO 63130-4899
United States
314-935-6384 (Phone)
314-658-6359 (Fax)

HOME PAGE: http://apps.olin.wustl.edu/faculty/zhou/

China Academy of Financial Research (CAFR)

Shanghai Advanced Institute of Finance
Shanghai P.R.China, 200030
China

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