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Forecasting Government Bond Risk Premia Using Technical Indicators

50 Pages Posted: 22 Aug 2011 Last revised: 13 Nov 2013

Jeremy Goh

Singapore Management University - Lee Kong Chian School of Business

Fuwei Jiang

Central University of Finance and Economics (CUFE) - School of Finance

Jun Tu

Singapore Management University - Lee Kong Chian School of Business

Guofu Zhou

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

Date Written: July 28, 2013

Abstract

While economic variables have been used extensively to forecast bond risk premia, little attention has been paid to technical indicators which are widely used by practitioners. In this paper, we study the predictive ability of a variety of technical indicators vis-a-vis the economic variables. We find that technical indicators have significant in both in- and out-of-sample forecasting power. Moreover, we find that using information from both technical indicators and economic variables increases the forecasting performance substantially. We also find that the economic value of bond risk premia forecasts from our methodology is comparable to that of equity risk premium forecasts.

Keywords: Bond risk premium predictability, Economic variables, Technical analysis, Moving average rules, Volume, Out-of-sample forecasts, Principal components

JEL Classification: C53, C58, G11, G12, G17

Suggested Citation

Goh, Jeremy and Jiang, Fuwei and Tu, Jun and Zhou, Guofu, Forecasting Government Bond Risk Premia Using Technical Indicators (July 28, 2013). 25th Australasian Finance and Banking Conference 2012; Asian Finance Association (AsFA) 2013 Conference. Available at SSRN: https://ssrn.com/abstract=1914227 or http://dx.doi.org/10.2139/ssrn.1914227

Jeremy Goh

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

469 Bukit Timah Road
Singapore 912409
Singapore

Fuwei Jiang

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

39 South College Road
Haidian District
Beijing, 100081
China

Jun Tu (Contact Author)

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

50 Stamford Road
#04-01
Singapore, 178899
Singapore

Guofu Zhou

CAFR (China Academy for Financial Research)

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

Washington University in St. Louis - Olin School of Business ( 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/

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