EconPapers    
Economics at your fingertips  
 

Equity premium prediction: Are economic and technical indicators unstable?

Fabian Baetje and Lukas Menkhoff

International Journal of Forecasting, 2016, vol. 32, issue 4, 1193-1207

Abstract: We show that technical indicators deliver stable economic value in predicting the US equity premium over the out-of-sample period from 1966 to 2014. The results tentatively improve over time, and beat alternatives over a large continuum of sub-periods. In contrast, economic indicators work well only until the 1970s, but lose predictive power thereafter, even when considering the last crisis. Translating the predictive power of technical indicators into a standard investment strategy delivers an annualized average Sharpe ratio of 0.55 p.a. (after transaction costs) for investors who entered the market at any point in time.

Keywords: Equity premium predictability; Economic indicators; Technical indicators; Break tests (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (29)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0169207016300267
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Equity Premium Prediction: Are Economic and Technical Indicators Unstable? (2016) Downloads
Working Paper: Equity premium prediction: Are economic and technical indicators instable? (2015) Downloads
Working Paper: Equity premium prediction: Are economic and technical indicators instable? (2015) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:32:y:2016:i:4:p:1193-1207

DOI: 10.1016/j.ijforecast.2016.02.006

Access Statistics for this article

International Journal of Forecasting is currently edited by R. J. Hyndman

More articles in International Journal of Forecasting from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-23
Handle: RePEc:eee:intfor:v:32:y:2016:i:4:p:1193-1207