Next Article in Journal
Capital Regulation and Bank Risk-Taking Behavior: Evidence from Pakistan
Previous Article in Journal
Impacts of Credit Default Swaps on Volatility of the Exchange Rate in Turkey: The Case of Euro
Article Menu

Export Article

Open AccessArticle
Int. J. Financial Stud. 2016, 4(3), 15; doi:10.3390/ijfs4030015

Back to the Future Betas: Empirical Asset Pricing of US and Southeast Asian Markets

Faculty of Business Administration, Stamford International University, Bangkok 10250, Thailand
Academic Editor: Nicholas Apergis
Received: 7 October 2015 / Revised: 11 July 2016 / Accepted: 12 July 2016 / Published: 20 July 2016
View Full-Text   |   Download PDF [224 KB, uploaded 20 July 2016]


The study adds an empirical outlook on the predicting power of using data from the future to predict future returns. The crux of the traditional Capital Asset Pricing Model (CAPM) methodology is using historical data in the calculation of the beta coefficient. This study instead uses a battery of Generalized Auto Regressive Conditional Heteroskedasticity (GARCH) models, of differing lag and parameter terms, to forecast the variance of the market used in the denominator of the beta formula. The covariance of the portfolio and market returns are assumed to remain constant in the time-varying beta calculations. The data spans from 3 January 2005 to 29 December 2014. One ten-year, two five-year, and three three-year sample periods were used, for robustness, with ten different portfolios. Out of sample forecasts, mean absolute error (MAE) and mean squared forecast error (MSE) were used to compare the forecasting ability of the ex-ante GARCH models, Artificial Neural Network, and the standard market ex-post model. Find that the time-varying MGARCH and SGARCH beta performed better with out-of-sample testing than the other ex-ante models. Although the simplest approach, constant ex-post beta, performed as well or better within this empirical study. View Full-Text
Keywords: CAPM; empirical; GARCH; ex-ante beta; artificial neural network; time-varying beta CAPM; empirical; GARCH; ex-ante beta; artificial neural network; time-varying beta
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Supplementary material

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

French, J. Back to the Future Betas: Empirical Asset Pricing of US and Southeast Asian Markets. Int. J. Financial Stud. 2016, 4, 15.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Int. J. Financial Stud. EISSN 2227-7072 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top