Estimating the market risk premium on The Johannesburg Stock Exchange using ex post and ex ante models

1987 ◽  
Vol 16 (30) ◽  
pp. 7-17
Author(s):  
S R Favish ◽  
J F Affleck-Graves
2014 ◽  
Vol 30 (6) ◽  
pp. 1939
Author(s):  
Kathleen Hodnett

<p>This study attempts to establish the cyclical nature of the value-growth spread on the Johannesburg Stock Exchange (JSE) over the period from 1 January 1997 through 31 December 2013, and subsequently undertakes to determine if the recent value-growth spread could be useful to forecast the near-term market risk premium. The three value-growth benchmarks used to classify value and growth stocks include earnings/price ratio (E/P), book/price ratio (B/P) and sales/price ratio (S/P). The ratio between the median S/P ratio for the value portfolio versus the growth portfolio is found to be the highest and most volatile over the examination period, which suggests that the relative valuation of value and growth stocks based on S/P could be cyclical and reflective of the market sentiments and degrees of risk aversion. The prediction of forward market risk premium using the trailing average of S/P value-growth spread achieved the highest R-squared of 26.79%. In addition, predicting forward market risk premium using the other two value-growth spreads is also statistically significant. Examining the coefficients of the regressions reveals that although a significant portion of the forward market risk premium is left unexplained, there exists a significantly positive correlation between recent value-growth spreads and near-term market risk premiums on the JSE. This implies that higher future reward could be expected for equity investments when the value risk premium is higher than its historical average, and vice versa.</p>


2011 ◽  
Vol 47 (1) ◽  
pp. 115-135 ◽  
Author(s):  
Mariano González ◽  
Juan Nave ◽  
Gonzalo Rubio

AbstractThis paper explores the cross-sectional variation of expected returns for a large cross section of industry and size/book-to-market portfolios. We employ mixed data sampling (MIDAS) to estimate a portfolio’s conditional beta with the market and with alternative risk factors and innovations to well-known macroeconomic variables. The market risk premium is positive and significant, and the result is robust to alternative asset pricing specifications and model misspecification. However, the traditional 2-pass ordinary least squares (OLS) cross-sectional regressions produce an estimate of the market risk premium that is negative, and significantly different from 0. Using alternative procedures, we compare both beta estimators. We conclude that beta estimates under MIDAS present lower mean absolute forecasting errors and generate better out-of-sample performance of the optimized portfolios relative to OLS betas.


2014 ◽  
Vol 23 (2) ◽  
pp. 51-58 ◽  
Author(s):  
Austin Murphy ◽  
Liang Fu ◽  
Terry Benzschawel

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