scholarly journals The historically realised equity risk premium as a guide to future expectations in an emerging market: The case of South Africa

2008 ◽  
Vol 2 (1) ◽  
pp. 89-104
Author(s):  
Jesse De Beer

The concept of an equity risk premium (ERP) is fundamental to modern financial theory and central to every decision at the heart of corporate finance. Efforts to quantify ERP are well rewarded by insights into the stability and dynamics of long-term investment performance. Such efforts require the quantification of both historically realised (ex post) and expected future (ex ante) premiums. Finding an appropriate proxy for the expected (ex ante) ERP remains a challenging aspect. One widely used application is the use of long-term averages of observed market premiums as a proxy for expected returns. The aim of this paper is to analyse the appropriateness of the historical methodology of estimating expected ERP in the South African context. The analysis in this paper suggests that analysing past historical figures remains useful in the SA context. This is supported by the results of the statistical analysis, showing stationarity of the ERP time-series, meaning that the true mean does not change over time. This implies that the historical average mean may be used as a proxy for the long-run expected ERP. However, the well-documented problems relating to large standard errors (predictability problem) and relevance due to changing circumstances are also evident in the SA data. Thus, investors would be well advised to analyse the past and apply informed judgments as to future differences, if any, when attempting to arrive at fair forecasts.

2018 ◽  
Vol 26 (3) ◽  
pp. 311-343
Author(s):  
Sungjeh Moon ◽  
Joonhyuk Song

This paper introduces two risk factors which are the covariance between long-run consumption growth and cash flows and the duration of cash flow, and investigates how these factors serve to explain the KOSPI return risk premiums. Based on our empirical results comparing the proposed two-factor cash flow model with the standard benchmark models such as CAPM and Fama-French 3-factor model (FF-3F), using KOSPI equity including de-listed stocks, the cash flow model explains 74.7% of the cross-section of equity risk premium while CAPM and FF-3F model explains 41.9% and 64.1% to the maximum, respectively, showing that the cash-flow model is superior in explaining the risk premium factor structure compared with the benchmark models. Also, the pricing error is only 4% in the two-factor cash flow model, while CAPM and FF-3F are 7.7% and 4.7%, respectively, indicating the cash flow model outperforms the standard benchmark models in pricing error as well. These results can be interpreted that the cross section of the equity risk premium is related to a firm’s cash flow and long-run consumption, and therefore the growth rate of consumption in the long run rather than contemporaneous consumption growth rate has a greater influence on the determination of the risk premium.


2005 ◽  
Vol 2 (4) ◽  
pp. 185-194 ◽  
Author(s):  
John R. Graham ◽  
Campbell R. Harvey

2019 ◽  
Vol 22 (2) ◽  
pp. 195-212 ◽  
Author(s):  
Jie Zhu

The expected equity risk premium is a key input of many asset prcing models in…nance. There exist a number of methods to estimate the risk premium. It is alsowell documented that the risk premium is time-varying. This paper brie‡y reviews twodi¤erent approaches. More speci…cally, the historical average and relative estimationare taken into closer examination. The …rst approach is applied to estimate equity riskpremium for stock markets in Greater China when the stock markets were recoveringfrom the bottom. Then the relative estimation approach is also adopted to empiricaldata to justify the …ndings in the …rst one, which takes into consideration the lowerrequired rate of return for Chinese investors due to lack of investment opportunities.After making these adjustments, we …nd that risk premium in mainland China is close torisk premium for Hong Kong and Taiwan markets. All of those markets have higher riskpremium compared to US market. The risk premium for Shanghai and Shenzhen marketare about 8% and 10% respectively. For Hong Kong and Taiwan these numbers become8% and 9%, where the long-term forward-looking risk premium for US market is about4%.


2015 ◽  
Vol 14 (3) ◽  
pp. 47-57
Author(s):  
Santhosh Kumar

The equity risk premium has been of paramount importance in the field of finance and is still a widely utilised central element for every risk return model in corporate finance, asset pricing and other fields of economic literature. This research captures the differences in the ex-post behaviour of equity risk premium between developed and emerging markets .Further, an investigation has been made into the impact of global integration on the ERP across G7 countries and 7 emerging countries. .The analysis has shown a decline in the ERP of developed nations and an upward trend in emerging markets over the chosen sub-sample period. We found out that there exists low correlation in ERP of emerging markets in comparison with developed markets


2016 ◽  
Vol 13 (4) ◽  
pp. 146-159 ◽  
Author(s):  
Sunil Poshakwale ◽  
Pankaj Chandorkar

The authors investigate the impact of structural monetary policy shocks on ex-post equity risk premium (ERP) of aggregate and sectoral FTSE indices and 25 Fama-French style value-weighted portfolios. They find that monetary policy shocks negatively affect the ERP but at the sectoral level, the magnitude of the response is heterogeneous. Further, monetary policy shocks have a significant negative (positive) impact on the ERP before (after) the implementation of quantitative easing (QE). The empirical evidence provided in the paper sheds light on the equity market’s asymmetric response to the BoE’s policy before and after the monetary stimulus. Keywords: monetary policy, equity risk premium, quantitative easing, monetary policy shocks, structural vector autoregression, Bank of England, Taylor monetary policy rule, unconventional monetary policy, output gap, inflation gap, Okun’s law. JEL Classification: E5, E30, G0, G1


2004 ◽  
Vol 2004 (1) ◽  
pp. 53-62 ◽  
Author(s):  
Jeremy J. Siegel

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