Relevant bibliographies by topics / Johannesburg Stock Exchange (JSE)

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Academic literature on the topic 'Johannesburg Stock Exchange (JSE)'

Author: Grafiati
Published: 4 June 2021
Last updated: 16 June 2025

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Journal articles on the topic "Johannesburg Stock Exchange (JSE)"

1

Sarpong, Prince Kwasi, Mabutho Sibanda, and Merle Holden. "Investigating Chaos on the Johannesburg Stock Exchange." Journal of Economics and Behavioral Studies 8, no. 5(J) (2016): 56–67. http://dx.doi.org/10.22610/jebs.v8i5(j).1431.

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This study investigates the existence of chaos on the Johannesburg Stock Exchange (JSE) and studies three indices namely the FTSE/JSE All Share, FTSE/JSE Top 40 and FTSE/JSE Small Cap. Building upon the Fractal Market Hypothesis to provide evidence on the behavior of returns time series of the above mentioned indices, the BDS test is applied to test for non-random chaotic dynamics and further applies the rescaled range analysis to ascertain randomness, persistence or mean reversion on the JSE. The BDS test shows that all the indices examined in this study do not exhibit randomness. The FTSE/JSE All Share Index and the FTSE/JSE Top 40 exhibit slight reversion to the mean whereas the FTSE/JSE Small Cap exhibits significant persistence and appears to be less risky relative to the FTSE/JSE All Share and FTSE/JSE Top 40contrary to the assertion that small cap indices are riskier than large cap indices.
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2

Davidson, Sinclair, and Steven Meyer. "The Monday effect and the Johannesburg Stock Exchange: Revisited." South African Journal of Business Management 24, no. 3 (1993): 83–87. http://dx.doi.org/10.4102/sajbm.v24i3.867.

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The Monday effect is an anomaly that has defied explanation. It has been found to be present in major stock exchanges around the world. Bhana found evidence in favour of this anomaly in the share returns on the Johannesburg Stock Exchange (JSE). In this article the Monday effect on the JSE is reinvestigated in a later period. The methodology employed is superior to that of previous studies. It appears that the Monday effect is no longer present in the pattern of share returns on the JSE. The results of the article suggest that the original methodology creates a bias in favour of finding a Monday effect. Evidence in favour of the trading time hypothesis is found, indicating that no equity growth occurs over weekends.
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3

Ngwakwe, Collins C. "Independent assurance compliance of sustainable development disclosures in the Johannesburg stock exchange firms." Corporate Ownership and Control 10, no. 2 (2013): 226–40. http://dx.doi.org/10.22495/cocv10i2c2art2.

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This paper examines the extent to which the sustainable development disclosures of companies listed on the Johannesburg stock exchange (JSE) comply with independent external assurance. This is necessary to provide information to responsible investors and to assess the sustainable development commitment of firms in the JSE. A sample of firms within the JSE was taken from the Socially Responsible Index (SRI) group and the non-SRI group. Analysis indicates an increase in the number of firms vying for recognition as socially responsible firms in the JSE’s SRI. Furthermore, a chi-square analysis shows that the SRI and non-SRI group of companies have a comparable rate of compliance with the independent external assurance of sustainable development disclosures. Overall findings indicate that the JSE’s SRI initiative has been functional in driving the sustainable development initiatives of firms in the JSE. There is practical evidence of firms’ commitment to carbon reduction, energy efficiency, waste management, black economic empowerment, water efficiency and other sustainable development initiatives. The paper concludes that stock exchanges may be a catalyst for driving sustainable development behaviour in firms located in emerging and developing countries, hence the paper recommends that stock exchanges in these countries may replicate the sustainable development initiative of the Johannesburg Stock Exchange as this may contribute to the sustainable economic development of emerging and developing countries. The paper offers opportunities for future research on the role of global stock exchanges in fostering sustainable development.
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4

Cheteni, Priviledge. "Stock Market Volatility Using GARCH Models: Evidence from South Africa and China Stock Markets." Journal of Economics and Behavioral Studies 8, no. 6(J) (2017): 237–45. http://dx.doi.org/10.22610/jebs.v8i6(j).1497.

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Abstract: This study looks into the relationship between stock returns and volatility in South Africa and China stock markets. A Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model is used to estimate volatility of the stock returns, namely, the Johannesburg Stock Exchange FTSE/JSE Albi index and the Shanghai Stock Exchange Composite Index. The sample period is from January 1998 to October 2014. Empirical results show evidence of high volatility in both the JSE market, and the Shanghai Stock Exchange. Furthermore, the analysis reveals that volatility is persistent in both exchange markets and resembles the same movement in returns. Consistent with most stock return studies, we find that movements of both markets seem to take a similar trajectory.Keywords: GARCH, ARCH effect, JSE index, Shanghai Stock Exchange Composite Index
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5

Bowie, D. C., and D. J. Bradfield. "Improved beta estimation on the Johannesburg Stock Exchange: A simulation study." South African Journal of Business Management 24, no. 4 (1993): 118–23. http://dx.doi.org/10.4102/sajbm.v24i4.872.

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In this article we focus on beta estimation in the thinly-traded environment of the Johannesburg Stock Exchange (JSE). We build on existing literature by evaluating a beta estimation procedure known as the trade-to-trade which has not until now been considered in the context of the JSE. We contrast our results with two known estimation procedures, i.e. the Cohen et al. and the traditional ordinary least squares (OLS). The trade-to-trade methodology, the estimator proposed by Cohen et al. and OLS are objectively assessed for shares typical of the JSE on the basis of unbiasedness and efficiency in the controlled environment of a simulation study. The trade-to-trade technique is found to be superior on both counts and is recommended as the appropriate technique for beta estimation on the JSE.
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6

K. Oseifuah, Emmanuel, and Carl H. Korkpoe. "A Markov regime switching approach to estimating the volatility of Johannesburg Stock Exchange (JSE) returns." Investment Management and Financial Innovations 16, no. 1 (2019): 215–25. http://dx.doi.org/10.21511/imfi.16(1).2019.17.

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The study used the Markov regime switching model to investigate the presence of regimes in the volatility dynamics of the returns of JSE All-Share Index (ALSI). Volatility regimes are as a result of sudden changes in the underlying economy generating the market returns. In all, twelve candidate models were fitted to the data. Estimates from the regime switching model were compared to the industry standard non-switching GARCH (1,1) using the Deviance Information Criteria (DIC). The results show that the two-regime switching EGARCH model with skewed Student t innovations describes better the return of the JSE Index. Additionally, we backtest the model results in order to confirm our findings that the two-regime switching EGARCH is the best of the models for the sample period.
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7

Bonga-Bonga, Lumengo. "The Evolving Efficiency Of The South African Stock Exchange." International Business & Economics Research Journal (IBER) 11, no. 9 (2012): 997. http://dx.doi.org/10.19030/iber.v11i9.7183.

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This paper tests the weak-form efficiency in the South African stock exchange - the Johannesburg Securities Exchange (JSE) - under the hypothesis that emerging markets efficiency evolves through time as these markets constantly enhance their regulatory environment. The paper makes use of the time varying GARCH model in testing this hypothesis. In addition, the paper compares the out-of-sample forecast performance of the time varying and fixed parameter GARCH models in predicting stock returns in the JSE making use of MSE-F statistics for nested models proposed (McCracken, 1999). The findings of the paper show that the two models provide the same conclusion in showing that the JSE has been efficient during the period of the analysis. In addition, the time varying model outperforms the fixed coefficient model in predicting the JSE stock returns. This finding indicates that the time-varying parameter model adds a benefit in testing the weak-form efficiency or modelling stock return in the JSE.
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8

Marozva, Godfrey. "The performance of socially responsible investment funds and exchange-traded funds: Evidence from Johannesburg stock exchange." Corporate Ownership and Control 11, no. 4 (2014): 150–59. http://dx.doi.org/10.22495/cocv11i4p11.

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The research reported in this article explored how the JSE SRI Index performed relative to exchange-traded funds during the period of economic growth as well as during the period of economic decline between 2004 and 2014. The JSE SRI Index and exchange traded funds are analysed by a single factor model as well as other risk-adjusted performance measures including the Sharpe ratio, the Treynor ratio and the M-squared ratio. The single-factor model regression results suggest that during the period of economic growth the JSE SRI index neither significantly outperformed nor underperformed the exchange-traded funds. However, the JSE SRI Index significantly underperformed the exchange-traded funds during the period of economic decline. Further tests that engaged other risk-adjusted measures indicated that the exchange-traded funds performed better than the JSE SRI index in both periods. Based on this research it is recommended that further research be conducted using models that can control for the liquidity difference in funds.
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9

Van der Merwe, R., and J. D. Krige. "Perfect foresight portfolios on the Johannesburg stock exchange." South African Journal of Business Management 48, no. 2 (2017): 1–9. http://dx.doi.org/10.4102/sajbm.v48i2.23.

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The main aim of this study was to determine the effect of unanticipated information, or noise, on the returns of cap-weighted portfolios in various segments of the JSE for the period 1995 to 2014. According to Fuller, Han and Tung (2012), all investors in a segment would gain maximum alpha from a portfolio weighted by ex post market capitalisation – in other words, a ‘perfect foresight’ (PF) portfolio. The PF portfolio is a buy-and-hold portfolio of all shares in a particular segment with weights at the beginning of the return period set to be proportional to the market capitalisation of the shares at the end of the return period. The excess return of the PF portfolio over the benchmark portfolio therefore is an estimate of the effect of unanticipated information on the return of the benchmark portfolio. It provides an estimate of the maximum annual amount of available alpha to all investors involved in that segment in a given year. In this study, the returns of PF portfolios were compared with the All Share, Large Cap, Mid Cap and Small Cap segments of the JSE. Intuitively, information to guide decisions on portfolio weighting would be more valuable and deliver more profit when the cross-sectional standard deviation of share returns is high. Therefore a secondary aim was to investigate the correlation between cross-sectional standard deviation and PF excess return. It was found that a strong positive correlation (more than 90%) existed between cross-sectional standard deviation and PF excess return in all segments. In ascending order of annual PF excess return and average cross-sectional standard deviation the results for the segments were: Large Cap (8% and 29%), All Share (9% and 32%), Mid Cap (13% and 36%) and Small Cap (17% and 43%).
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10

McKane, Graeme, and James Britten. "Liquidity and size effects on the Johannesburg Stock Exchange (JSE)." Investment Analysts Journal 47, no. 3 (2018): 229–42. http://dx.doi.org/10.1080/10293523.2018.1485218.

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