Relevant bibliographies by topics / Johannesburg Stock Exchange

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  1. Journal articles

Academic literature on the topic 'Johannesburg Stock Exchange'

Author: Grafiati
Published: 4 June 2021
Last updated: 28 July 2024

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Journal articles on the topic "Johannesburg Stock Exchange"

1

Bradfield, D. J. "A note on the seasonality of stock returns on the Johannesburg Stock Exchange." South African Journal of Business Management 21, no. 1/2 (1990): 7–9. http://dx.doi.org/10.4102/sajbm.v21i1.909.

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Evidence from studies on the major stock exchanges world-wide suggests that stocks listed on these markets earn abnormally high returns in the month of January. In this article the seasonality of stocks on the Johannesburg Stock Exchange is empirically investigated. Surprisingly no January effects are found, however, a significant December seasonal effect is documented. A plausible explanation for this finding is offered.
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2

Bradfield, D. J. "A note on the seasonality of stock returns on the Johannesburg Stock Exchange." South African Journal of Business Management 21, no. 1/2 (1990): 7–9. http://dx.doi.org/10.4102/sajbm.v21i1/2.909.

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Evidence from studies on the major stock exchanges world-wide suggests that stocks listed on these markets earn abnormally high returns in the month of January. In this article the seasonality of stocks on the Johannesburg Stock Exchange is empirically investigated. Surprisingly no January effects are found, however, a significant December seasonal effect is documented. A plausible explanation for this finding is offered.
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3

Kilian, N. "ESG Metrics Disclosures for Index-Listed Companies in Paris, New York and Johannesburg." European Company Law 20, Issue 4 (2023): 76–83. http://dx.doi.org/10.54648/eucl2023012.

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Against the background of Index listed companies, for example the Paris Stock Exchange (Euronext) CAC 40 ESG Index, New York (NY) Stock Exchange iShares Core MSCI World UCITS ETF Index and the Johannesburg Stock Exchange (JSE) Equity Fund or Index, this article will review similarities in ESG metrics disclosures relevant to each index and whether a stock exchange could rate an index for ESG compliance without making use of an external rating company, for example MSCI. This article also discusses the method used by MSCI to rate listed companies for ESG compliance and whether asset or fund managers could rate their investment portfolios independently from a stock exchange. In this regard, three asset managers – BNP Paribas, Blackrock and Old Mutual – are examined for similarities in their ESG rating processes. In addition, this article explains whether the above stock exchanges are using the same ESG metrics or not. Paris Stock Exchange, New York Stock Exchange, Johannesburg Stock Exchange, ESG, asset manager index, asset manager ESG compliance, ESG rating, United Nations Sustainable Stock Exchanges Initiative
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4

Fateye, Oluwatosin Babatola, Damilola Damilola, and Professor Ajayi. "Modelling of Daily Price Volatility of South Africa Property Stock Market Using GARCH Analysis." Journal of African Real Estate Research 7, no. 2 (2022): 24–42. http://dx.doi.org/10.15641/jarer.v7i2.1144.

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The study examined the volatility of the daily market price of listed property stocks on the Johannesburg Stock Exchange (JSE) for a 10year period (2008-2017). The study used daily prices from January 2, 2008 to December 29, 2017 of twelve (12) quoted property companies out of the twenty-seven (27) listed on Johannesburg Stock Exchange (SA REIT Association, 2020). The study computed the average daily price of the selected (12) property stocks and was used as a proxy for the daily market price for the property stock market in the analysis. The study modelled SA-REIT market price volatility using generalised autoregressive conditional heteroskedasticity (GARCH 1, 1). The GARCH model reported that the previous day's information of both the daily market price (ARCH term) and the volatility (GARCH term) have a positive and significant (p<.05) effect on the current day’s daily market price volatility in the property stock market. The result of the model implies that investment in the property stock market is strongly driven by positive news on daily price than a negative shock; meaning that South Africans' investors are more sensitive and exhibit a sharp response to good news on daily market price than bad news when thinking of investing in listed property company shares on Johannesburg Stock Exchange.
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5

Ward, Mike. "Risk on The Johannesburg Stock Exchange." De Ratione 8, no. 2 (1994): 99–114. http://dx.doi.org/10.1080/10108270.1994.11435052.

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6

Hoffman, AJ. "Stock return anomalies: Evidence from the Johannesburg Stock Exchange." Investment Analysts Journal 41, no. 75 (2012): 21–41. http://dx.doi.org/10.1080/10293523.2012.11082542.

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7

Nyakurukwa, Kingstone. "Information Flow Between the Zimbabwe Stock Exchange and the Johannesburg Stock Exchange: A Transfer Entropy Approach." Organizations and Markets in Emerging Economies 12, no. 2 (2021): 353–76. http://dx.doi.org/10.15388/omee.2021.12.60.

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The purpose of this paper is to determine whether there was information flow between the stock markets of Zimbabwe and South Africa during the time the Zimbabwean economy was dollarized. The author used econophysics-based Shannonian and Rényian transfer entropy estimates to establish the flow of information between the markets in tranquil periods as well as at the tails of return distributions. The only significant Shannonian transfer entropy estimate was from Johannesburg Stock Exchange (JSE) resources index to Zimbabwe Stock Exchange (ZSE) mining index. The findings show that the only significant tail dependence was between JSE All Share Index (JALSH) and ZSE Mining on the one hand, and between JSE Resources and ZSE Mining on the other hand. However, the magnitudes of the effective transfer entropy values are relatively low, showing that there are weak linkages between the Zimbabwe Stock Exchange and the Johannesburg Stock Exchange. The lack of significant information flows between the exchanges of the two countries offer opportunities to fund managers for portfolio diversification. From a government point of view, it is imperative that the tempo of economic and political reform be accelerated so that integration between the markets can be fast-tracked. Integrated markets will benefit Zimbabwe as this will reduce the cost of equity and accelerate economic growth.
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8

Oberholzer, Merwe, and Marli Theunissen. "Benchmarking Of Johannesburg Stock Exchange CEO Compensation." International Business & Economics Research Journal (IBER) 11, no. 9 (2012): 1061. http://dx.doi.org/10.19030/iber.v11i9.7189.

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The purpose of the study is to empirically compare CEO compensation benchmarks set by the frequently used Linear Regression Analysis (LRA), which is based on averages and Data Envelopment Analysis (DEA), which is based on best practices. To fulfill this purpose, an empirical investigation on South African listed companies was executed using a sample of 187 Johannesburg Stock Exchange (JSE) companies, grouped into three categories according to their sizes by using total assets, i.e. large, medium and small companies. For the LRA model, total CEO compensation is the dependent variable (y) with return on equity (as a measurement of performance) and total assets (as measurement of company size) as the independent variables (x). In the LRA model, the expected CEO compensation was calculated as a benchmark for each company and then compared to the actual value of the CEO compensation. In the DEA model, total CEO compensation is the input variable and return on equity and total assets the two output variables. The input-orientated technical efficiency estimate was calculated and the input targets (benchmarks for CEO compensation) set by the DEA model were compared to the actual CEO compensation. The study found that, using the LRA model, CEOs are on average actually underpaid in monetary terms by 36.8%, 33.2% and 17.8% for the large, medium and small companies, respectively. In contrast, the results for these three groups using DEA have shown that CEOs are on average actually overpaid in monetary terms by 47.6% 55.3% and 49.9%. This implies that LRA favors CEOs in comparison with the DEA model. Therefore, the study concludes that the frequently used LRA model is probably a reason that contributes to excessive CEO compensation.
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9

Rensburg, P. van, and K. Slaney. "Market Segmentation on the Johannesburg Stock Exchange." Studies in Economics and Econometrics 21, no. 3 (1997): 1–23. http://dx.doi.org/10.1080/03796205.1997.12129110.

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10

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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