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The objective of the study was to comparatively assess the impact of credit risk on the performance of big and small banks in South Africa. Data from audited financial reports of 14 commercial banks were obtained and divided into two panel data sets and analysed using the R-Studio software version 3.5.1 to assess the impact of capital adequacy ratio (CAR), non-performing loan to gross loan (NPLGL), loan-to-deposit ratio (LTDR), leverage ratio (LR), board gender diversity (BGD), with bank size (total asset) and AGE as control variables, on performance, (return on asset [ROA] and return on equity [ROE]). The findings of the study revealed that non-performing loan (NPL), CAR, LR, LTDR and age of banks all have significant and greater impact on performance, as measured by ROA, of small banks when compared with big banks. Surprisingly, NPL was revealed to have a lesser impact on the ROE of small banks as compared to the ROE of big banks but showed no impact on the ROA of big banks during the period of 2008–2017.

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.

This study seeks to investigate herd behaviour among equity mutual fund managers and the performance of mutual funds that trade against the herd in South Africa. The behaviour of mutual funds has an effect on the stability and volatility of stock markets, the ultimate returns to the investors. The study builds upon the efficient market hypothesis, portfolio theory and behavioural finance to provide evidence of the behaviour of mutual funds in an emerging market context using the Johannesburg Stock Exchange. The Lakonishok, Shleifer and Vishney (1991) measure of herding is used to ascertain the behaviour of mutual funds over the period 2006 to 2012. Institutional investors in South Africa are susceptible to the behavioural bias of herding and this phenomenon influences the performance of their funds. Funds that trade in the opposite direction of herd funds are able to put up a superior performance over time. Superior performance, however, does not entice mutual fund investors to invest less in under-performing funds and more in funds that recently show superior performance. These findings imply that following investment waves does not culminate in superior returns in the stock market. Consequently, mutual funds that take an opposite direction to herd funds help stabilize the stock market and lessen the severity of bear markets. This study categorizes mutual funds into 'herding' and 'contrarian' and provides an insight into the performance of each category. Investors who oppose herd behaviour realize greater returns over time while stabilizing the markets at the same time.

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