3. Electronic Theses and Dissertations (ETDs) - All submissions
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Item Application of machine learning algorithms to predict the closing price of the Johannesburg Stock Exchange all-share index(2020) Makgwedi, Precious MakganotoStock markets are regarded as one of the most important indicators of the economy’s strength and development. Predicting stock prices is of critical importance for investors who wish to minimise the risks of investments. Stock price prediction is a difficult task since stock prices are influenced by factors such as the financial status of the company, socioeconomic conditions of the country, political atmospheres, and natural hazards. The Efficient Market Hypothesis (EMH) states that stock markets behave like a random walk and due to this reason, it is complex to forecast the stock market. Researchers use time series forecasting, technical, and fundamental analyses to predict the stock values while proving or disproving the EMH. In the past, researchers used traditional methods such as Autoregressive Integrated Moving Average (ARIMA) to predict stock prices. Currently, deep learning architectures are widely used to solve time-dependent problems and can provide a huge push to the problem of stock price prediction. The main objective of this study is to develop a framework that forecasts the daily closing price of All- Share index data based on deep learning techniques. To achieve this objective, Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) are employed. A Vector Autoregressive (VAR) model is used to benchmark the deep learning techniques. The analysis is based on the Financial Times Stock Exchange (FTSE)/ Johannesburg Stock Exchange (JSE) All-Share (J203) data collected from Iress Expert. The results show that all the methods are able to predict the closing price of the index. GRU predicted the future closing price with an average Mean Absolute Percentage Error (MAPE) of 9.349% maximum while LSTM was able to predict with the maximum average error of 9.459%. A VAR model performed with the maximum average error of 2.152%.Item Share price reaction to dividend cuts and omissions: evidence from South Africa(2020) Raedani, Phumudzo PreciousThis study examines the effects of dividend cuts and omission on the performance of South African firms listed on the Johannesburg Stock Exchange (JSE) over the sample period of 1996 and 2016. The study examines an overlooked area in dividend change studies and is motivated by the conflicting conclusions that exist in finance literature around what dividend reductions signal to the market. The study made use of a total of 94 firms which comprises both the dividend decrease and omission sample as well as the control (peer) firm sample. The study employs the event study methodology using the control firm and the capital asset pricing model (CAPM) to test for the effect of dividend cuts and omissions on the share price. The study also tests for the relationship between dividend cuts and omissions and variables such as the return on assets(ROA), the market to book ratio (M/B) and the capital expenditure (CAPEX). The study finds negative abnormal returns for both control adjusted returns and the CAPM adjusted returns. The market to book ratio results show that there is a decrease in growth prospects for both high and low market to book ratio firms. In terms of the return on asset analysis, dividend decrease sample firms were found have had poor operating performance years prior the dividend cut announcement and continued to experience poor operating performance years after the cut, suggesting that dividend decrease firms were not as profitable and hence the reason to cut dividends. The dividend decrease firms were found to increase capital expenditures even years after the dividend decrease announcement whereas the opposite was found for control firms. The overall results are consistent with international literature where changes in dividends appear to be linked to changes in future growth opportunitiesItem Does idiosyncratic risk derive price momentum and long term reversal :evidence from the Johannesburg Stock Exchange(2019) Mahsayanyika, RichThis study examines if the idiosyncratic risk is the main source behind the persistence of price momentum and reversal effects. Idiosyncratic risk limits arbitrage, regardless of the arbitrageur’s diversification. Price momentum is prevalent only in high idiosyncratic risk stocks, highlighting that idiosyncratic risk limits arbitrage in price momentum mispricing. Long-term reversal is not related to idiosyncratic risk. Long term reversal stocks generates a smaller aggregate return than price momentum stocks, so the findings along with those in related studies suggest that underreaction and overreaction might be the main driving force behind long term reversal returns. The findings of this study are consistent with some of South African literature which suggest that momentum is a more persistent investing strategy than long term reversal on the Johannesburg Stock Exchange (JSE).Item Monetary policy and stock market liquidity: empirical evidence from the Johannesburg Stock Exchange (JSE)(2018) Nyika, Patrick. H.e recent financial crisis has given liquidity an important role in the financial market functioning. Especially in small size equity markets like the African, lack of liquidity has been reported as major issue. In order to source the causes of the lack of liquidity, this study investigated the relationship between monetary policy and stock market liquidity in South Africa using fixed and random effect estimations for stock specific effect and VAR impulse response function for portfolio analysis. We first estimate a Taylor rule for South Africa, which we augment with a financial indicator adapted from the literature and use the difference between actual and fitted values to measure monetary stance. The literature on the monetary policy rules in South Africa revealed M3 as the instrument used by the SARB before the period of inflation targeting that started in February 2000. We then used the monetary stance computed from the Taylor rule and the growth rate of M3 as measures of monetary policy. The panel regression analysis, with monetary policy measured by the growth rate of money supply, is only significant in the case of illiquidity models while monetary policy shows no effect on liquidity models in that case. In the case of monetary policy as measured by Taylor rule, the turnover model revealed a negative relationship, but weakly significant. Further, a positive and significant effect at 5% and 10% was revealed for Amihud’s illiquidity measure and Roll’s price impact measure. The impulse response analysis shows different results as compared to the stock specific analysis. The study found that monetary policy, as measured by money supply, has a positive effect on the liquidity variables which are turnover and trading volume; and also found that the monetary policy, as measured by the Taylor monetary stance, has a positive effect on illiquidity variables.Item Capital asset pricing model test on the Johannesburg stock exchange(2018) Mokgele, Kabelo KeosiThe Capital Asset Pricing Model (CAPM), jointly accredited to Markowitz (1952), Treynor (1961), Sharpe (1964), Lintner (1965) and Mossin (1966), provides that, at equilibrium, the return on all risky assets is attributable to their covariance with the market portfolio. This paper studies whether the CAPM holds for the South African market (represented by the Johannesburg Stock Exchange), by using the methodology developed by Fama and Macbeth (1973). Furthermore, the paper expands on other factors that influence asset returns and interrogates alternative asset pricing models. The findings of the study on individual assets rejects CAPM in the context of South Africa. This is consistent with other empirical studies. CAPM is also rejected for the Industrial Index as well as the Top 40 index. What is interesting to note however, is that for the Resources index, CAPM is validated.Item Target price accuracy: South African equity market(2019) Sebele, PotsoMuch that has been studied around target prices has generally revealed weak prediction ability on individual analysts’ level. In this report, we pursue an unprecedented approach and analyse consensus target price forecasting ability. Like past academic works, we conclude that, consensus target price accuracy in forecasting future market share price is inadequate, with consistent prediction errors that are fairly auto-correlated. We also discovered that target price prediction errors are correlated to earnings forecast errors suggesting that the latter is underpinned by earnings forecast. Regarding our last objective, we found out that prediction errors are positively related to implicit return, earnings per share and price per book value but negatively related to market capitalisation of companies.Item Analysing the efficiency of the Johannesburg Stock Exchange using the magic formula(2018) Vincent, Christopher JohnThis study examined the efficiency of South African markets, namely the Johannesburg Stock Exchange (JSE) through the use of a value investing strategy called the “magic formula”, which was created by Joel Greenblatt and published in his 2006 book “the little book that beats the market”. This study back tested the magic formula on the JSE from 2000 to 2016. It ranked stocks according to the magic formula methodology, using earnings yield and return on capital to derive portfolios. The portfolios were then compared against the JSE All Share Index (the market). The magic formula showed evidence of outperformance of the market over the period, even when accounting for risk. The magic formula was compared against other portfolios derived from value investing ratios, namely ROA, ROE and EY. The ROA portfolio produced the best risk-adjusted results, but all value investing portfolios outperformed the market providing evidence against efficient markets.Item Stealth trading on South African equities market(2019) Arumero, AshleyThe research examines if there are traders on the Johannesburg Stock Exchange (JSE) with information advantage. By employing high frequency data from 53 securities, the findings show that agents engage in small size trades to camouflage their information advantage. The inverted U-shaped plot was obtained from the dynamic probability of small trades model, which is consistent with the literature. The findings show that stealth trading is more frequent during the middle of the day on the JSE than any other time of the day. About 38% of traders were trading from an information advantage during the period of analysis. This implies that the remaining 62% of the traders engage in uninformed tradesItem The fama-french five-factor model: evidence from the JSE(2018) Cox, ShaunThe desire to explain the returns of shares listed on stock exchanges has long driven research into asset pricing models. The formation of the Capital Asset Pricing Model (CAPM) served as the starting point for almost all models derived to describe share returns. Further research into returns discovered that there were various risk factors that impacted share returns; these could be captured by market value (size) and the book-to-market ratio (value). In 1993, Eugene Fama and Kenneth French used these to expand on the CAPM. The Fama-French three-factor model created a framework to model returns and allowed for other researchers to explore asset pricing further. In 2015, Fama and French augmented their profitability and investment factors onto their threefactor model. The author of this study postulated that these additional factors may proxy for quality, a formally undefined characteristic of shares that is used in selecting investments. This study tested the effectiveness of the five-factor model and the additional factors in explaining returns on the Johannesburg Securities Exchange (JSE). The five-factor model was compared to the traditional size-value three-factor model as well as other three-factor models that incorporated the additional factors. Furthermore, the study looked at what premiums are present in the returns on the JSE and captured by the various models tested. The results show that the size-value and size-profitability three-factor models best describe time-series returns when comparing models. The five-factor model best explains the crosssection of returns and overall, the results identify a strong inverse size effect and value and market premiums. Interestingly, the strength of the original size-value three-factor model is reinforced. The additional factors of profitability and investment contribute to explaining the returns on the JSE. Furthermore, profitability could be seen as a contributing factor in a “quality premium”. In addition to being a risk factor, quality could also be used as a filter through which the traditional premiums like size or value can be unlocked.Item The determinants of fund performance: does size really matter in South Africa?(2018) Ramos, D.This research seeks to better understand the determinants of fund performance in a South African context. It will focus extensively on fund size, past performance, fees, and expense ratios and their relationship with performance. While other research has shown an inverse relationship between fees and performance, it seems divided on the relationship between fund size and performance in various markets. Due to the high regulatory environment, asset managers in South Africa face multiple restrictions that have limited their investible universe. The results presented in this research show that funds in South Africa exhibit the “Hot Hands” phenomenon as well as it documents the negative relationship between fees and performance for South African funds. Lastly, results show a positive relationship between fund size and performance where funds in South Africa enjoy economies of scale.