South African Financial Market Research Articles

The influences of psychological factors on investors decision making in the South African derivative market

Studies in behavioral finance have shown that human behavior often diverges from the rationality assumed by economists, as their decisions can occasionally be swayed by their emotional and psychological states. Given this concern, the study examines psychological factors influencing individual decision-making in the South African financial market. A structured questionnaire was used in collecting data from 414 participants who are individual investors actively involved in trading in the Johannesburg stock exchange market with the application of the random sampling method. The main objective of this study is to explore the psychological variables or biases that determine the investment decision-making of individual investors. Furthermore, this paper investigates psychological factors such as Anchoring, Herding, Overconfidence and Representative biases in investment decision-making. Findings revealed that all the variables, overconfidence, herding, anchoring and representative heuristics have a relationship with each other but the only variable that influences the individual investment decision is the representative heuristic while less consideration is given to another variable. The results of this study would help financial advisors understand the high importance of psychological factors and help them integrate behavioral insights into investment strategies. This will in turn help them provide better services to their clients. It will also help individual investors to acknowledge and understand the psychological factors influencing investment decisions and how to take note of them to make better decisions. Policymakers can consider the implications of psychological biases on market stability.

Stochastic Default Risk Estimation Evidence from the South African Financial Market

AbstractThis paper provides empirical studies of the estimation of defaultable bonds in the South African financial markets. The key objective is to estimate the unobservable factors affecting bond yields for South African major banks. The maximum likelihood approach is adopted for the estimation methodology. Multi-dimensional Cox–Ingersoll–Ross (CIR)-type factor models are considered and compared. Extended Kalman filtering techniques are employed in order to tackle the situation that the factors cannot be observed directly. We find empirical evidence that default risk varies with the business cycle, increased sharply in the South African financial market during COVID-19 and the $$\alpha$$ α -CIR model performs better than the classical CIR model.

Quantification of the stock market value at risk by using FIAPARCH, HYGARCH and FIGARCH models

<abstract><p>The South African financial market is developing with periods of high and low volatility. Employing an adequate volatility model is essential to manage market risk. This research study was designed to investigate the effectiveness of the fractionally integrated asymmetric power autoregressive conditional heteroskedasticity contrasted with long-memory GARCH-type models, such as the fractionally integrated generalized autoregressive conditional heteroskedasticity and the hyperbolic generalized autoregressive conditional heteroskedasticity for producing the measure of market risk known as the value at risk. These long-memory GARCH-type models assume that the distributions of the index returns follow normal, student-$ t $, skewed student-$ t $ and generalized error distributions. The historical closing price time series of the Johannesburg Stock Exchange all share, the mining and the banking indices are considered. The value at risk and its backtesting for short and long trading positions on the different confident levels are computed and they correspond to the right and left quantiles of the return distributions, respectively. The results reveal that FIAPARCH with a standard student-$ t $ distribution is an appropriate model for producing a robust value at risk in the context of mining and banking indices. Alternatively, FIGARCH with the assumed skewed student-$ t $ distribution model is a good fit to produce a value at risk for the Johannesburg Stock Exchange All Share Index.</p></abstract>

Integrated Governance, Risk, and Compliance (GRC) and Combined Assurance: A Comparative Institutional Study

The combined assurance model plays a pivotal role in integrating a company’s governance, risk, and compliance (GRC) processes. More than a decade after the South African financial market initiated the model through King III Report in 2009, the Indonesian financial market strived to adopt it in 2013. However, very few companies in Indonesia have reported its implementation. We hypothesized that institutional theory could explain the phenomenon. This comparative study thus used qualitative and quantitative approaches to analyze the adoption of the combined assurance model in South African and Indonesian markets. Qualitative content analysis was employed to interrogate the annual reports of 130 companies listed on the Johannesburg Stock Exchange and the Indonesia Stock Exchange to identify professions and their activities in implementing the model. Afterwards, an estimation model was built using binary logistic regression based on the identified variables. It was found that regulative and normative pillars were the most determining factors in implementing a combined assurance model. In addition, it was found that the integrated report approach and market capitalization were associated with model implementation. These findings can be the basis for state and professions (i.e., authorities, regulators, and standard-setting bodies), especially in Indonesia, to enhance the companies’ integrated GRC. Keywords: combined assurance; corporate governance; institutional theory; risk management; internal audit

Examining stylized facts and trends of FTSE/JSE TOP40: a parametric and Non-Parametric approach

<abstract><p>It is critical in risk and portfolio management to identify groups or classes of financial returns. Portfolio diversification is one of the first decisions made during the portfolio construction phase, and it entails allocating assets among various asset class groups to maximize the risk/reward trade-off. Therefore, this research provides a detailed examination of empirical analysis concerning the characterization of financial markets. In this study, we use parametric and non-parametric approaches to look at stylized facts and patterns of the FTSE/JSE Top40, which comprises the top 40 holdings companies in the South African financial market. To the best of our knowledge, this is the first time a model of this type has been used to create a map that characterizes this index. Our findings indicated that the majority of the properties of the data were valid including among others, clustering volatility, monthly seasonal effects and significant autocorrelation (or serial correlation) on logarithmic returns. Moreover, we found that intra-week trend effects exist, whereas the weekend effect has practically vanished in the FTSE/JSE Top40. With regard to the transition probabilities of the MS(2)-GJR-GARCH (1,1) model, the FTSE/JSE Top40 index had a 98.8% chance of exhibiting long memory, while the volatility had a 99.6% chance of exhibiting long memory.</p></abstract>

Stochastic Default Risk Estimation: Evidence from the South African Financial Market

Stochastic Default Risk Estimation: Evidence from the South African Financial Market

Financial Stress Index and Economic Activity in South Africa: New Evidence

The importance of a sound and stable financial system and by extension economic stability was brought to the fore by the global financial crisis (GFC). The economic and social costs of the GFC have renewed the commitment of stakeholders in the financial sector including central banks to develop instruments and methodologies that will be useful in monitoring financial stress within the financial system and the real economy. This study contributes to the growing literature by developing a financial stress indicator for the South African financial market. The financial stress indicator (FSI) is a single aggregate indicator that is constructed to reflect the systemic nature of financial instability and also to measure the vulnerability of the financial system to both internal and external shocks. Using the principal component analysis (PCA), the results show that financial stress can be identified by the financial stress indicator. Furthermore, using a recursive Vector Autoregression (VAR) model to estimate the impact of financial stress on output and investment, the result shows that financial stress has a negative impact on economic growth and investment, though not immediately. FSI is very useful for gauging the effectiveness of government measures to mitigate the impact of financial stress. Concerted effort to stimulate investment and domestic production by relevant stakeholders is necessary to mitigate the impact of financial stress. This will go a long way to alleviating the impact of the financial stress on industrial production, employment and the economy at large.

Evaluating South Africa’s market risk using asymmetric power auto-regressive conditional heteroscedastic model under heavy-tailed distributions

Orientation: Value-at-risk (VAR) and other risk management tools, such as expected shortfall (conditional VAR), are heavily reliant on a suitable set of underlying distributional conjecture. Thus, distinguishing the underlying distribution that best captures all properties of stock returns is of great interest to both scholars and risk managers. Research purpose: Comparing the execution of the generalised auto-regressive conditional heteroscedasticity (GARCH)-type model combined with heavy-tailed distributions, namely the Student’s t -distribution, Pearson type-IV distribution (PIVD), generalised Pareto distribution (GPD) and stable distribution (SD), in estimating VAR of Johannesburg Stock Exchange (JSE) All Share Price Index (ALSI) returns. Motivation for the study: The proposed models have the potential to apprehend volatility clustering and the leverage effect through the GARCH scheme and at the same time model the heavy-tailed behaviour of the financial returns. Research approach/design and method: The GARCH-type model combined with heavy-tailed distributions, namely the Student’s t -distribution, PIVD, GPD and SD, is developed to estimate VAR of JSE ALSI returns. The model performances are assessed through Kupiec likelihood ratio test. Main findings: The results show that the asymmetric power auto-regressive conditional heteroscedastic models combined with GPD and PIVD are the robust VAR models for South African’s market risk. Practical/managerial implications: The outcomes of this study are expected to be of salient value to financial analysts, portfolio managers, risk managers and financial market researchers, thus giving a better understanding of the South African financial market. Contributions/value-add: Asymmetric power auto-regressive conditional heteroscedastic model combined with heavy-tailed distributions provides a good option for modelling stock returns.

The Nexus Between Johannesburg Stock Exchange and the United States Unemployment Rate Announcement: An Impulse Response Analysis

The study explores the relationship between the unemployment rate in the United States and South Africa’s stock prices from the beginning of 2013 to the last day 2017. The objective of this paper is to examine the impact of the US unemployment rate announcement on the South African financial market. Results of Impulse Response analysis show that there is a very minimal impact from the US unemployment announcement to South Africa’s stock prices which disappears within two days of the announcement. In addition, the Johannesburg stock exchange index marginally responds to own shocks, which marginally fades away within two days. These findings imply that the changes in the US employment policies have a direct ripple effect on the South African macroeconomic environment, its investing public sentiments and corporate confidence on the future prospects of businesses.

The impact of flexible corporate governance disclosures on value relevance. Empirical evidence from South Africa

PurposeConsidering that the Johannesburg Stock Exchange (JSE) has enacted in its Listings Requirements, compliance of listed firms to International Financial Reporting Standards (IFRS) and King Code of Good Corporate Governance, this study aims to investigate the impact of internal corporate governance attributes on the value relevance of accounting information in South Africa.Design/methodology/approachThe fixed effect generalised least squares regression is used for the period from 2002 to 2014. Proxies for internal corporate governance are the size of the board, leadership structure, board activity, staggered board, boardroom independence, presence of key committees and board gender diversity. Value relevance is measured using the adjusted R2 derived from a regression of stock price on earnings and equity book values by following Ohlson’s accounting-based valuation framework.FindingsThe findings suggest that the net asset value per share is value-relevant in South African listed firms and also when the boardroom is largely independent. The value of earnings per share (EPS) is more robust when corporate governance structures, such as separating the roles of chief executive officer and chairperson, proportion of board-independent board members and presence of board committees, are in place. This suggests that EPS favours agency and resource dependence theories.Practical implicationsThe value relevance of accounting information in the South African financial market underscores the importance of requisite rules and supervision regarding financial reporting to allow asset owners and managers in the allocation of capital decisions. This study supports the view that corporate governance plays a key role in ensuring, amongst others, credible financial reporting. The outcome of this study could inform the JSE to enforce, even stricter, compliance with IFRS and corporate governance to improve the value relevance of financial information.Social implicationsSignificant corporate governance reforms around the world suggest that regulators and policy makers consider corporate governance as a pertinent tonic in ensuring, amongst others, credible financial reporting. The implications of the study might assure users of financial information of how compliance to corporate governance practices may influence the value of the firm. This paper provides empirical evidence in the South African context that EPS, unlike net asset value per share, is driven by corporate governance structures.Originality/valueThe period of this study is unique, because it covers a relatively stable economic period before the financial crisis, a challenging and unstable period of time when the financial crisis materialised, and the aftermath of the financial crisis. In addition, the examination period of the study also covers the two corporate governance reforms in South Africa, King II in 2002 and King III in 2009, as well as the new Companies Act No. 71 of 2008. These exogenous factors may influence the results.

A comparative cross-regime analysis on the performance of GARCH-based value-at-risk models: Evidence from the Johannesburg stock exchange

A topic of recent interest in financial risk management is the predictive accuracy of Value-at-risk (VaR) models for adequate capitalization under different market conditions (or regimes). This article assesses the forecasting performance of popular GARCH-based volatility models in the context of VaR estimation. In particular, we conduct a cross-regime analysis between time periods whereby market conditions experiences a shift. Stock returns data from the FTSE/JSE Africa All Share index were selected for the evaluation of both long and short positions of trade. Despite prior findings of the long memory models dominating in the South African financial market, we conclude that such dominance does not necessary hold when assessed under different regimes of the market. Moreover, our findings indicated a need for implementations of model switching policies, which may provide significant improvements in forecasting and minimize chances of VaR estimates falling short of actual trading losses.

Computations and Performance Analysis of Self-Financing Fixed-Mix Investment Portfolio Strategies in a South African Financial Market

The potential of active portfolio management with fixed-mix strategies is analysed under the systemic risk settings of the derivative market and the financial assets market. The fast exponential growth of fixed-mix portfolios under the non-degeneracy condition, which is the non-constancy of the price ratios and as well as the prices’s total returns, and the stationary condition, (see [Dempster, Evsteegniv an Schenk-Hopp´e, in Journal of Mathematical Economics, 46 (2010), pp. 248-266]), asserts a potential to uphold such conditions with financial engineered transactions. The proxies which analytically hold the assumptions and the required conditions of constant rebalanced portfolios are studied by analysing the dynamics of stochastic prices of futures and forward contracts on commodity prices. The mean-reversion typical settings of the prices of traded assets declare the non-degeneracy condition and the associated stationarity form on the marking-to-market process of a traded instrument. The performed computations of portfolio strategies in the South African financial market, without considering assets dividend rates and trading costs, show the superiority of fixed-mix portfolios over counter leveraged effective risk increased optimal buy and hold portfolios. The superiority is shown to be a tactical problem.

The Impact of Monetary Policy on Financial Market in South Africa: A VAR Analysis

Like in many other countries, the South African financial market facilitates the process of raising capital by channelling funds to more productive economic activity, thereby building the nation's economy while enhancing job opportunities and wealth creation. The aim of this paper is to assess the impact of monetary policy on financial market in South Africa. It is important to constantly look into this interaction since policy decisions have a direct influence on financial market. A negative response from the market side may jeopardise economic stability. The study uses the vector autoregressive (VAR) model to evaluate the impact of monetary policy on financial market in South Africa. The model consists of five policy instruments as variables; namely: money supply (M3), real exchange rate(ER), discount Rate (R), consumer price index (CPI), gross domestic product (GDP) and the two market related variables: Stock market turnover (S) and Bond market turnover (B). Data is obtained from SARB and OECD databases for a period of 53 quarters from 2000:Q1 to 2013:Q1. By the use of impulse response function (IRF), the study found that given current economic situation in South Africa, stock market turnover reacts positively to money supply; discount rate; real exchange and GDP shocks. On the other hand stock market turnover reacts negatively to CPI economic shocks. To correct CPI negative impact on markets, we suggest that the policymakers could envisage a contractionary monetary policy translated by a proportional cut in money supply through the sales of government securities.

The relationship between βeta and stock returns in the JSE securities exchange in South Africa

The purpose of this study was is to examine the relationship between stock βeta and returns in the JSE Securities Exchange. If the model is applicable in its entirety or can explain the beta-stock returns relationship, it raises an important academic question, mainly, how should the South African financial market be viewed by investors and portfolio managers, given the political-social-economical classifications that South Africa finds itself in, sometimes referred to as developing, emerging or underdeveloped? The time-series data used was from Sharenet as well as from the South African Reserve Bank macro-economic time series data. The sample period consisted of 10 years of monthly time series data between January 2001 and December 2010. Regression analysis was applied using the conditional approach. When using the conditional capital asset pricing model (CAPM) and cross-sectional regression analysis, the findings strongly supported the significant relationship between stock excess returns and βeta. However, the results do not provide strong evidence of a CAPM relation between risks and realized return trade-off in the South African financial markets. These results demonstrate that the South African financial markets are complex and financial tools, such as the CAPM can be used to explain complex financial phenomenon as in other developed markets, although complete reliance on the CAPM should be relied upon.

On the analysis of cross-correlations in South African market data

We report briefly on an application of random matrix theory to the analysis of SA financial market data (An Analysis of cross-correlations in South African financial market data, e- print cond-mat/0402389). Correlation matrices C are constructed from 10 years of daily data for stocks listed on the Johannesburg Stock Exchange from January 1993 to December 2002. Spectral properties of C are tested against random matrix predictions. We highlight some quantitative differences which arise when treating prices as existing only when measured, as opposed to interpolating missing or illiquid trading days with a zero-order hold.

102 Years of South African financial market history

Extracted from text ... Number 56 - Part 5 C Firer and M Staunton* 102 Years of South African financial market history *Respectively Graduate School of Business, University of Cape Town, Private Bag, Rondebosch 7701, Republic of South Africa and London Business School Email: cfirer@gsb.uct.ac.za and mstaunton@london.edu 1. Introduction An important aspect of research in investments is a study of the past. In order to answer questions dealing with the expected returns and risks from equity, bond and bill markets, to establish yardsticks for judging the worth of new projects and to understand what returns investors in shares and bonds may require, a ..

Immunisation in South Africa

ABSTRACTMost empirical research on immunisation has not considered such issues as, for instance, transaction costs, nor has the convexity of portfolios been quantified. Furthermore, this research has been based on data from overseas capital markets. An important study using South African data tended to be ‘theoretical’. This article attempts to overcome the shortcomings referred to in the above research. It assesses the feasibility of immunisation in South Africa and attempts to keep it as practical as possible. The results are encouraging, although imperfect. The evidence tends to indicate that, with the increasing sophistication of the South African financial market, bond practitioners who possess knowledge of bond immunisation techniques should have a distinct advantage over their competitors.