An Analysis of Herding Behaviour during Market Cycles in South Africa

Herding behaviour can be captured by the relationship between share price movements with the market, typified by beta. We examine herding behaviour for the period 1995 to 2011 and find that it is absent overall, yet present during bear market periods only. When examined alongside the market cycle, herding appears to dramatically fluctuate before a market contraction. Conceptually, herding can be seen as an explanatory factor for the existence of a nonlinear market model. Our findings infer that a negative market reaction (contraction) is preceded by an increase in herding. The evidence of herding in during a South African market contraction can thus impact financial forecasts and volatility estimates of the market. Further, it could possibly indicate the level of confidence of market participants – both experienced and inexperienced individuals tend to follow the group consensus in times of a market downturn, yet deviate from the group consensus in times of a market upturn

The dynamics of market efficiency: testing the adaptive market hypothesis in South Africa

A thesis submitted to the School of Economic and Business Sciences, Faculty of Commerce, Law and Management, University of the Witwatersrand in fulfilment of the requirements for the degree of Doctor of Philosophy (Ph/D). Johannesburg, South Africa June 2016In recent years, the debate on market efficiency has shifted to providing alternate forms of the hypothesis, some of which are testable and can be proven false. This thesis examines one such alternative, the Adaptive Market Hypothesis (AMH), with a focus on providing a framework for testing the dynamic (cyclical) notion of market efficiency using South African equity data (44 shares and six indices) over the period 1997 to 2014. By application of this framework, stylised facts emerged. First, the examination of market efficiency is dependent on the frequency of data. If one were to only use a single frequency of data, one might obtain conflicting conclusions. Second, by binning data into smaller sub-samples, one can obtain a pattern of whether the equity market is efficient or not. In other words, one might get a conclusion of, say, randomess, over the entire sample period of daily data, but there may be pockets of non-randomness with the daily data. Third, by running a variety of tests, one provides robustness to the results. This is a somewhat debateable issue as one could either run a variety of tests (each being an improvement over the other) or argue the theoretical merits of each test befoe selecting the more appropriate one. Fourth, analysis according to industries also adds to the result of efficiency, if markets have high concentration sectors (such as the JSE), one might be tempted to conclude that the entire JSE exhibits, say, randomness, where it could be driven by the resources sector as opposed to any other sector. Last, the use of neural networks as approximators is of benefit when examining data with less than ideal sample sizes. Examining five frequencies of data, 86% of the shares and indices exhibited a random walk under daily data, 78% under weekly data, 56% under monthly data, 22% under quarterly data and 24% under semi-annual data. The results over the entire sample period and non-overlapping sub-samples showed that this model's accuracy varied over time. Coupled with the results of the trading strategies, one can conclude that the nature of market efficiency in South Africa can be seen as time dependent, in line with the implication of the AMH.MT201

Do Mutual Funds Attract the Right Investor? A Stochastic Dominance Approach

Decision theory is concerned with identifying values and uncertainties in a given decision that result in the optimal outcome (Wald, 1939). It is one of the core aspects of any financial or investment decision. We consider the case where the investor has the choice between a passive index (such as a market index) and an actively managed mutual fund. Our analysis aims to determine which option an investor will choose based on a statistical ranking method known as stochastic dominance. We then evaluate this choice against the background information supplied by the mutual fund to ascertain whether the choice given by stochastic dominance is indeed in line with the investor profile given by the mutual fund. It is found that of the 11 mutual funds examined over the sample period of April 2006 to April 2013, only 4 attract the correct type of investor, 3 attract a mixture of investors and 4 attract (arguably) the wrong type of investor

Forecasting changes in the South African volatility index. A comparison of methods

Increased financial regulation with tougher capital standards and additional capital buffers has made understanding volatility in financial markets more imperative. This study investigates various forecasting techniques in their ability to forecast the South African Volatility Index (SAVI). In particular, a time-delay neural network’s forecasting ability is compared to more traditional methods. A comparison of the residual errors of all the forecasting tools used suggests that the time-delay neural network and the historical average model have superior forecasting ability over traditional forecasting models. From a practical perspective, this suggests that the historical average model is the best forecasting tool used in this study, as it is less computationally expensive to implement compared to the neural network.  Furthermore, the results suggest that the SAVI is extremely difficult to forecast, with the volatility index being purely a gauge of investor sentiment in the market, rather than being seen as a potential investment opportunity.&nbsp

Fusion investing: an esoteric approach to portfolio formation

This study contributes to the debate on active and passive portfolio management by providing an alternate means of constructing an active portfolio. This “fusion strategy” has underpinnings in the realm of behavioural finance, namely the value-growth phenomenon and the momentum effect. The fusion strategy developed in this study was compared against two passive benchmarks and four active benchmarks. All returns are calculated net of transaction costs, initially set to 1% per month per share. Statistical testing, done via stochastic dominance, yielded inconclusive results in the majority of cases. The exception however, was that Fund B stochastically dominated the fusion strategy at second order. This implies that a risk-averse investor would prefer to invest in Fund B. By the use of Sharpe and Treynor ratios, the results were also inconclusive. However, the Sortino ratio shows that the fusion strategy outperforms all benchmarks chosen, except Fund A. The performance of the fusion strategy was also not induced by either a sector rotation strategy, the existence of the January effect or by the level of transaction costs

The short-run performance of equity issues in South Africa: Bad timing or a last resort?

Understanding the stock market’s reaction to secondary equity offerings (SEOs) is vital for managers who are commonly tasked with deciding on how to finance their firm’s operations. This study investigated the short-run performance of firms conducting equity issuance on the Johannesburg Stock Exchange (JSE) over the period 1998–2015 by exploring both rational and behavioural models in predicting SEO behaviour. Event-study analysis reveals that the market generally reacts negatively to the announcement of SEOs with a statistically significant average two-day cumulative abnormal return of -2.6%. We also found that the probability of a firm conducting a SEO is significantly negatively related to the number of years listed and the future share return. Although it would make sense that more corporate activity takes place during periods of high investor sentiment, there is no significant evidence that firms conducting SEOs are attempting to time the market

Complementing South African inflation surveys: A suitable forecasting tool

Central banks currently perform inflation expectation surveys in order to better align their inflation expectations with that of the general public. However, surveys are time-consuming, complicated, expensive and not always accurate, thus compromising the credibility of these expectations. The complexity of inflation targeting and the difficulty of forecasting in real time can also cause policymakers to consider more basic models, which can lead to inexact forecasts. This article employs less complicated models, such as the seasonally adjusted autoregressive integrated moving average and Holt-Winters exponential smoothing models, to provide equally reliable forecasts. A more complex approach in the form of a non-linear autoregressive neural network process was also employed to model the strategic and rational manner in which the general public formulates their expectations. Overall, the forecast estimates provided by these models were superior when compared with the inflation expectations provided by the International Monetary Fund, South African Reserve Bank and Bureau for Economic Research

Is consumer confidence an indicator of JSE performance?

While most studies examine the impact of business confidence on market performance, we instead focus on the consumer because consumer spending habits are a natural extension of trading activity on the equity market. This particular study examines investor sentiment as measured by the Consumer Confidence Index in South Africa and its effect on the Johannesburg Stock Exchange (JSE). We employ Granger causality tests to investigate the relationship across time between the Consumer Confidence Index and market performance. The results show weak evidence of a contemporaneous relationship; however, significant evidence of a Granger caused relationship is apparent. Further, changes in investor sentiment Granger-cause changes in the two indices used, generally with a lag of 9 and 12 months, but not vice versa. Thus, we find that Consumer Confidence leads JSE performance during our sample period. Our research provides evidence contradicting the common perception of consumer confidence lagging market performance, particularly in the South African context