Thesis (M.M. (Finance & Investment))--University of the Witwatersrand, Faculty of Commerce, Law and Management, Graduate School of Business Administration, 2013. / Recent unexpected variability in the earnings of agribusinesses in South Africa has led stakeholders to ask as to why projected financial performance tended to be so different from the actual results achieved. This paper aims to make an empirical contribution to the discussion on the effects of soft commodity price volatility on the returns of entities whose major business involves derivatives trading in agricultural commodity products. Firstly, mathematical models for commodity price volatility are determined for the major agricultural commodities on the South African Futures Exchange (SAFEX) using the autoregressive conditional heteroskedasticity (ARCH) and the generalised autoregressive conditional heteroskedasticity (GARCH) type of approaches. Secondly, the study then seeks to ascertain whether there are causality links between the commodity price volatility and the returns or earnings realised by selected agribusinesses over time. The paper then discusses some trading strategies that are applicable given that commodity price volatility can be forecasted using the statistical models identified under the study.

Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Management Graduate School of Business Administration University of the Witwatersrand April 2016 / This thesis examined commodity futures on the South African Futures Exchange (SAFEX) from two angles; the investors’ perspective and that of the futures exchange. For the former, the research looked at market inefficiencies and resultant arbitrage opportunities while for the latter, extraordinary market movements are examined by exploring how extreme value analysis (EVA) is ideal for exchange risk management and maintaining market integrity. This broadly leads to four empirical contributions to the literature on commodity futures. Using a variety of time series models, wheat contract anomalies are identified by developing new trading rules whose outcomes are superior to any approach based on chance. Monte Carlo simulation employed in an out-of-sample period after accounting for transaction costs establishes that the trading rules are financially profitable. An examination of information flows across four major markets indicated that the Zhengzhou Commodity Exchange (ZCE) is the most endogenous market, Euronext and the London International Financial Futures Exchange (LIFFE) the most exogenous, while Kansas City Board of Trade (KCBT) is the most influential and sensitive wheat market. SAFEX is a significant receiver of information but does not impact the other markets. Another contribution, analysing maturity effects by incorporating traded volume, change in open interest, and the bid-ask spread while accounting for multicollinearity and seasonality indicates that only wheat supports the so called maturity effect. Lastly, asymmetry is found in long and short positions in SAFEX contracts, and using extreme value theory (EVT) in margin optimization, evidence is found that price limits significantly impact large contract returns. Several implications arise from these results. SAFEX wheat contract inefficiencies could be attractive to speculators. Wheat margins should be higher nearer maturity. Optimizing margins using EVT could reduce trading costs, increase market attractiveness and liquidity while enhancing price discovery. South Africa should increase wheat production since reducing imports will lower vulnerability to adverse price transmission. JEL Classification: C13, C14, C58, G01, G13, G17 Keywords: Futures market; commodities; volatility; seasonality; information flows, margins / MB2016