The South African white maize market is considered to be significantly more volatile than any other agricultural product traded on the South African Futures Exchange (SAFEX). This accentuates the need to effectively manage price risk, by means of hedging, to ensure a more profitable and sustainable maize production sector (Geyser, 2013:39; Jordaan, Grové, Jooste, A. & Jooste, Z.G., 2007:320). However, hedging at lower price levels might result in significant variation margins or costly buy–outs in order to fulfil the contract obligations. This challenge is addressed in this study by making use of technical analysis, focusing on the development of a practical and applicable composite technical indicator with the purpose of improving the timing of price risk management decisions identified by individual technical indicators. This may ultimately assist a producer in achieving a higher average hedge level compared to popular individual technical indicators. The process of constructing a composite indicator was commenced by examining the prevailing tendency of the market. By making use of the Directional Movement Index (DMI), as identified in the literature study, the market was found to continually shift between trending prices (prices moving either upwards or downwards) and prices trading sideways. Consequently, implementing only a leading (statistically more suitable for trading markets) or lagging (statistically more suitable for trending markets) technical indicator may generate false sell signals, as demonstrated by the application of these technical indicators in the white maize market. This substantiated the motivation for compiling a composite indicator that takes both leading and lagging indicators into account to more accurately identify hedging opportunities. The composite indicator made use of the Relative Strength Index (RSI) and Stochastic oscillator as leading indicators, and the Exponential Moving Average (EMA) and Moving Average Convergence Divergence (MACD) as lagging indicators. The results validated the applicability of such a composite indicator, as the composite indicator outperformed the individual technical indicators in the white maize market. The composite indicator achieved the highest average hedge level, the lowest average sell signals generated over the entire period, as well as the highest average hedge level as a percentage of the maximum price over the entire period. Hence, the composite indicator recognised hedging opportunities more accurately compared to individual technical indicators, which ultimately led to higher achieved hedging levels. / MCom. (Risk management), North-West University, Potchefstroom Campus, 2014

The South African white maize market is considered to be significantly more volatile than any other agricultural product traded on the South African Futures Exchange (SAFEX). This accentuates the need to effectively manage price risk, by means of hedging, to ensure a more profitable and sustainable maize production sector (Geyser, 2013:39; Jordaan, Grové, Jooste, A. & Jooste, Z.G., 2007:320). However, hedging at lower price levels might result in significant variation margins or costly buy–outs in order to fulfil the contract obligations. This challenge is addressed in this study by making use of technical analysis, focusing on the development of a practical and applicable composite technical indicator with the purpose of improving the timing of price risk management decisions identified by individual technical indicators. This may ultimately assist a producer in achieving a higher average hedge level compared to popular individual technical indicators. The process of constructing a composite indicator was commenced by examining the prevailing tendency of the market. By making use of the Directional Movement Index (DMI), as identified in the literature study, the market was found to continually shift between trending prices (prices moving either upwards or downwards) and prices trading sideways. Consequently, implementing only a leading (statistically more suitable for trading markets) or lagging (statistically more suitable for trending markets) technical indicator may generate false sell signals, as demonstrated by the application of these technical indicators in the white maize market. This substantiated the motivation for compiling a composite indicator that takes both leading and lagging indicators into account to more accurately identify hedging opportunities. The composite indicator made use of the Relative Strength Index (RSI) and Stochastic oscillator as leading indicators, and the Exponential Moving Average (EMA) and Moving Average Convergence Divergence (MACD) as lagging indicators. The results validated the applicability of such a composite indicator, as the composite indicator outperformed the individual technical indicators in the white maize market. The composite indicator achieved the highest average hedge level, the lowest average sell signals generated over the entire period, as well as the highest average hedge level as a percentage of the maximum price over the entire period. Hence, the composite indicator recognised hedging opportunities more accurately compared to individual technical indicators, which ultimately led to higher achieved hedging levels. / MCom. (Risk management), North-West University, Potchefstroom Campus, 2014

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Land ist eine kritische Ressource für nachhaltige Entwicklung, doch ihre relative Knappheit erfordert Abwägungen, die für eine Gestaltung von nachhaltiger und gerechter Politik identifiziert werden müssen. Diese ist empirisch herausfordernd, da Landressourcen in verschiedenen abgelegenen lokalen Bedingungen genutzt werden und über voneinander abhängigen globalen Märkten gehandelt werden. Diese Dissertation trägt mit drei empirischen Studien zu dieser Identifizierungsbemühung bei. Das erste Kapitel hinterfragt das Potenzial von Preisanreizen zur Eindämmung der Entwaldung für Ölpalmplantagen in Indonesien. Die Ergebnisse deuten darauf hin, dass machbare marktbasierte Eingriffe in der vorgelagerten Palmöl-Lieferkette die nicht regulierte Entwaldung effektiv und gerecht reduzieren könnten, die ansonsten dem globalen Bedarf folgen würde. Das zweite Kapitel untersucht die Ausbreitungsmechanismen, durch die Schocks auf globalen Landressourcenmärkten indirekt zu Landnutzungsänderungen führen. Die Ergebnisse bestätigen einen globalen Verdrängungsmechanismus und etablieren einen kausalen Zusammenhang zwischen den Renewable Fuel Standards (RFS) in den Vereinigten Staaten und der Ausweitung bedeutender landwirtschaftlicher treibender Kräfte der Entwaldung in pan-tropischen Gebieten. Das dritte Kapitel erforscht die Auswirkungen der RFS auf internationale Unterernährung. Die Ergebnisse zeigen, dass der disruptive Effekt der Nachfrage-Schocks durch die RFS dank ihrer Vorhersehbarkeit abgemildert wird. Dennoch werden Bedenken bezüglich der Ernährungssicherheit in Ländern erhoben, in denen die Lebensmittelversorgung von Importen abhängt, insbesondere im Falle unerwarteter Schocks auf den globalen Märkten für Landressourcen. / Land is a critical resource for sustainable development, but its relative scarcity implies trade-offs that need to be identified to design sustainable and fair policy. This task is challenging empirically, because land resources are used in a variety of remote local conditions, and they are traded through interdependent global markets. This thesis contributes three empirical studies to this identification effort. The first chapter questions the potential of price incentives to mitigate deforestation for oil palm plantations in Indonesia. The results indicate that feasible market interventions upstream the palm oil supply chain could effectively and equitably mitigate unregulated deforestation otherwise left to follow global demand. The second chapter tests the propagation mechanisms through which shocks on global markets for land resources indirectly cause land use change. The results corroborate a global scale displacement mechanism specifically, and they establish a causal link between the Renewable Fuel Standards (RFS) in the United States and the expansion of major agricultural drivers of deforestation in pan-tropical areas. The third chapter explores the impact of the RFS on international undernourishment. The results indicate that the disruptive effect of the demand shocks by the RFS is mitigated by their predictability. Yet, this raises concerns about food security in countries where calorific supply depends on imports, in the case of unexpected shocks on global markets for land resources.