The purpose of this study was to explore and gain insight into the current purpose of contracting and, in the main, the future of contracting in emerging markets. The study aimed to explore the nature of contracting in emerging markets in order to understand what the future of contracting will be in emerging markets. The study was a qualitative study and a sample of ten participants was interviewed. Findings of the study indicated that the emerging market environment is risky due to unfamiliar local nuances; and local laws are preferred over international law. Technology and innovation are not a strong focus in emerging markets but relationship frameworks allow for some degree of flexibility and innovation. Relationships and their importance were the biggest finding of this research prompting an exploration of the Confucian concept of guanxi highlighting relational networks within social settings. The research further identified that contract professionals need to firstly be both competent and globally literate. Relationships and links between skills, knowledge and the operating environment are intertwined in determining the future of contracting. The research concluded by making recommendations to Chief Executive Officers of multinationals, lawyers, contract professionals and consultants in emerging market firms in light of the findings of this research. The research highlights the legal and both internal and external contextual considerations of contracting and also suggests variables for further research that are crucial for a deeper understanding of contracting in emerging markets. / Dissertation (MBA)--University of Pretoria, 2014. / zkgibs2015 / Gordon Institute of Business Science (GIBS) / MBA / Unrestricted

Liquidity is an important market characteristic for participants in every financial market. One of the three components of liquidity is market depth. Prior literature lacks a comprehensive analysis of depth in U.S. futures markets due to past limitations on the availability of data. However, recent innovations in data collection and dissemination provide new opportunities to investigate the depth dimension of liquidity. In this dissertation, the Chicago Mercantile Exchange (CME) Group proprietary database on depth is employed to study the dynamics of depth in the U.S. futures markets. This database allows for the analysis of depth along the entire limit order book rather than just at the first level. The first essay examines the characteristics of depth within the context of the five-deep limit order book. Results show that a large amount of depth is present in the book beyond the best level. Furthermore, the findings show that the characteristics of five-deep depth between day and night trading vary and that depth is unequal across levels within the limit order book. The second essay examines the link between the five-deep market depth and the bid-ask spread. The results suggest an inverse relation between the spread and the depth after adjusting for control factors. The third essay explores transitory volatility in relation to depth in the limit order book. Evidence supports the relation between an increase in volatility and a subsequent decrease in market depth. Overall, the results of this dissertation are consistent with limit order traders actively managing depth along the limit order book in electronic U.S. futures markets.

In this doctoral dissertation, I study markets in which the private information held by various agents may be reflected in prices, and as a result may be leaked to other market participants. Specifically, I study how the market microstructure interacts with the price discovery process, the market efficiency, agents' market power, and social welfare. This dissertation consists of two chapters. The first chapter studies the implications of leakage of information through prices for the efficient operation of markets with heterogeneous agents. Focusing on uniform-price double auctions, I first characterize how the presence of heterogeneity (e.g., in terms of agents’ trading costs, information precision, or risk attitudes) can shape the information content of prices and hence the market’s informational efficiency. I find that price informativeness decreases with the extent of heterogeneity in the market. I then establish that such reductions in price informativeness can in turn manifest themselves as an informational externality: in the presence of heterogeneity, agents do not internalize the impact of their trading decisions on the information revealed to others via prices. This chapter also shows that the welfare implications of this heterogeneity-induced informational externality depends on the intricate details of the market. The results thus indicate that accounting for the possibility of information leakage should be an important consideration in designing markets with asymmetric information. I conclude by exploring the welfare implications of market segmentation in the presence of heterogeneous agents and information leakage. The second chapter studies how information asymmetry shapes price impact in the presence of strategic interactions, i.e., agents' actions being strategic substitutes or strategic complements. Focusing on demand-function competition with strategic interactions, I first establish the existence and characterize the equilibrium. The characterization indicates that strategic interactions have a direct impact on the weights agents put on their private information: as strategic interaction increases, agents put less weight on their private information. I also characterize the relation between price impact, strategic interaction, and information asymmetry. While price impact decreases as the level of information asymmetry decreases, the relation between price impact and strategic interaction is more subtle, and it depends on whether agents submit upward- or downward-sloping demand schedules. When agents submit downward-sloping demand curves, price impact decreases as the extent of strategic substitutability increases, and increases as the extent of strategic complementarity increases. Furthermore, strong interaction may mitigate or exacerbate the effect of information asymmetry on agents' price impact, depending on the slope of the inverse supply curve. The results in this chapter thus emphasize the importance of accounting for strategic interactions between market participants, when assessing their price impact in markets with asymmetric information.

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Since Engle and Granger formulated the concept of cointegration in 1987, the literature has extensively examined the unbiasedness of the commodity futures prices using the cointegration-based technique. Despite intense attention, many of the previous studies suffer from the contradicting empirical results. That is, the cointegration test and the stationarity test on the differential contradict each other. In marked contrast, my dissertation develops the no-arbitrage cost-of-carry model in the NYMEX light sweet crude oil futures market and tests stationarity of the spot-futures differential. It is demonstrated that the primary cause of the "cointegration paradox" is the model misspecifications resulting in omitted variable bias.

This master’s thesis predicts the development and assesses the potential of cryptocurrencies in the areas of investment, trade and technology based on their technical, economic and legal analysis. Although the thesis deals with cryptocurrencies in general, the key focus is placed on their most prominent representative (Bitcoin) in trying to predict the effects on the future of financial markets from a wide, multidisciplinary perspective.

Ever since Granger first proposed the idea of quantitatively testing the causal relationship between data streams, the endeavor of accurately inferring the causality in data and using that information to predict the future has not stopped. Artificial Intelligence (AI), by utilizing the massive amounts of data, helps to solve complex problems, whether they include the diagnosis and detection of disease through medical imaging, email spam detection, or self-driving vehicles. Perhaps, this thesis will be trivial in ten years from now. AI has pushed humankind to reach the next technological level in technology. Nowadays, among most machine leaning inquiries, statistical relationships are determined using correlation measures. By feeding data into machine learning algorithms, computers update the algorithm’s parameters iteratively by extracting and mapping features to learning targets until the correlation increases to a significant level to cease the training process. However, with the increasing developments of powerful AI, there is really a shortage of exploring causality in data. It is almost self-evident that ”correlation is not causality." Sometimes, the strong correlation established between variables through machine learning can be absurd and meaningless. Providing insight into causality information through data, which most of the machine learning methods fall short to do, is of paramount importance. The subsequent chapters detail the four endeavors of studying causality in financial markets, earthquakes, animal/human brain signals, the predictivity of data sets. In Chapter 2, we further developed the concept of causality networks into a higher-order causality network. We applied these to financial data and tested their validity and ability to capture the system’s causal relationship. In next Chapter 3, We examined another type of time series-earthquakes. Violent seismic activities decimate people's lives and destroy entire cities and areas. This begs us to understand how earthquakes work and help us make reliably and evacuation-actionable predictions. The causal relationships of seismic activities in different areas are studied and established. Biological data, specifically brain signals, are time-series data and their causal pattern are explored and studied. Different human and mice brain signals are analyzed and clustered in Chapter 4 using their unique causal pattern to understand different brain cell activity. Finally, we realized that the causal pattern in the time series can be used to compress data. A causal compression ratio is invented and used as the data stream’s predictivity index. We describe this in Chapter 5.

The internationalization process of firms has essentially been in two contexts, one focusing on those from the developed, and the other on those from the developing economies (Buckley et al.2008). According to (Panond, 2007), internationalization of Emerging Market Multinational Corporations (EMMNCs) has appeared in two waves, the first wave, which emerged in the late 1970s and early 1980s viewed the competitive advantages of EMMNCs as being derived from their ability in reducing costs through scale economies, often substituting machinery with human labour and replacing imported inputs with cheaper local ones, or improving performance through knowledge of operating in less developed markets.The objective of this research has been to understand the variables that drive the success of Mergers and Acquisitions as a mode of entry in Emerging Markets. The research looks at the application of these variables my multinational corporations from both emerging markets and those from developed markets; the aim is to ascertain if these variables are applied differently depending on the type of economy a multinational originates from.Given the saturation of developed markets multinationals have embarked on growth strategies into emerging markets where these markets are perceived as untapped, however most have failed to realise shareholder value as a result of the dynamics and challenges that these economies bring.Fukao et al. 2005 suggests that market share is one of the most useful means used in assessing the structure of the market and a particularly desirable characteristic of a target firm. This is usually couched in terms of having a ―good market position‖ in the relevant market. The specific target criterion is of special consideration in sectors which may show a high degree of stability of market structure (as compared to those which are characterized by technology intensity, low entry barriers and powerful competition, showing high volatility of market shares). As a result, it is expected that the market share variable will bear a positive coefficient in explaining the likelihood of foreign acquisition.The research proved successful that the application of the variables that determine success of an acquisition and merger between multinationals was similar and what drove this success was mainly based on experience in doing mergers and acquisitions. These led to further insights for current and future work on the topic. / Dissertation (MBA)--University of Pretoria, 2012. / Gordon Institute of Business Science (GIBS) / unrestricted

This study describes a sustainable empowerment process used to mobilise, capacitate and sustainably empower communities.An approach to unlock the potential of the high number of unemployed youth within the emerging markets was investigated. These unemployed youth do not have the correct skills, experience and opportunities to become productive citizens of a country. This research looked at methods used to enable the youth to contribute sustainably to the formal economy as a key to empowering the community.The success factors for community empowerment and the contributions made by stakeholders were explored.The research was based on exploratory research of a South African company, Next S and their operations within local communities. Next S was used because of their innovative and dynamic operations and long history with community projects. / Dissertation (MBA)--University of Pretoria, 2012. / Gordon Institute of Business Science (GIBS) / unrestricted

In light of the global mining industry’s record profits in 2011, this inquiry explored the institutional drivers of mining multinational’s subsidiaries overall performance. Using a lens of institutional theory, this inquiry explored why the subsidiaries of emerging mining multinationals have outperformed the subsidiaries of developed mining multinationals in emerging markets.The inquiry used Mann-Whitney U hypothesis testing to compare the financial performance of 46 emerging mining subsidiaries and 39 developed mining subsidiaries. The inquiry ran eight multiple regression models to test subsidiary performance variables against institutional variables obtained from the 2011/2012 Fraser Institute annual survey of mining companies.The findings support and add to the institutional and international business literature. Emerging multinational enterprises and their subsidiaries possess dynamic institutional capabilities which allows them to better manage institutional uncertainty than developed multinational enterprises and their subsidiaries in emerging markets. An institutional development model has been developed to assist managers of multinational enterprises reduce their institutional uncertainty in emerging markets. / Dissertation (MBA)--University of Pretoria, 2012. / Gordon Institute of Business Science (GIBS) / unrestricted