Examining long-run relationships of the BRICS stock market indices to identify opportunities for implementation of statistical arbitrage strategies

>Magister Scientiae - MScPurpose:This research investigates the existence of long-term equilibrium relationships among the stock market indices of Brazil, Russia, India, China and South Africa (BRICS). It further investigates cointegrated stock pairs for possible implementation of statistical arbitrage trading techniques.Design:We utilize standard multivariate time series analysis procedures to inspect unit roots to assess stationarity of the series. Thereafter, cointegration is tested by the Johansen and Juselius (1990) procedure and the variables are interpreted by a Vector Error Correction Model (VECM). Statistical arbitrage is investigated through the pairs trading technique.Findings:The five stock indices are found to be cointegrated. Analysis shows that the cointegration rank among the variables is significantly influenced by structural breaks. Two pairs of stock variables are also found to be cointegrated. This guaranteed the mean reversion property necessary for the successful execution of the pairs trading technique. Determining the optimal spread threshold also proved to be highly significant with respect to the success of this trading technique.Value:This research seeks to expand on the literature covering long-run co-movements of the volatile emerging market indices. Based on the cointegration relation shared by the BRICS, the research also seeks to encourage risk taking when investing. We achieve this by showing the potential rewards that can be realized through employing appropriate statistical arbitrage trading techniques in these markets

The effect of gold price volatility on stock market returns in South Africa

The South African stock market has become a major player in the African Securities Exchanges Association through its performance. Gold is one of the commodities that are traded at Johannesburg Stock Exchange, hence gold price fluctuations are the crucial factor that JSE needs to keep its eye on. The demand for gold in South Africa is continuously rising because gold has full security, less credit risk and is a highly liquid instrument. Based on the given background, the study examines the effect of gold price volatility on stock market returns in South Africa, employing the Generalised Autoregressive Conditional Heteroskedasticity (GARCH) (1.1) model. The study used monthly data covering the period from 2005 to 2017. The Storage model and discounted cash flows model which are the theories that connect gold price and stock market were specified. The research findings are supported by previous studies. The gold price volatility was found to have a negative effect on stock market returns, and the proxy of stock market returns is the All Share Index. The study will help to provide an understanding of how gold price volatility affects the stock market that will help policymakers to come up with policies that are relevant to volatility of gold price towards stock market

Sharp and Practical Performance Bounds for MCMC and Multiple Testing

With the greater adoption of statistical and machine learning methods across science and industry, a greater awareness of the need to align statistical theory ever more closely with the demands of applications is developing. One recurring theme within this process is the re-examination of basic questions and core assumptions through the lens of modern mathematical statistics. This thesis targets two such basic questions in two different contexts: posterior simulation using Markov chain Monte Carlo (MCMC), on the one hand; and multiple hypothesis testing, on the other. For MCMC, we analyze convergence in terms of the expectations of a limited number of query functions, rather than the entire posterior. We show both theoretically and via simulations that the resultant theory predicts the required chain length more sharply than global convergence criteria. Furthermore, we provide match- ing lower bounds that show our bounds are essentially optimal in their dependence on chain parameters and target accuracy. For multiple testing, we provide the first general framework for establishing the optimal tradeoff between false positives (measured by the False Discovery Rate, or FDR) and false negatives (measured by the False Non-discovery rate, or FNR). We begin by proving some of the first non-asymptotic results available on this topic – initially in the context of Gaussian-like test statistics. We then go on to develop the more general framework. The latter applies to test statistics with essentially arbitrary analytic forms and dependence, recovers previous results as special cases, and yields numerically simulable lower bounds that can be evaluated in almost any model of interest

Einheitswurzeltests in Panel- und Zeitreihenmodellen : neue Testverfahren und ökonomische Anwendungen

In this dissertation new test statistics for the (panel) unit root hypothesis are presented. Besides a novel approach to testing the unit root hypothesis in univariate time series, the major part of this thesis is dedicated to unit root testing in cross sectionally dependent panels with potentially time varying innovation variances. The wild bootstrap is presented as an effective means to obtain robust test procedures with good power and size properties.In der vorliegenden Dissertation werden neue Teststatistiken zur Überprüfung der (Panel-) Einheitswurzelhypothese vorgestellt. Neben einem neuen Ansatz zum Testen der Einheitswurzelhypothese in univariaten Zeitreihenmodellen ist der Großteil der Arbeit dem Testen der Einheitswurzelhypothese in Paneldatensätzen mit Querschnittsabhängigkeit und potentiell zeitvariablen Innovationsvarianzen gewidmet. Der externe Bootstrap wird als geeignete Methode vorgestellt, um Testprozeduren mit korrekter Größe und hoher Güte zu erhalten

Learning And Decision Making In Groups

Many important real-world decision-making problems involve group interactions among individuals with purely informational interactions. Such situations arise for example in jury deliberations, expert committees, medical diagnoses, etc. We model the purely informational interactions of group members, where they receive private information and act based on that information while also observing other people\u27s beliefs or actions. In the first part of the thesis, we address the computations that a rational (Bayesian) decision-maker should undertake to realize her optimal actions, maximizing her expected utility given all available information at every decision epoch. We use an approach called iterated eliminations of infeasible signals (IEIS) to model the thinking process as well as the calculations of a Bayesian agent in a group decision scenario. Accordingly, as the Bayesian agent attempts to infer the true state of the world from her sequence of observations, she recursively refines her belief about the signals that other players could have observed and beliefs that they would have hold given the assumption that other players are also rational. We show that IEIS algorithm runs in exponential time; however, when the group structure is a partially ordered set the Bayesian calculations simplify and polynomial-time computation of the Bayesian recommendations is possible. We also analyze the computational complexity of the Bayesian belief formation in groups and show that it is NP-hard. We investigate the factors underlying this computational complexity and show how belief calculations simplify in special network structures or cases with strong inherent symmetries. We finally give insights about the statistical efficiency (optimality) of the beliefs and its relations to computational efficiency. In the second part, we propose the no-recall model of inference for heuristic decision-making that is rooted in the Bayes rule but avoids the complexities of rational inference in group interactions. Accordingly to this model, the group members behave rationally at the initiation of their interactions with each other; however, in the ensuing decision epochs, they rely on heuristics that replicate their experiences from the first stage and can be justified as optimal responses to simplified versions of their complex environments. We study the implications of the information structure, together with the properties of the probability distributions, which determine the structure of the so-called ``Bayesian heuristics\u27\u27 that the agents follow in this model. We also analyze the group decision outcomes in two classes of linear action updates and log-linear belief updates and show that many inefficiencies arise in group decisions as a result of repeated interactions between individuals, leading to overconfident beliefs as well as choice-shifts toward extreme actions. Nevertheless, balanced regular structures demonstrate a measure of efficiency in terms of aggregating the initial information of individuals. Finally, we extend this model to a case where agents are exposed to a stream of private data in addition to observing each other\u27s actions and analyze properties of learning and convergence under the no-recall framework

AN EMPIRICAL ANALYSIS OF THE DETERMINANTS OF NIGERIA’S INWARD FOREIGN DIRECT INVESTMENT (FDI) FLOWS: A COINTEGRATION ANALYSIS

Despite a myriad of studies related to inward foreign direct investment (FDI) determinants, studies on how such determinants may differ in developing versus developed countries have produced mixed results from which it is difficult to discern a conventional wisdom. Moreover, only relatively few studies have specifically investigated inward FDI determinants in Nigeria (Adelegan, 2009; Ekpo, 1997; Ajakaiye, 2010; Ajayi, 2006; Anyanwu, 1998; Olatunji, 2011; Ariyo, 2009; Okpara,et al., 2012), leaving a glaring gap on the key factors influencing inward FDI in Nigeria. Aiming to address this gap, the present PhD thesis intends to investigate the determinants of inward FDI in Nigeria. To address this primary aim, the specific research objectives are: (i) To critically review past literature, both theoretical and empirical, on the key determinant factors affecting Nigeria’s inward FDI; (ii) To collect relevant data, formulate an adequate model specification and choose the most suitable econometric technique to undertake the empirical analysis using a state-of-the-art cointegration technique (the ARLD bounds testing approach to cointegration); (iii)To interpret and discuss the results, identifying the main findings, and draw out key policy implications. The study uses annual data from 1970 to 2014 and employs the Autoregressive Distributed Lag (ARDL) bounds testing approach to cointegration, a testing procedure for level relationshipsdeveloped by Pesaran and Shin (1999) and Pesaran et al. (2001). The major advantage of the ARDL approach to cointegration compared to other methods employed in previous studies is that it can be applied even if the regressors have different orders of integration, I(0) or I(1). This feature provides flexibility and also helps to avoid a potential “pre-test bias”, i.e., the specification of a long-run model on the basis of I(1) variables only (Pesaran et al., 2001). In addition, and being based on a single equation, the ARDL methodology performs better in small samples compared to alternative multivariate cointegration procedures, for example the Johansen ML method (Romilly et al., 2001). A comprehensive theory-based model is developed accounting for many variables, such as the interest rate, external debt, oil rents, the Gross Domestic Product (GDP) growth rate, trade and exchange rate volatility. The analysis of FDI determinants in the Nigerian economy yielded reliable, robust and economically meaningful results thereby offering an insight into the driving factors of inward FDI.The empirical results indicate that the interest rate, external debt, oil rents, and the GDP growth rate have a statistically significant long-run effect on FDI, while trade and exchange rate volatility are found to be statistically insignificant. With the exception of the GDP growth rate, which presents a negative estimated coefficient, the signs of the statistically significant variables are consistent with theory. From a policy point of view, regarding the GDP growth rate, there should be concerted efforts to boost the performance of the non-oil sector in Nigeria through more investments in the agricultural and industrial sectors which will make the growth of the economy spread across other sectors and, in turn, encourage inward FDI in such areas. The findings also indicate that trade is statistically insignificant. This can be attributed to the fact that FDI flowing to Nigeria is mostly resource-oriented due to the Nigerian government being more focused on policies that attract FDI to the oil sector and neglected others such as agriculture and manufacturing. Finally, the findings suggest that exchange rate volatility has a negative, yet statistically insignificant impact on FDI. This result may be explained by the fact that Nigeria’s inward FDI is so oil-dependent that exchange rate volatility, albeit likely to deter investment, appears to have an insignificant effect statistically. The study makes both theoretical and methodological contributions to knowledge by providing vital information on FDI determinants in Nigeria thus guiding Nigerian leaders in government in decision making as well as other researchers interested in the study of FDI in Nigeria. Several policy implications flow from the findings. Countries such as Nigeria, endowed with natural resources, should pursue policies targeted at full deregulation (privatisation) of their natural resource sector to better utilise the abundance of their natural resources and to attract additional FDI. Nigeria should also pursue better debt management practices. When debts are acquired, they should be targeted towards future consumption and longer term investments. Most importantly, as an import-dependent economy, the Nigerian government should also formulate export-driven and appropriate fiscal policies that will stabilise and balance Nigeria’s trade relationship with other world economies. The Nigerian government should create the necessary environment that will regulate macroeconomic and specifically monetary policy (interest rate) which is essential for the attraction of FDI inflows into the economy. Finally, Nigeria should ensure that the quality of exportable commodities is improved to enhance international competitiveness

Characteristics features, economical aspects and environmental impacts of gen-4 nuclear power for developing countries

The growing demand of energy has delicate the requirement of alternative sources of energies other than fossil fuels. Though renewable energy resources like solar, biomass, hydro and geothermal energy appear as environment friendly, replenishing sources of energy, a comprehensive solution appears far-fetched as far as large scale production and wide-spread dissemination is concerned when long term cost factors are taken into consideration. In this paper, discussions on the advanced fourth generation nuclear power on the basis of environmental contamination, energy security, cost of fossil fuels and electricity generation and have philosophy to the prospects of nuclear power as the ultimate future energy option for the developing countries are done. This study proposes that gen-4 nuclear appears to be a long term environment favorable panacea to the much discoursed problem of energy crisis by maintaining energy security and long term cost concern in developing countries as well as in the whole world. Keywords: Gen-4 nuclear, reactor, kinetics, neutron, delayed neutron, transient