Analysis of dependence structure between the Rand/U.S Dollar exchange rate and the gold/platinum prices

Copulas functions are a flexible tool for modelling the dependence structure between variables. The joint and marginal distributions of Copulas are not constrained by the assumptions of normality. This study examines the dependence structure between the gold, platinum prices and the ZAR/U.S.D exchange rate using Copulas. The study found that marginal distributions of Copulas follows the ARMA (1, 1)-EGARCH (1, 1) and ARMA(1, 1)-APARCH (1, 1) models under different error terms including the normal, the student-t and the skew student-t error terms. It used the Normal, the Student-t, the Gumbel, the rotated Gumbel, the Clayton, the rotated Clayton, the Plackett, the Joe Clayton and the Normal time varying Copulas to analyse the dependence structure between returns prices of gold, platinum and ZAR/U.S.D exchange rate. The results showed evidence of a positive strong dependence between the returns prices of gold, platinum and returns on the Rand/U.S.D exchange rate for constant and time varying Copulas. The result also showed a co-movement of exchange rates and gold and platinum prices during a rise or declining prices of gold and platinum. The results imply that fluctuations in gold and platinum prices generate Rand/U.S.D exchange rate volatility.StatisticsM. Sc. (Statistics

Ether: Bitcoin's competitor or ally?

Although Bitcoin has long been dominant in the crypto scene, it is certainly not alone. Ether is another cryptocurrency related project that has attracted an intensive attention because of its additional features. This study seeks to test whether these cryptocurrencies differ in terms of their volatile and speculative behaviors, hedge, safe haven and risk diversification properties. Using different econometric techniques, we show that a) Bitcoin and Ether are volatile and relatively more responsive to bad news, but the volatility of Ether is more persistent than that of Bitcoin; b) for both cryptocurrencies, the exuberance and the collapse of bubbles were identified, but Bitcoin appears more speculative than Ether; c) there is negative and significant correlation between Bitcoin/Ether and other assets (S\&P500 stocks, US bonds, oil), which would indicate that digital currencies can hedge against the price movements of these assets; d) there is negative tail independence between Bitcoin/Ether and other financial assets, implying that these cryptocurrencies exhibit the function of a weak safe haven; and e) The inclusion of Bitcoin/ Ether in a portfolio improve its efficiency in terms of higher reward-to-risk ratios. But investors who hold diversified portfolios made of stocks or bonds and Ether may face losses over bearish regime. In such situation, stock and bond investors may take a short position on Bitcoin

Studies on African equity markets and global shocks : co-movement, contagion, and diversification

A Doctoral thesis submitted in fulfilment of the requirements for the award of Doctor of Philosophy degree in the field of Finance The Graduate school of Business Administration, University of the Witwatersrand, October 2016The global financial system has experienced turmoil in the past three decades, at the least. Although the shocks originate abroad, they possess some rippling effects on African economies. The essence of market integration and cross-border listings of stocks has fueled the need for African markets to be well integrated with the global economy. Despite this need, available empirical literature exploring the integration of African markets regionally, and with the rest of the world appear unclear. Moreover, the possibility of global shocks transmitting to Africa via its emerging equity markets remains underexplored. At the same time, such knowledge is critical for not only understanding the functioning of equity markets in particular, but also important for regulating the financial system in general. This thesis addresses these gaps inherent in extant literature and proffer empirical and theoretical solutions by exploring the nexus between African stock markets and global shocks. The emphasis is on contagion, co-movement, and diversification. The thesis is organized into four empirical essays, each deeply touching on specific theme (s) that form the core of the problems or research questions under investigation while employing advanced econometric techniques that underpin the modeling of asset returns. The first essay examines the capacity of African equity markets to act as ‗hubs‘ for portfolio investors during tranquil and turbulent conditions of global equity and commodity markets. The findings posit that African stock markets provide decorrelation from commodity and global equity markets during extreme market conditions. To the extent that the results reveal the strength of African stocks in cushioning international portfolio investors in a mean-variance stand-point during market crashes, the essay helps to decay doubts in the minds of investors on the perceived lack of capacity of the continent‘s stocks to yield higher expected risk-return trade-offs during global market sell-offs. The implication of the study is that given the recent history of commodities and global stocks, fund managers around the world seeking viable alternatives to compensate for losses from commodity shocks through uncorrelated markets may consider the equity markets in Africa, albeit on account of volatility persistence, present and past market conditions, markets stability, as well as size and liquidity issues. The second essay examines regional and global co-movement of African stock markets using the three-dimensional continuous Morlet wavelet transform methodology. The essay establishes evidence of stronger co-movements broadly narrowed to short-run fluctuations. The co-movements are time-varying and commonly non-homogeneous – with phase difference arrow vectors implying lead-lag African Equity Markets and Global Shocks 2016 © Gideon Boako Page iii relationships. The presence of lead-lag effects and stronger co-movements at short-run fluctuations may induce arbitrage and diversification opportunities to both local and international investors with long-term investment horizons. The findings also reveal that some African equity markets are, to a degree, segmented from volatilities of the dollar and euro exchange rates. The third essay sheds light on whether African equity markets decoupled from, and / or converged with regional and global markets from 2003 to 2014, and analyzes the implications of that for shocks spillovers. Although there is no evidence of African markets convergence either regionally or globally, shock propagation exists in a time-varying setting. Regional markets in Africa are not just ‗shock absorbers‘ but also ‗shock transmitters‘. In the last essay, the dependence structure and (extreme) downside developed equity markets and currency price risk spillover effects to African stock markets using value-at-risk (VaR) and conditional value-at-risk (CoVaR) based on stochastic copulas is modeled. The study finds evidence of non-homogenous weak negative dependence between stocks and the USD and EUR exchange rates. Except for Egypt, there is evidence of positive significant dependencies between all African markets and their developed counterparts. Although, evidence of both uni-directional and bidirectional causality, as well as upper and lower tail dependencies are found across the stocks and currency markets, only some minuscule evidence of downside spillover effects was recorded, albeit episodic. It is observed that propagation of shocks from the GFC had a second round effect in African stock markets. Thus, the impact of the GFC to African economies was not through the credit crunches and liquidity freezes in Phase I of the crisis, but rather through the global recession that followed into the second phase. The findings are consistent with the view that global shocks propagation to developing markets may stagger during crisis and intensify post-crisis. A practical implication from the results is that given the relatively scarce resources and levels of technological know-how available to African governments, efforts to wean the continent‟s equity markets from adverse effects of global market crashes should be geared towards plans and programmes to mitigate the shocks not at the early stages but latter stages, where the effects to Africa could be prominently felt. Three key arguments are deduced from all the essays. First, although financial market underdevelopment seems prima-facie, to help countries isolate themselves against immediate contagion, it also reduces the ability of the real economy to cushion the impact of the crisis. African Equity Markets and Global Shocks 2016 © Gideon Boako Page iv Therefore, the argument of the thesis is that despite the common fear that a highly integrated and developed market may present fertile grounds for shock spillover, Africa must continue to pursue programmes aimed at enhancing inter and intra-regional integration. However, the degree and extent of both inter- and intra-regional integration ought to be pegged at certain optimal levels in order to reap benefits from scale economies. Such endeavours at integration will not only help in risk diversification but also help smooth the impact of shocks. The second argument is that, the proposition of the ―decoupling theory‖ i.e. returns of African equity markets and global stocks are not jointly normal during crisis periods may not be entirely tenable, empirically. Thirdly, the thesis argues that the “shift-contagion” theory may not reflect the reality for Africa, particularly during initial stages of crisis. Instead, the thesis suggests an extension and argues for a “delayed-shift contagion” theory. Keywords: Decoupling, shift-contagion, spillover effects, CoVaR, exchange rates, commodities. JEL Classification: C40, C58, F31, F36, G10, G11, G15,GR201

Estimating Dependences and Risk between Gold Prices and S&P500: New Evidences from ARCH,GARCH, Copula and ES-VaR models

This thesis examines the correlations and linkages between the stock and commodity in order to quantify the risk present for investors in financial market (stock and commodity) using the Value at Risk measure. The risk assessed in this thesis is losses on investments in stock (S&P500) and commodity (gold prices). The structure of this thesis is based on three empirical chapters. We emphasise the focus by acknowledging the risk factor which is the non-stop fluctuation in the prices of commodity and stock prices. The thesis starts by measuring volatility, then dependence which is the correlation and lastly measure the expected shortfalls and Value at risk (VaR). The research focuses on mitigating the risk using VaR measures and assessing the use of the volatility measures such as ARCH and GARCH and basic VaR calculations, we also measured the correlation using the Copula method. Since, the measures of volatility methods have limitations that they can measure single security at a time, the second empirical chapter measures the interdependence of stock and commodity (S&P500 and Gold Price Index) by investigating the risk transmission involved in investing in any of them and whether the ups and downs in the prices of one effect the prices of the other using the Time Varying copula method. Lastly, the third empirical chapter which is the last chapter, investigates the expected shortfalls and Value at Risk (VaR) between the S&P500 and Gold prices Index using the ES-VaR method proposed by Patton, Ziegel and Chen (2018). Volatility is considered to be the most popular and traditional measure of risk. For which we have used ARCH and GARCH model in our first empirical chapter. However, the problem with volatility is that it does not take into account the direction of an investments’ movement: volatility of stocks is that they suddenly jump higher and investors are not distressed with gains. When we talk about investors for them the risk is about the odds of losing money, after my research and findings VaR is based on the common-sense fact. Hence, investors care about the odds of big losses, VaR answers the question, what is my worst-case scenario? Or simply how much I could lose in a really bad month? The results of the thesis demonstrated that measuring volatility (ARCH GARCH) alone was not sufficient in measuring the risk involved in an investment therefore methodologies such as correlation and VAR demonstrates better results. In terms of measuring the interdependence, the Time Varying Copula is used since the dynamic structure of the de- pendence between the data can be modelled by allowing either the copula function or the dependence parameter to be time varying. Lastly, hybrid model further demonstrates the average return on a risky asset for which Expected Shortfall (ES) along with some quantile dependence and VaR (Value at risk) is utilised. Basel III Accord which is applied in coming years till 2019 focuses more on ES unlike VaR, hence there is little existing work on modelling ES. The thesis focused on the results from the model of Patton, Ziegel and Chen (2018) which is based on the statistical decision theory. Patton, Ziegel and Chen (2018), overcame the problem of elicitability for ES by using ES and VaR jointly and propose the new dynamic model of risk measure. This research adds to the contribution of knowledge that measuring risk by using volatility is not enough for measuring risk, interdependence helps in measuring the dependency of one variable over the other and estimations and inference methods proposed by Patton, Ziegel and Chen (2018) using simulations proposed in ES-VaR model further concludes that ARCH and GARCH or other rolling window models are not enough for determining the risk forecasts. The results suggest, in first empirical chapter we see volatility between Gold prices and S&P500. The second empirical chapter results suggest conditional dependence of the two indexes is strongly time varying. The correlation between the stock is high before 2008. The results further displayed slight stronger bivariate upper tail, which signifies that the conditional dependence of the indexes is influence by positive shocks. The last empirical chapter findings proposed that measuring forecasts using ES-Var model proposed by Patton, Ziegel and Chen (2018) does outer perform forecasts based on univariate GARCH model. Investors want to 10 protect themselves from high losses and ES-VaR model discussed in last chapter would certainly help them to manage their funds properly

Commodity exposure in the eurozone: How EU energy security is conditioned by the Euro

The European Union is immersed in a process of energy transition focused on reducing the weight of fossil fuels. The current context is also characterized by the increasing attention paid to energy security, conditioned by the volatility of the prices for energy raw materials, among other factors. This work analyzes the raw material price exposure of electricity producers in the Eurozone. The results indicate that the listing of raw materials in U.S. dollars is the primary cause of business exposure, with an impact greater than the price of the raw material itself. A geographic analysis also indicates that there are important differences in the level of exposure among companies in different countries, which can make it difficult to reach a consensus in the European UnionS

New insights on hidden Markov models for time series data analysis

The goal of this thesis is to develop novel methods for the analysis of financial data by using hidden Markov models based approaches. The analysis focuses on univariate and multivariate financial time series, modeling interrelationships between financial returns throughout different statistical methods, such as graphical models, quantile and expectile regressions. The dissertation is divided into three chapters, each of them examining different classes of assets returns for a comprehensive risk analysis. The methodologies we propose are illustrated using real-world data and simulation studies

statistical methods on risk management of extreme events

The goal of the dissertation is the investigation of financial risk analysis methodologies, using the schemes for extreme value modeling as well as techniques from copula modeling. Extreme value theory is concerned with probabilistic and statistical questions re- lated to unusual behavior or rare events. The subject has a rich mathematical theory and also a long tradition of applications in a variety of areas. We are interested in its application in risk management, with a focus on estimating and forcasting the Value-at-Risk of financial time series data. Extremal data are inherently scarce, thus making inference challenging. In order to obtain good estimates for risk measures, we develop a two-stage approach: (1) fitting the GARCH-type models at the first stage to describe the volatility clustering and other stylized facts of financial time series; (2) using the extreme value theory based models to fit to the tails of the residuals. Additionally, the performance measures provide information in terms of the comparison of the two-stage semi-parametric approach with the parametric methodologies, through robust backtesting. Copula is a particular branch of probability theory, with which, given sufficient data, we can separate the marginal behavior of individual risks and their dependence structure from a multivariate random variable. Linear correlation is widely used to model dependence but has limitations as a measure of association and thus we opt to use copulas to analyze the dependence structure and build models for our different problems arising in risk management. For this part of the dissertation, we take a look at different copula families, highlight for some when they are most appropriate to use for a particular application, discuss some of their drawbacks as diverse scenarios occur in different risk management models, and explore the possibility of developing the copula modeling to reflect the complicated dependence structure of portfolios

Optimal Asset Allocation Under Linear Loss Aversion

Growing experimental evidence suggests that loss aversion plays an important role in asset allocation decisions. We study the asset allocation of a linear loss-averse (LA) investor and compare the optimal LA portfolio to the more traditional optimal mean-variance (MV) and conditional value-at-risk (CVaR) portfolios. First we derive conditions under which the LA problem is equivalent to the MV and CVaR problems. Then we analytically solve the twoasset problem, where one asset is risk-free, assuming binomial or normal asset returns. In addition we run simulation experiments to study LA investment under more realistic assumptions. In particular, we investigate the impact of different dependence structures, which can be of symmetric (Gaussian copula) or asymmetric (Clayton copula) type. Finally, using 13 EU and US assets, we implement the trading strategy of an LA investor assuming assets are reallocated on a monthly basis and find that LA portfolios clearly outperform MV and CVaR portfolios.LOss aversion, portfolio optimization, MV and CVaR portfolios, copula, investment strategy

Empirical Analysis of Natural Gas Markets

Recent developments in the natural gas industry warrant new analysis of related issues. Environmental, social, and governance (ESG) investments have accelerated the shift away from coal as the dominant source of electricity. Its low environmental impact, reduced volume, and broad availability make liquefied natural gas (LNG) a popular alternative, during this time of transition between traditional fuels and newer options. In the United States, the shale gas revolution has made natural gas a game changer. In this book, we focus on empirical analyses of the natural gas market and its growing relevance worldwide

The GARCH-EVT-Copula model and simulation in scenario-based asset allocation

Financial market integration, in particular, portfolio allocations from advanced economies to South African markets, continues to strengthen volatility linkages and quicken volatility transmissions between participating markets. Largely as a result, South African portfolios are net recipients of returns and volatility shocks emanating from major world markets. In light of these, and other, sources of risk, this dissertation proposes a methodology to improve risk management systems in funds by building a contemporary asset allocation framework that offers practitioners an opportunity to explicitly model combinations of hypothesised global risks and the effects on their investments. The framework models portfolio return variables and their key risk driver variables separately and then joins them to model their combined dependence structure. The separate modelling of univariate and multivariate (MV) components admits the benefit of capturing the data generating processes with improved accuracy. Univariate variables were modelled using ARMA-GARCH-family structures paired with a variety of skewed and leptokurtic conditional distributions. Model residuals were fit using the Peaks-over-Threshold method from Extreme Value Theory for the tails and a non-parametric, kernel density for the interior, forming a completed semi-parametric distribution (SPD) for each variable. Asset and risk factor returns were then combined and their dependence structure jointly modelled with a MV Student t copula. Finally, the SPD margins and Student t copula were used to construct a MV meta t distribution. Monte Carlo simulations were generated from the fitted MV meta t distribution on which an out-of-sample test was conducted. The 2014-to-2015 horizon served to proxy as an out-of-sample, forward-looking scenario for a set of key risk factors against which a hypothetical, diversified portfolio was optimised. Traditional mean-variance and contemporary mean-CVaR optimisation techniques were used and their results compared. As an addendum, performance over the in-sample 2008 financial crisis was reported. The final Objective (7) addressed management and conservation strategies for the NMBM. The NMBM wetland database that was produced during this research is currently being used by the Municipality and will be added to the latest National Wetland Map. From the database, and tools developed in this research, approximately 90 wetlands have been identified as being highly vulnerable due to anthropogenic and environmental factors (Chapter 6) and should be earmarked as key conservation priority areas. Based on field experience and data collected, this study has also made conservation and rehabilitation recommendations for eight locations. Recommendations are also provided for six more wetland systems (or regions) that should be prioritised for further research, as these systems lack fundamental information on where the threat of anthropogenic activities affecting them is greatest. This study has made a significant contribution to understanding the underlying geomorphological processes in depressions, seeps and wetland flats. The desktop mapping component of this study illustrated the dominance of wetlands in the wetter parts of the Municipality. Perched wetland systems were identified in the field, on shallow bedrock, calcrete or clay. The prevalence of these perches in depressions, seeps and wetland flats also highlighted the importance of rainfall in driving wetland formation, by allowing water to pool on these perches, in the NMBM. These perches are likely to be a key factor in the high number of small, ephemeral wetlands that were observed in the study area, compared to other semi-arid regions. Therefore, this research highlights the value of multi-faceted and multi-scalar wetland research and how similar approaches should be used in future research methods has been highlighted. The approach used, along with the tools/methods developed in this study have facilitated the establishment of priority areas for conservation and management within the NMBM. Furthermore, the research approach has revealed emergent wetland properties that are only apparent when looking at different spatial scales. This research has highlighted the complex biological and geomorphological interactions between wetlands that operate over various spatial and temporal scales. As such, wetland management should occur across a wetland complex, rather than individual sites, to account for these multi-scalar influences