Stock Market Modeling: A System Adaptation Approach

Ph.DDOCTOR OF PHILOSOPH

IDENTIFICATION AND ANALYSIS OF STOCK MARKET DYNAMICS

Ph.DDOCTOR OF PHILOSOPH

Commodity price volatility, stock market performance and economic growth: evidence from BRICS countries

Abstracts in English, Afrikaans and ZuluThe study investigated the nexus between commodity price volatility, stock market performance, and economic growth in the emerging economies of Brazil, Russia, India, China, and South Africa (the BRICS) predicated on two hypotheses. First, the study hypothesised that in modern integrated financial systems, commodity price volatility predisposes stock market performance to be non-linearly related to economic growth. The second hypothesis was that financial crises are an inescapable feature of modern financial systems. The study used daily data on stock indices and selected commodity prices as well as monthly data on national output proxies and stock indices. The study analysed data for non-linearities, fractality, and entropy behaviour using the spectral causality approach, univariate GARCH, EGARCH, FIGARCH, DCC-GARCH, and Markov Regime Switching (MRS) – GARCH. The four main findings were: first, spectral causality tests signalled dynamic non-linearities in the relationship between the three commodity futures prices and the BRICS stock indices. Second, the predominantly non-linear relationship between commodity prices and stock prices was reflected in the nexus between the national output proxies and the indices of the five main commodity classes. Third, spectral causality analysis revealed that the causal structures between commodity prices and national output proxies were non-linear and dynamic. Fourth, the Nyblom parameter stability tests revealed evidence of structural breaks in the data that was analysed. The DCC-GARCH model uncovered strong evidence of contagion, spillovers, and interdependence. The study added to the body of knowledge in three ways. First, micro and macro levels of commodity price changes were linked with corresponding stock market performance indicator changes. Second, unlike earlier studies on the commodity price – stock market performance – economic growth nexus, the study employed spectral causality analysis, single - regime GARCH analysis, Dynamic Conditional Correlation (DCC) – GARCH and a two-step Markov – Regime – Switching – GARCH as a unified analytical approach. Third, spectral causality graphs depicting relationships between stock indices and national output proxies revealed benign business cycle effects, thus, contributing to broadening the scope of business cycle theoryBusiness ManagementPhD. (Management Studies

Quantitative Methods for Economics and Finance

This book is a collection of papers for the Special Issue “Quantitative Methods for Economics and Finance” of the journal Mathematics. This Special Issue reflects on the latest developments in different fields of economics and finance where mathematics plays a significant role. The book gathers 19 papers on topics such as volatility clusters and volatility dynamic, forecasting, stocks, indexes, cryptocurrencies and commodities, trade agreements, the relationship between volume and price, trading strategies, efficiency, regression, utility models, fraud prediction, or intertemporal choice

Three Risky Decades: A Time for Econophysics?

Our Special Issue we publish at a turning point, which we have not dealt with since World War II. The interconnected long-term global shocks such as the coronavirus pandemic, the war in Ukraine, and catastrophic climate change have imposed significant humanitary, socio-economic, political, and environmental restrictions on the globalization process and all aspects of economic and social life including the existence of individual people. The planet is trapped—the current situation seems to be the prelude to an apocalypse whose long-term effects we will have for decades. Therefore, it urgently requires a concept of the planet's survival to be built—only on this basis can the conditions for its development be created. The Special Issue gives evidence of the state of econophysics before the current situation. Therefore, it can provide excellent econophysics or an inter-and cross-disciplinary starting point of a rational approach to a new era

Application of Machine Learning to Financial Time Series Analysis

This multidisciplinary thesis investigates the application of machine learning to financial time series analysis. The research is motivated by the following thesis question: ‘Can one improve upon the state of the art in financial time series analysis through the application of machine learning?’ The work is split according to the following time series trichotomy: 1) characterization — determine the fundamental properties of the time series; 2) modelling — find a description that accurately captures features of the long-term behaviour of the system; and 3) forecasting — accurately predict the short-term evolution of the system

Green Technologies for Production Processes

This book focuses on original research works about Green Technologies for Production Processes, including discrete production processes and process production processes, from various aspects that tackle product, process, and system issues in production. The aim is to report the state-of-the-art on relevant research topics and highlight the barriers, challenges, and opportunities we are facing. This book includes 22 research papers and involves energy-saving and waste reduction in production processes, design and manufacturing of green products, low carbon manufacturing and remanufacturing, management and policy for sustainable production, technologies of mitigating CO2 emissions, and other green technologies