Markov chains provide a powerful framework for modeling the stochastic behavior of economic and financial variables. This book explores the application of hidden Markov processes, which have proven effective in engineering fields like speech recognition, and highlights their growing significance in social science research. By bridging these disciplines, the text aims to enhance understanding and utilization of Markov models in various research contexts, showcasing their versatility and impact on analyzing complex systems.
This book explores the empirical analysis of stock markets using the Cross-Correlation Function (CCF) approach. It delves into the relationships between different stock market indices and examines how they influence one another over time. The author presents a comprehensive methodology for analyzing market dynamics and provides insights into market efficiency, volatility, and interdependencies. By employing empirical data, the work aims to enhance understanding of market behavior and inform investment strategies.
The global financial crisis saw many Eurozone countries bearing excessive public debt. This led the government bond yields of some peripheral countries to rise sharply, resulting in the outbreak of the European sovereign debt crisis. The debt crisis is characterized by its immediate spread from Greece, the country of origin, to its neighbouring countries and the connection between the Eurozone banking sector and the public sector debt. Addressing these interesting features, this book sheds light on the impacts of the crisis on various financial markets in Europe. This book is among the first to conduct a thorough empirical analysis of the European sovereign debt crisis. It analyses, using advanced econometric methodologies, why the crisis escalated so prominently, having significant impacts on a wide range of financial markets, and was not just limited to government bond markets. The book also allows one to understand the consequences and the overall impact of such a debt crisis, enabling investors and policymakers to formulate diversification strategies, and create suitable regulatory frameworks.
The effects of international trade and foreign direct investment (FDI) on developing economies have long been debated. Since the 1980s, countries with open policies, particularly in Asia and parts of Latin America, have generally outperformed those with closed policies, notably in sub-Saharan Africa. As globalization continues to advance, the focus has shifted from whether to engage in the world economy to how to effectively enhance participation and maximize welfare gains. Sub-Saharan African nations must engage in international trade and investment, with policies aimed at boosting international competitiveness deemed essential. Competitiveness in trade is defined as a country's ability to produce and sell goods internationally at lower prices than competitors, while competitiveness in investment refers to attracting significant foreign investment inflows. This analysis adopts a dynamic approach to comparative advantage, recognizing that competitors are also working to improve their capabilities in trade and investment. Thus, the study emphasizes the importance of developing strategies that enhance a country's competitiveness in the global market.
This book provides a comprehensive study of advanced empirical techniques in finance and financial economics, making it ideal for students, academic researchers, and industry professionals. It emphasizes contemporary empirical methods for analyzing financial markets, utilizing actual market data. By focusing on implementation, the book guides readers in rigorously combining finance theory with modeling technology to enhance existing literature. Its primary goal is to equip readers with a variety of tools and techniques for exploring financial market issues from a fresh perspective, distinguishing it from typical econometrics volumes. While traditional econometric methods remain relevant, this book introduces additional modeling topics that facilitate a deeper understanding of finance theory and its practical applications. For instance, modern finance theory, particularly in derivatives analysis, necessitates a sophisticated grasp of stochastic processes. Furthermore, the analysis of actual data requires innovative statistical tools tailored to the unique characteristics of financial data. To address these evolving needs, the book presents diverse modeling approaches with a strong emphasis on their application within the finance sector.
