Advances in Quantitative Methods for Economics and Business

Bringing together a distinguished group of contributors, this volume in honor of Jos Garca Prez provides a comprehensive overview of the latest advances in quantitative methods for business and economics, including distribution theory, econometrics, behavioral finance, financial networks and economic applications, as well as parallels exploring Jos Garca Prez's research interests. Contemporary challenges in this field include evaluating the robustness of structural econometric analyses under collinearity, identifying the connections between long-term memory and financial performance, and treating multicollinearity in the Nelson-Siegel model. To tackle these problems, this book offers a wealth of innovative approaches, methodologies, and theoretical frameworks. For example, it presents new probability distributions, explores the application of partial least structural equation modeling in economics, discusses the theoretical-practical approach to portfolio management in sustainable finance and Environmental, Social and Governance, and reviews the application and usefulness of state-of-the-art machine learning and artificial intelligence in applied finance. The book serves as a valuable resource for researchers and practitioners in econometrics, finance, and economics, providing a comprehensive yet accessible resource for further exploration and study. In honoring Jos Garca Prez, it not only pays tribute to a distinguished scholar but will also act as a catalyst for continued exploration and advancement in the dynamic and evolving landscape of quantitative methods for economics and business.