Advances in Quantitative Methods for Economics and Business

Bringing together a distinguished group of contributors, this volume in honor of José García Pérez 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 José García Pérez'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 José García Pérez, 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.

Modeling Income Distributions using Two-Sided densities. - The Valuation Method Based On Two Cumulative Distribution Functions With Different Beta Distribution Families. - The efficiency and effectiveness of health systems in response of the COVID-19 pandemic: Good Governance and Economic Freedom effects. - On the Robustness of Structural Econometrics and Collinearity. - The metric number and non-essential approximate multicollinearity. - Multicollinearity mitigation and unbiased estimations: an application of Restricted Least Squares. - A new-generation statistical data analysis technique: Partial Least Structural Equation Modeling (PLS-SEM). Application in Economics, Econometrics and Finance. - Exploring Misconceptions Related To Sampling Distribution, Confidence Intervals, And Hypothesis Testing: A Perspective From Econometrics. - Sustainable Finance and ESG Investing: A Theoretical-Practical Approach from Portfolio Management. - Portfolio Selection: An approach from Random Matrix Theory. - Analysis Of Machine Learning And Artificial Intelligence In Finance: Growth And New Trends. - Mutual fund performace and the impact of regulatory constraints. - Clustering, long memory and stocks performance. - Improved estimation of implied volatility with stacking-blending ensemble model. - Long Memory and Financial Markets: from econometrics to econophysics. - Statistical Arbitrage- an approach from econophysics. - Temporal fluctuation scaling and Temporal Theil Scalingin financial time series. - A New Form of Financial Contagion: Covid-19 And Stock Market Responses. - Causality and correlation in the Maritime s circular economy a correlation and causal analysis using a panel of EU countries. - A retrospective prediction model for births in the province of almeria (18th and 19th centuries). - A novel methodology for the measurement of social exclusion: An example in the Region of Murcia, Spain. - Capital structure in the hospital sector in eastern Spain: Balearic Islands, Valencian Community and Region of Murcia. - Nelson-Siegel model and multicollinearity. - Macrofinancial Magnitudes And Patient Satisfaction With The Healthcare System: Some Dynamic Panel Data Evidence. - Digital Goodwill Valuation.