The era of globalization has brought about unprecedented social, political, and environmental challenges for policy makers around the world due to the global impact of economic decisions. In view of these challenges, economics, as a discipline, needs to be taught with the goal of broadening the dialogue on social responsibility, and developing a new pluralist culture of decision making which is inclusive to different schools of economic thought. Pluralist Readings in Economics: Key-concepts and policy tools for the 21st century highlights the long-standing debates regarding economic systems, business models, criteria of justice, and economic policies by providing conceptual openings to economic theory in an engaging and accessible way. The author provides broad coverage of relevant topics through the selection of influential economic thinkers and introduces the reader to their ideas, context, and relevant interpretations. While dealing with complex problems, the author goes beyond commonly known concepts by presenting questions on the historical context of globalization. The study of economic concepts in this way leads to asking new questions concerning various issues relevant to economics. The goal of the text is to provide an interdisciplinary perspective to readers in order to equip them with information that is key to address global economic challenges. Thus, this pluralist approach calls for a reflection of the evolution of global social and economic conditions to demonstrate problem solving approaches that align with the goal of addressing these challenges. Pluralist Readings in Economics: Key-concepts and policy tools for the 21st century is suitable to a broad interdisciplinary readership as it will benefit all those who seek to better understand the complex stakes of the capitalist system, in the tensions between regulatory policies, free market equilibria, and participatory openings in governance. This introductory work also prepares the reader for debates and discussion in economic theory aimed at shaping policy transformations towards a more equitable, just and sustainable world.

Interest Rate Modeling for Risk Management presents an economic model which can be used to compare interest rate and perform market risk assessment analyses. The key interest rate model applied in this book is specified under real-world measures, and the result is used as to generate scenarios for interest rates. The book introduces a theoretical framework that allows estimating the market price of interest rate risk. For this, the book starts with a brief explanation of stochastic analysis, and introduces interest rate models such as Heath-Jarrow-Morton, Hull-White and LIBOR models. The real-world model is then introduced in subsequent chapters. Additionally, the book also explains some properties of the real-world model, along with the negative price tendency of the market price for risk and a positive market price of risk (with practical examples). Readers will also find a handy appendix with proofs to complement the numerical methods explained in the book. This book is intended as a primer for practitioners in financial institutions involved in interest rate risk management. It also presents a new perspective for researchers and graduates in econometrics and finance on the study of interest rate models. The second edition features an expanded commentary on real world models as well as additional numerical examples for the benefit of readers.

This book describes the Throughput Model methodology that can enable individuals and organizations to better identify, understand, and use algorithms to solve daily problems. The Throughput Model is a progressive model intended to advance the artificial intelligence (AI) field since it represents symbol manipulation in six algorithmic pathways that are theorized to mimic the essential pillars of human cognition, namely, perception, information, judgment, and decision choice. The six AI algorithmic pathways are (1) Expedient Algorithmic Pathway, (2) Ruling Algorithmic Guide Pathway, (3) Analytical Algorithmic Pathway, (4) Revisionist Algorithmic Pathway, (5) Value Driven Algorithmic Pathway, and (6) Global Perspective Algorithmic Pathway. As AI is increasingly employed for applications where decisions require explanations, the Throughput Model offers business professionals the means to look under the hood of AI and comprehend how those decisions are attained by organizations. Key Features: - Covers general concepts of Artificial intelligence and machine learning - Explains the importance of dominant AI algorithms for business and AI research - Provides information about 6 unique algorithmic pathways in the Throughput Model - Provides information to create a roadmap towards building architectures that combine the strengths of the symbolic approaches for analyzing big data - Explains how to understand the functions of an AI algorithm to solve problems and make good decisions - informs managers who are interested in employing ethical and trustworthiness features in systems. Dominant Algorithms to Evaluate Artificial Intelligence: From the view of Throughput Model is an informative reference for all professionals and scholars who are working on AI projects to solve a range of business and technical problems.