This textbook provides a comprehensive and accessible guide to solving heterogeneous agent models in Economics and Finance, building upon representative agent frameworks. Designed for advanced master's students, Ph.D. candidates, and researchers, it systematically introduces the numerical tools and methods required to solve these models, addressing both idiosyncratic and aggregate risk.

The book is structured in two parts, covering both discrete and continuous time frameworks. Part I focuses on discrete time, introducing foundational concepts such as stochastic optimal control theory and numerical dynamic programming. It covers key computational techniques, including value function iteration, the endogenous gridpoint method, and methods for handling inequality constraints. These tools are then extended to heterogeneous agent models, exploring their mechanics, the law of motion of the agents' distribution, stationary equilibria, transition dynamics, and aggregate risk. Notable models, such as Huggett (1993), Aiyagari (1994), and Krusell-Smith (1998), are thoroughly examined and solved with step-by-step numerical algorithms and visualizations.

Part II transitions to continuous time, enabling the incorporation of more sophisticated stochastic processes. Topics include dynamic programming in continuous time, diffusion and jump diffusion processes, and the numerical methods-such as finite upwind difference schemes-needed to solve these models.

With a step-by-step approach, this textbook bridges the gap between representative and heterogeneous agent models, providing clear visualizations, numerical algorithms, and solution techniques. Readers will gain not only the computational skills to implement these models but also the insight to select the appropriate framework for their research objectives.

This book provides the first full-scale comparative historical analysis of the evolution of soybean farming in five South American countries; these nations now dominate the world market for soybeans, the most valuable agricultural product in the world. However, these countries only began producing soybeans on a large scale in the second half of the 20th century, replacing the United States as the leading exporters by the first decade of the new century. This book also examines soybean farming's association with the introduction of modern commercial agricultural production in several of these countries, many of which had previously exported few agricultural products competitively.

In 2026, EUROMOD - the European Union's tax-benefit microsimulation model - marks its 30th anniversary. Established in 1996 as an academic prototype, the model has grown into a central pillar of European social policy analysis. Today, EUROMOD provides a harmonized and transparent framework for assessing the distributional and fiscal effects of tax-benefit policies across EU Member States and partner countries. Its evidence has shaped national debates, informed EU-level policymaking, and contributed to a deeper understanding of income distribution, poverty, labor market incentives, and redistribution.

Over the past three decades, EUROMOD has inspired a vast body of academic research and institutional analysis, producing hundreds of peer-reviewed articles and policy reports. This anniversary volume takes stock of that achievement. It documents the historical evolution of EUROMOD, explains how the model is used in policy processes across Europe, and highlights methodological innovations and future directions in microsimulation.

Bringing together leading scholars and practitioners, the contributions offer a dual perspective: a retrospective account of how EUROMOD became a cornerstone of social policy assessment, and a forward-looking exploration of the model's next 30 years. The volume includes a curated selection of influential EUROMOD-based studies - spanning diverse topics, countries, and periods - reprinted from leading peer-reviewed journals to showcase the breadth and depth of the model's scientific impact.

This book provides policymakers, researchers, and students with a unique resource on the development, application, and future potential of microsimulation in the EU. Documenting the foundations and evolution of a tool now used daily by researchers, statistical offices, and policymakers, this book celebrates EUROMOD's enduring contribution to the science and practice of social policy analysis in Europe and beyond.

This two-volume edited collection explores how the rapid advancement of emerging technologies such as artificial intelligence, blockchain and the platform economy is challenging international tax systems to adapt to a new economic reality. In an economic world characterized by increased capital mobility, complex cross-border flows and smart business models, while practices such as base erosion and profit shifting (BEPS) are simultaneously reducing states' tax revenues and amplifying pressures on governments to rethink the global tax architecture, the book provides a comprehensive and integrated analysis of the impact of the digital transformation on global taxation.

The book draws on research from around the globe to identify current gaps and propose concrete solutions to develop sustainable, equitable and resilient tax frameworks. One of the book's most compelling insights is its critical analysis of traditional paradigms of taxation that were designed for an industrial economy based on tangible assets and physical presence. The book demonstrates that these concepts are outdated in today's context, where economic value is predominantly created through data, intellectual property and platform-based business models. At the same time, the contributions explore the limitations of possible solutions, paying specific attention to their varying effectiveness between developed and emerging economies. This is a vital resource for economists, researchers and tax professionals in understanding and implementing tax systems that are fair, efficient and adaptable to new economic realities.

This book aims to bridge climate risk and public-debt practice. It sets out how to design and execute green and sustainability-linked borrowing; build credible KPIs and targets; verify, report and assure; and deploy disaster or pause clauses where they add value. Moving beyond transactions, it links risk to budget tagging and PFM, and shows how swaps, guarantees and other state-contingent features rebalance sovereign and municipal balance sheets. Cases from advanced and emerging economies demonstrate issuance strategy, investor communication and audit-ready controls that align budgets, bonds and resilience.

Wie Philosophie im Zeichen der Klimakrise betreiben? Wie die Geschichte der Aufklaerung erzaehlen, wenn mit ihr zugleich die Grundlagen fuer das Zeitalter der Verbrennung fossiler Energien gelegt wurden? Und warum entwickelte die Moderne Ideen wie Fortschritt und Freiheit losgeloest von ihren materiellen Bedingungen? Die Beitraege in diesem Band von u. a. Jacob Blumenfeld, Alyssa Battistoni, Dipesh Chakrabarty, Eva Horn, Iwona Janicka, Fredrik Albritton Jonsson, Kohei Saito und Eva von Redecker gehen diesen grundsaetzlichen Fragen sowie alternativen Denkentwuerfen nach, die im Kanon der Philosophie keinen Platz gefunden haben. Eine Neujustierung der Philosophie und ihrer Geschichte im Zeichen der planetaren Krise.

A critical examination of the Federal Reserve-told by the policymakers, economists, and observers who know it best

The Federal Reserve is one of the most powerful institutions in the world-and one of the least understood. Drawing on twenty-one interviews with former governors, reserve bank presidents, staff economists, lawmakers, journalists, scholars, international central bankers, and investors, Fed Reckoning explores how the institution has navigated the defining upheavals of the modern era: the global financial crisis, the pandemic shock, the post-2021 inflation surge, and the banking turmoil of 2023. It traces the modern Federal Reserve from Volcker to Powell, examining its evolving approach to the dual mandate, financial stability, regulation and supervision, and communication.

Just as importantly, these interviews reveal the people behind the institution: their judgments, disagreements, frustrations, and sense of mission. The result is a candid, deeply informed portrait of the Federal Reserve at a moment when its power is immense, its independence is under pressure, and its future path is far from certain-and essential reading for anyone seeking to understand how it makes and defends its decisions.

This book offers a compelling exploration of the modern transformation of traditional Chinese political thought. Through a comparative lens, it examines how ancient concepts, such as the people's principle, rule of law, and freedom, interact with and diverge from their modern counterparts. The author looks into the ideological resources embedded in classical Chinese political philosophy, asking how these ideas can inform contemporary political life and values.
By addressing key questions, such as the differences between ancient and modern understandings of freedom and law, and the role of intellectuals in shaping political discourse, the book provides a rich, critical framework for rethinking the relevance of tradition in modernity. It also reflects on the theoretical misinterpretations that have emerged during this transformation.
This book is ideal for university students seeking to understand the evolution of Chinese political thought, as well as scholars engaged in political theory, philosophy, and intellectual history.

Mathematical finance and computing are parts of nearly all aspects of everyday life. The discipline has underpinned beneficial modern capabilities, financial modelling, predictive analysis and optimization including search algorithms, financial data visualisation, financial computing, numerical analysis for predictions, and quantitative risk management. Mathematics and computer science are constantly evolving and contributing to most areas of science, engineering and finance; therefore, future generations of mathematical scientists should reassess the increasingly cross-disciplinary nature of the mathematical sciences. Mathematical Finance and Financial Computing with Real-World Applications presents current scientific and technological innovations from leading academics, researchers, and experts across the globe in mathematical sciences and computing.

The volume will discuss new technical ideas and features that can be incorporated into day-to-day life for the benefit of society. A diversified spectrum of scientific advancements is discussed, including applications of stochastics differential equation, numerical analysis, financial computation, computation dynamics, nonlinear optimization, machine learning, and artificial intelligence. Readers will explore diverse ideas and innovations in the field of financial computation and its growing connections to various fields of mathematics and statistics.

This book will benefit young and middle level researchers in quantitative finance, financial computing and quantitative risk management. Professors, students, and researchers working in research areas such as mathematical finance, financial modelling, asset pricing, volatility modelling, risk analysis, predictive modelling, portfolio optimization, statistical finance, financial computing, financial engineering, financial data analysis and data science can use this book to improve their results.

In Sustainable Fixed Income, Christoph Klein, together with several leading managers and academics, delivers expert coverage of fixed-income research and credit analysis guided by sustainability objectives.

Part One describes the fixed-income market, beginning with a brief history and then introducing government bonds as its cornerstone. It discusses the assumption that government bonds from leading developed countries can still be considered risk-free.

Part Two covers the measurement of corporate credit risk. The author explains how to build a comprehensive quantitative Credit Rating Model that incorporates ESG key performance indicators (KPIs) for individual issuers. Part Three discusses ESG risk assessments and ratings, as well as the link between ESG and credit risk. It provides examples of how artificial intelligence (AI) can help investors and risk managers detect and monitor risks.

Part Four provides an overview of sustainable finance instruments, such as green bonds, as well as principles and developments in global capital markets. It includes regulators' perspectives on how banks must measure and manage ESG and climate risks and discusses how fixed-income investors can generate impact. Furthermore, this section provides insights into the recommended skills for market participants.

An insightful and comprehensive discussion of a timely subject in credit risk analysis, Sustainable Fixed Income will earn a prominent place in the libraries of portfolio managers, risk professionals, fixed-income securities analysts, investors, financial officers, treasurers and traders everywhere.

Financial markets are inherently nonlinear, noisy, and full of hidden structure. This book provides a clear and practical pathway for mastering machine learning in such an environment, guiding readers from foundational understanding to confident application. Rather than overwhelming the reader with an encyclopedic list of algorithms, it focuses on a carefully selected set of methods that offer the best balance of performance, interpretability, and robustness. By concentrating on these core approaches, the book equips you to understand not only how to use machine learning models, but also why they behave as they do and how to improve them thoughtfully.

Through an accessible and disciplined approach, the text shows how to build solutions that avoid the common traps of financial modeling-overfitting, misapplied validation, and the temptation to chase patterns that vanish upon closer inspection. Readers learn how to design workflows that respect temporal dependencies, handle imbalanced data responsibly, and translate theoretical concepts into models that deliver meaningful and trustworthy results.

This book serves quantitative finance professionals seeking modern tools with statistical rigor, data scientists transitioning into finance who must adapt to domain-specific challenges, and students or researchers who require practical guidance alongside their theoretical training. It also supports practitioners versed in Python or other analytical platforms who want to enhance their capabilities in financial contexts, as well as engineers responsible for deploying machine learning systems in production environments. For readers with an interest in the role of machine learning in finance, it provides a clear and intuitive introduction to advanced techniques without unnecessary complexity.

This book offers a grounded and practical guide for anyone aiming to turn machine learning concepts into reliable, high-value applications in the financial world.

Digital markets and disruptive technologies have radically reshaped investor behavior. As this book explains, social media, algorithmic trading, and gamified platforms amplify fundamental behavioral biases such as overconfidence and loss aversion. These "digital investors," driven by real-time information and herd dynamics, are pushing markets into increasingly unstable territory-beyond the reach of traditional frameworks. Measuring digitally-driven irrationality with outdated metrics is no longer viable. Regulators aim to keep markets open and transparent, yet investors and platforms struggle to navigate new rules designed to protect both markets and consumers. This book explores the critical intersection of human psychology, technology, and financial governance in a world of constant change.

A practical guide to private debt investing in real estate markets worldwide

In Beyond Banks: The Rise of Private Debt in Real Estate Finance, senior finance professional Roxana Mohammadian-Molina delivers an authoritative examination of private credit's expanding role in property development. Drawing on her experience at Barclays, Morgan Stanley, and eight years in real estate private debt, she offers a case study-driven approach spanning multiple market cycles, geographies, and deal structures.

Beyond Banks explores the evolution of real estate private debt, examining new lending models, risk management strategies, and the role of private credit in modern portfolio construction. The book connects investor perspectives with practitioner insights on deal structuring and risk underwriting while analysing market trends, regulations, and private credit opportunities across different jurisdictions worldwide.

Readers will also find:

• Detailed case studies providing practical insights from real-world transactions across various market cycles, geographies, and deal structures
• Analysis of emerging lending models and their implications for both investors seeking fixed-income alternatives and developers seeking funding
• Risk management strategies and underwriting frameworks essential for evaluating and structuring private debt investments in real estate
• Global perspective on regulatory environments and market trends shaping private credit opportunities across different international jurisdictions
• Thought leadership on portfolio construction and how private debt fits within broader investment strategies for institutional investors

Ideal for real estate developers seeking funding, investors exploring fixed-income alternatives, and finance professionals expanding their private credit expertise, Beyond Banks provides the practical knowledge and global perspective needed to navigate this rapidly evolving sector.