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Gesamtkatalog

Catalogue complet

Sargent T: Dynamic Programming

Dynamic Programming

Finite States

Modern Trends In Financial Engineering

Multiscale Financial Data Analytics and Machine Learning offers a systematic and comprehensive study on the multiscale approach to financial data analytics and machine learning. This book covers an array of multiscale methods to discover the properties of various timescales embedded in a financial time series, including noise-assisted empirical mode decomposition methods. Important interpretable multiscale outputs from the estimation are recognized as a new set of features that can be used for machine learning. The feature selection problem for machine learning is examined in this volume.This book offers an applied quantitative approach that combines novel analytical methodologies and practical applications to a wide array of examples with real-world data. It is self-contained and organized in its presentation. The explanations of the methodologies are both accessible and detailed enough to capture the interest of the curious student or researcher. Step-by-step descriptions of the algorithms are provided for straightforward implementation.

Multiscale Financial Data Analytics And Machine Learning

World Scientific Lecture Notes In Economics And Policy

This book attempts to understand the operation and properties of 'market economies'. We do this by carefully examining, refining and in some cases extending the major theorems that Microeconomics has established in response to the Walrasian conjecture. We critically evaluate theorems and results, that assert the existence, uniqueness, stability, optimality and empirical relevance of Walrasian equilibrium states. As a result of our work, we attempt to comment on the wisdom of recommending that socio-economic systems operate as a collection of deregulated competitive markets.

Lectures In General Equilibrium Microeconomics

The book addresses the underlying question of mis-specification in models estimated with spatial data. When spatial econometrics focusses on model estimation techniques, it is most often assumed that mis-specification is restricted to spatial autocorrelation and occasionally heteroskedasticity.

Introduction to Applied Spatial Econometrics

Derivatives: Mathematical Foundations for Finance Students is written for students of finance and actuarial science who want to understand derivatives not just as formulas but as ideas that make sense. The goal is to build the mathematical foundations up step by step - starting from the familiar territory of first-year undergraduate probability and statistics and moving all the way to stochastic calculus and the principles of risk-neutral pricing, which form the heart of modern financial mathematics.This text will enable the reader to:¿ understand models of asset price behaviour and apply stochastic calculus ¿ use stochastic simulations in R to investigate processes and price options ¿ price options with the binomial model ¿ derive solutions to the Black-Scholes equation using risk-neutral pricing ¿ price interest-rate derivatives using Black's model, short-rate models and the Heath-Jarrow-Morton (HJM) framework ¿ tackle quantitative finance exam questions.It incorporates a range of learning features to aid student understanding, including boxed examples, end-of-chapter summaries, selected questions from Society of Actuaries (US) Quantitative Finance examinations and further reading suggestions. The book is also supported by a suite of digital learning resources, including PowerPoint slides, multiple choice questions, instructor manual/advice document for lecturers, and a test bank.Derivatives: Mathematical Foundations for Finance Students will appeal to both undergraduate and postgraduate students who wish to understand the principles of stochastic calculus and option pricing.

Mathematical Foundations for Finance Students

Derivatives

Elements in Econophysics

Classical mechanics provided the conceptual and methodological foundations of neoclassical economics, which has its roots in economic individualism. Since the early twentieth century, statistical mechanics has underpinned a lesser-known approach to economics and finance, one that focuses on aggregates and the interactions between individuals. This has led to the emergence of a new field of research, known as econophysics, which brings to the fore concepts such as emergent properties, power laws, networks, entropy, and multifractality, thereby reshaping economic enquiry.

A Connected History of Two Disciplines

The Rise of Econophysics

Business Guides on the Go

Making Complex Choices Simple

Popular Optimization

A rigorous, cutting-edge overview of the range of methods used to conduct causal inference in the social sciences. This textbook provides a lucid, rigorous, and cutting-edge overview of the methods used to conduct causal inference in the social sciences, covering all the core techniques and latest advances. Offering a detailed survey of the current state of microeconometric theory, Damian Clarke delves deeply into machine learning applications and presents developments in difference-in-difference methods, instrumental variables, multiple hypothesis testing, and other advanced topics. With a diverse range of examples and exercises offering hands-on experience, Applied Microeconometrics equips graduate students and researchers to apply state-of-the art scholarship to actionable problems. <ul><li>Integrates a rich array of machine learning methods into causal modeling frameworks</li><li>Covers recent advances in difference-in-differences and dynamic research designs, formal discussions of challenges related to inference and hypothesis testing, and heterogeneity analysis</li><li>Features a breadth of real-world examples from recent papers</li><li>Includes coding implementation in Python, R, and Stata</li></ul>

Applied Microeconometrics

This open access book is a unique resource in computational mathematical optimization. It conveys the entire spectrum from the basic theory to the most advanced tricks in reformulations and decomposition approaches to solving mixed-integer linear programs. The book has useful and partly previously unpublished facts for students, teachers, and practitioners alike. The content covers algorithmic ideas like column generation, cutting planes, and branch-and-price, reformulation techniques like Dantzig-Wolfe decomposition and Lagrangian relaxation, the very important application domains of vehicle routing and crew scheduling, and has some practical advice when it comes to an implementation. Many notes and even more didactic illustrations and examples bring the theory to life, complemented by almost 140 exercises, including solutions. As a side effect, readers learn ways how to formulate integer programming models for a great variety of combinatorial optimization problems. The material draws from more than 400 references and the four authors' own decades of experience in the field. Several photos taken by the authors bring a personal touch to the writing, among other tiny anecdotal elements that the connoisseur will appreciate. The book is not, and cannot be encyclopedic, but it has the ambition to be the standard text and main reference in the field for the years to come.
Students, researchers, and practitioners aiming to solve large, complex discrete and combinatorial optimization problems—whether in industry, science, or technology—will find this book essential for exploring optimal and near-optimal solutions through decomposition methods and column generation.

Branch-and-Price

Lecture Notes in Operations Research

This book presents the best papers from the 6th International Conference on Mathematical Research for Blockchain Economy (MARBLE) 2025, held in Athens, Greece. While most blockchain conferences and forums are dedicated to business applications, product development or Initial Coin Offering (ICO) launches, this conference focused on the mathematics behind blockchain to bridge the gap between practice and theory.
Blockchain technology has been considered as the most fundamental and revolutionizing invention since the Internet. Every year, thousands of blockchain projects are launched and circulated in the market, and there is a tremendous wealth of blockchain applications, from finance to healthcare, education, media, logistics, and more. However, due to theoretical and technical barriers, most of these applications are impractical for use in a real-world business context. The papers in this book reveal the challenges and limitations, such as scalability, latency, privacy, and security and showcase solutions and developments to overcome them.

6th International Conference MARBLE 2025, Athens, Greece

Mathematical Research for Blockchain Economy

In today's data-driven business world, organizations struggle to extract actionable insights from vast amounts of information. This textbook bridges theory and practice, offering structured approaches to leverage data for enhanced decision-making through machine learning, AI, and optimization modeling-transforming raw data into competitive business intelligence.Decision Making and Analytics: Data-Driven Business Intelligence and Optimization features advanced analytical methodologies paired with real-world implementation studies, creating a progressive learning path from customer behavior analysis through hybrid decision models. By integrating fuzzy logic, neural networks, text mining, and reinforcement learning, it provides a comprehensive toolkit applicable across business scenarios, turning abstract concepts into practical solutions.Serving multiple audiences, this resource bridges the gap between classroom theory and industry practice for students in industrial engineering, business analytics, and management information systems. Practitioners gain applicable methodologies to improve organizational decision-making. At the same time, researchers benefit from cutting-edge approaches across various domains, and policymakers can develop data-informed strategies-addressing the growing demand for professionals who translate data into strategic decisions.The textbook employs open-ended questions that develop analytical reasoning skills without predetermined solutions, better preparing students for real-world complexity. Supporting materials include high-quality figure slides, as well as PowerPoint slides, for qualified adopters, enabling engaging learning environments that effectively communicate complex concepts while building practical, data-driven decision-making skills.

Data-Driven Business Intelligence and Optimization

Decision-Making and Analytics

Routledge Revivals

Planning the Mexican Economy (originally published in 1984), based on original research, looks at how the problems induced by oil led development have been and might be faced in the Mexican economy. It uses econometric modelling to chart the relationship between different sectors of the economy.

Alternative Development Strategies

Planning the Mexican Economy

Dynamic Programming

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