Reflecting the fast pace and ever-evolving nature of the financial industry, the Handbook of High-Frequency Trading and Modeling in Finance details how high-frequency analysis presents new systematic approaches to implementing quantitative activities with high-frequency financial data. Introducing new and established mathematical foundations necessary to analyze realistic market models and scenarios, the handbook begins with a presentation of the dynamics and complexity of futures and derivatives markets as well as a portfolio optimization problem using quantum computers. Subsequently, the handbook addresses estimating complex model parameters using high-frequency data. Finally, the handbook focuses on the links between models used in financial markets and models used in other research areas such as geophysics, fossil records, and earthquake studies. The Handbook of High-Frequency Trading and Modeling in Finance also features: Contributions by well-known experts within the academic, industrial, and regulatory fields A well-structured outline on the various data analysis methodologies used to identify new trading opportunities Newly emerging quantitative tools that address growing concerns relating to high-frequency data such as stochastic volatility and volatility tracking; stochastic jump processes for limit-order books and broader market indicators; and options markets Practical applications using real-world data to help readers better understand the presented material The Handbook of High-Frequency Trading and Modeling in Finance is an excellent reference for professionals in the fields of business, applied statistics, econometrics, and financial engineering. The handbook is also a good supplement for graduate and MBA-level courses on quantitative finance, volatility, and financial econometrics. Ionut Florescu, PhD, is Research Associate Professor in Financial Engineering and Director of the Hanlon Financial Systems Laboratory at Stevens Institute of Technology. His research interests include stochastic volatility, stochastic partial differential equations, Monte Carlo Methods, and numerical methods for stochastic processes. Dr. Florescu is the author of Probability and Stochastic Processes, the coauthor of Handbook of Probability, and the coeditor of Handbook of Modeling High-Frequency Data in Finance, all published by Wiley. Maria C. Mariani, PhD, is Shigeko K. Chan Distinguished Professor in Mathematical Sciences and Chair of the Department of Mathematical Sciences at The University of Texas at El Paso. Her research interests include mathematical finance, applied mathematics, geophysics, nonlinear and stochastic partial differential equations and numerical methods. Dr. Mariani is the coeditor of Handbook of Modeling High-Frequency Data in Finance, also published by Wiley. H. Eugene Stanley, PhD, is William Fairfield Warren Distinguished Professor at Boston University. Stanley is one of the key founders of the new interdisciplinary field of econophysics, and has an ISI Hirsch index H=128 based on more than 1200 papers. In 2004 he was elected to the National Academy of Sciences. Frederi G. Viens, PhD, is Professor of Statistics and Mathematics and Director of the Computational Finance Program at Purdue University. He holds more than two dozen local, regional, and national awards and he travels extensively on a world-wide basis to deliver lectures on his research interests, which range from quantitative finance to climate science and agricultural economics. A Fellow of the Institute of Mathematics Statistics, Dr. Viens is the coeditor of Handbook of Modeling High-Frequency Data in Finance, also published by Wiley.

This book provides an up-to-date series of advanced chapters on applied financial econometric techniques pertaining the various fields of commodities finance, mathematics & stochastics, international macroeconomics and financial econometrics. International Financial Markets: Volume I provides a key repository on the current state of knowledge, the latest debates and recent literature on international financial markets. Against the background of the "financialization of commodities" since the 2008 sub-primes crisis, section one contains recent contributions on commodity and financial markets, pushing the frontiers of applied econometrics techniques. The second section is devoted to exchange rate and current account dynamics in an environment characterized by large global imbalances. Part three examines the latest research in the field of meta-analysis in economics and finance. This book will be useful to students and researchers in applied econometrics; academics and students seeking convenient access to an unfamiliar area. It will also be of great interest established researchers seeking a single repository on the current state of knowledge, current debates and relevant literature.

Variations in the foreign exchange market influence all aspects of the world economy, and understanding these dynamics is one of the great challenges of international economics. This book provides a new, comprehensive, and in-depth examination of the standard theories and latest research in exchange-rate economics. Covering a vast swath of theoretical and empirical work, the book explores established theories of exchange-rate determination using macroeconomic fundamentals, and presents unique microbased approaches that combine the insights of microstructure models with the macroeconomic forces driving currency trading.

Macroeconomic models have long assumed that agents--households, firms, financial institutions, and central banks--all have the same information about the structure of the economy and therefore hold the same expectations and uncertainties regarding foreign currency returns. Microbased models, however, look at how heterogeneous information influences the trading decisions of agents and becomes embedded in exchange rates. Replicating key features of actual currency markets, these microbased models generate a rich array of empirical predictions concerning trading patterns and exchange-rate dynamics that are strongly supported by data. The models also show how changing macroeconomic conditions exert an influence on short-term exchange-rate dynamics via their impact on currency trading.

Designed for graduate courses in international macroeconomics, international finance, and finance, and as a go-to reference for researchers in international economics, "Exchange-Rate Dynamics" guides readers through a range of literature on exchange-rate determination, offering fresh insights for further reading and research.Comprehensive and in-depth examination of the latest research in exchange-rate economics Outlines theoretical and empirical research across the spectrum of modeling approaches Presents new results on the importance of currency trading in exchange-rate determination Provides new perspectives on long-standing puzzles in exchange-rate economics End-of-chapter questions cement key ideas

Stochastic differential equations are differential equations whose solutions are stochastic processes. They exhibit appealing mathematical properties that are useful in modeling uncertainties and noisy phenomena in many disciplines. This book is motivated by applications of stochastic differential equations in target tracking and medical technology and, in particular, their use in methodologies such as filtering, smoothing, parameter estimation, and machine learning. It builds an intuitive hands-on understanding of what stochastic differential equations are all about, but also covers the essentials of Ito calculus, the central theorems in the field, and such approximation schemes as stochastic Runge-Kutta. Greater emphasis is given to solution methods than to analysis of theoretical properties of the equations. The book's practical approach assumes only prior understanding of ordinary differential equations. The numerous worked examples and end-of-chapter exercises include application-driven derivations and computational assignments. MATLAB/Octave source code is available for download, promoting hands-on work with the methods.

It is impossible to understand modern economics without knowledge of the basic tools of gametheory and mechanism design. This book provides a graduate-level introduction to the economic modeling of strategic behavior. The goal is to teach Economics doctoral students the tools of game theory and mechanism design that all economists should know.

High-frequency trading is an algorithm-based computerized trading practice that allows firms to trade stocks in milliseconds. Over the last fifteen years, the use of statistical and econometric methods for analyzing high-frequency financial data has grown exponentially. This growth has been driven by the increasing availability of such data, the technological advancements that make high-frequency trading strategies possible, and the need of practitioners to analyze these data. This comprehensive book introduces readers to these emerging methods and tools of analysis.

Yacine Ait-Sahalia and Jean Jacod cover the mathematical foundations of stochastic processes, describe the primary characteristics of high-frequency financial data, and present the asymptotic concepts that their analysis relies on. Ait-Sahalia and Jacod also deal with estimation of the volatility portion of the model, including methods that are robust to market microstructure noise, and address estimation and testing questions involving the jump part of the model. As they demonstrate, the practical importance and relevance of jumps in financial data are universally recognized, but only recently have econometric methods become available to rigorously analyze jump processes.

Ait-Sahalia and Jacod approach high-frequency econometrics with a distinct focus on the financial side of matters while maintaining technical rigor, which makes this book invaluable to researchers and practitioners alike."

This third edition capitalizes on the success of the previous editions and leverages the important advancements in visualization, data analysis, and sharing capabilities that have emerged in recent years. It serves as an accelerated guide to decision support designs for consultants, service professionals and students. This 'fast track' enables a ramping up of skills in Excel for those who may have never used it to reach a level of mastery that will allow them to integrate Excel with widely available associated applications, make use of intelligent data visualization and analysis techniques, automate activity through basic VBA designs, and develop easy-to-use interfaces for customizing use. The content of this edition has been completely restructured and revised, with updates that correspond with the latest versions of software and references to contemporary add-in development across platforms. It also features best practices in design and analytical consideration, including methodical discussions of problem structuring and evaluation, as well as numerous case examples from practice.

Today, most money is credit money, created by commercial banks. While credit can finance innovation, excessive credit can lead to boom/bust cycles, such as the recent financial crisis. This highlights how the organization of our monetary system is crucial to stability. One way to achieve this is by separating the unit of account from the medium of exchange and in pre-modern Europe, such a separation existed. This new volume examines this idea of monetary separation and this history of monetary arrangements in the North and Baltic Seas region, from the Hanseatic League onwards. This book provides a theoretical analysis of four historical cases in the Baltic and North Seas region, with a view to examining evolution of monetary arrangements from a new monetary economics perspective. Since the objective exhange value of money (its purchasing power), reflects subjective individual valuations of commodities, the author assesses these historical cases by means of exchange rates. Using theories from new monetary economics , the book explores how the units of account and their media of exchange evolved as social conventions, and offers new insight into the separation between the two. Through this exploration, it puts forward that money is a social institution, a clearing device for the settlement of accounts, and so the value of money, or a separate unit of account, ultimately results from the size of its network of users. The History of Money and Monetary Arrangements offers a highly original new insight into monetary arrangments as an evolutionary process. It will be of great interest to an international audience of scholars and students, including those with an interest in economic history, evolutionary economics and new monetary economics.

This book explores the novel uses and potentials of Data Envelopment Analysis (DEA) under big data. These areas are of widespread interest to researchers and practitioners alike. Considering the vast literature on DEA, one could say that DEA has been and continues to be, a widely used technique both in performance and productivity measurement, having covered a plethora of challenges and debates within the modelling framework.

Computable general equilibrium (CGE) models play an important role in supporting public-policy making on such issues as trade, climate change and taxation. This significantly revised volume, keeping pace with the next-generation standard CGE model, is the only undergraduate-level introduction of its kind. The volume utilizes a graphical approach to explain the economic theory underlying a CGE model, and provides results from simple, small-scale CGE models to illustrate the links between theory and model outcomes. Its eleven hands-on exercises introduce modelling techniques that are applied to real-world economic problems. Students learn how to integrate their separate fields of economic study into a comprehensive, general equilibrium perspective as they develop their skills as producers or consumers of CGE-based analysis.

Panel data is a data type increasingly used in research in economics, social sciences, and medicine. Its primary characteristic is that the data variation goes jointly over space (across individuals, firms, countries, etc.) and time (over years, months, etc.). Panel data allow examination of problems that cannot be handled by cross-section data or time-series data. Panel data analysis is a core field in modern econometrics and multivariate statistics, and studies based on such data occupy a growing part of the field in many other disciplines. The book is intended as a text for master and advanced undergraduate courses. It may also be useful for PhD-students writing theses in empirical and applied economics and readers conducting empirical work on their own. The book attempts to take the reader gradually from simple models and methods in scalar (simple vector) notation to more complex models in matrix notation. A distinctive feature is that more attention is given to unbalanced panel data, the measurement error problem, random coefficient approaches, the interface between panel data and aggregation, and the interface between unbalanced panels and truncated and censored data sets. The 12 chapters are intended to be largely self-contained, although there is also natural progression. Most of the chapters contain commented examples based on genuine data, mainly taken from panel data applications to economics. Although the book, inter alia, through its use of examples, is aimed primarily at students of economics and econometrics, it may also be useful for readers in social sciences, psychology, and medicine, provided they have a sufficient background in statistics, notably basic regression analysis and elementary linear algebra.

This book is concerned with recent developments in time series and panel data techniques for the analysis of macroeconomic and financial data. It provides a rigorous, nevertheless user-friendly, account of the time series techniques dealing with univariate and multivariate time series models, as well as panel data models. It is distinct from other time series texts in the sense that it also covers panel data models and attempts at a more coherent integration of time series, multivariate analysis, and panel data models. It builds on the author's extensive research in the areas of time series and panel data analysis and covers a wide variety of topics in one volume. Different parts of the book can be used as teaching material for a variety of courses in econometrics. It can also be used as reference manual. It begins with an overview of basic econometric and statistical techniques, and provides an account of stochastic processes, univariate and multivariate time series, tests for unit roots, cointegration, impulse response analysis, autoregressive conditional heteroskedasticity models, simultaneous equation models, vector autoregressions, causality, forecasting, multivariate volatility models, panel data models, aggregation and global vector autoregressive models (GVAR). The techniques are illustrated using Microfit 5 (Pesaran and Pesaran, 2009, OUP) with applications to real output, inflation, interest rates, exchange rates, and stock prices.

An excellent starting point for graduate-level econometrics, this comprehensive, well-organized and well-written introductory text includes all of the major topic areas of the subject, clearly explained through concepts rather than relying on complex algebra, and carefully pitched at the right level for students who may not already have a strong background in the subject. The text also includes discussion of bootstrap inference in order to aid students in understanding inference based on exact and asymptotic distributions.

David F. Hendry is a seminal figure in modern econometrics. He has pioneered the LSE approach to econometrics, and his influence is wide ranging. This book is a collection of papers dedicated to him and his work. Many internationally renowned econometricians who have collaborated with Hendry or have been influenced by his research have contributed to this volume, which provides a reflection on the recent advances in econometrics and considers the future progress for the methodology of econometrics. Central themes of the book include dynamic modelling and the properties of time series data, model selection and model evaluation, forecasting, policy analysis, exogeneity and causality, and encompassing. The book strikes a balance between econometric theory and empirical work, and demonstrates the influence that Hendry's research has had on the direction of modern econometrics. Contributors include: Karim Abadir, Anindya Banerjee, Gunnar Bardsen, Andreas Beyer, Mike Clements, James Davidson, Juan Dolado, Jurgen Doornik, Robert Engle, Neil Ericsson, Jesus Gonzalo, Clive Granger, David Hendry, Kevin Hoover, Soren Johansen, Katarina Juselius, Steven Kamin, Pauline Kennedy, Maozu Lu, Massimiliano Marcellino, Laura Mayoral, Grayham Mizon, Bent Nielsen, Ragnor Nymoen, Jim Stock, Pravin Trivedi, Paolo Paruolo, Mark Watson, Hal White, and David Zimmer.

Computational Economics: A concise introduction is a comprehensive textbook designed to help students move from the traditional and comparative static analysis of economic models, to a modern and dynamic computational study. The ability to equate an economic problem, to formulate it into a mathematical model and to solve it computationally is becoming a crucial and distinctive competence for most economists. This vital textbook is organized around static and dynamic models, covering both macro and microeconomic topics, exploring the numerical techniques required to solve those models. A key aim of the book is to enable students to develop the ability to modify the models themselves so that, using the MATLAB/Octave codes provided on the book and on the website, students can demonstrate a complete understanding of computational methods. This textbook is innovative, easy to read and highly focused, providing students of economics with the skills needed to understand the essentials of using numerical methods to solve economic problems. It also provides more technical readers with an easy way to cope with economics through modelling and simulation. Later in the book, more elaborate economic models and advanced numerical methods are introduced which will prove valuable to those in more advanced study. This book is ideal for all students of economics, mathematics, computer science and engineering taking classes on Computational or Numerical Economics.

The application of time series techniques in economics has become increasingly important, both for forecasting purposes and in the empirical analysis of time series in general. This book brings together recent research at the frontiers of the subject and analyzes the areas of time series analysis of most importance to applied economics. The author discusses three basic areas of time series analysis: univariate models, multivariate models, and nonlinear models. Particular emphasis is placed on applications of the theory to important areas of applied economics and on the computer software and programs needed to implement the techniques. It is an up-to-date text, extending the basic techniques of analysis to cover the development of methods that can be used to analyze a wide range of economic problems.

An Introductory Econometrics Text Mathematical Statistics for Applied Econometrics covers the basics of statistical inference in support of a subsequent course on classical econometrics. The book shows students how mathematical statistics concepts form the basis of econometric formulations. It also helps them think about statistics as more than a toolbox of techniques. Uses Computer Systems to Simplify Computation The text explores the unifying themes involved in quantifying sample information to make inferences. After developing the necessary probability theory, it presents the concepts of estimation, such as convergence, point estimators, confidence intervals, and hypothesis tests. The text then shifts from a general development of mathematical statistics to focus on applications particularly popular in economics. It delves into matrix analysis, linear models, and nonlinear econometric techniques. Students Understand the Reasons for the Results Avoiding a cookbook approach to econometrics, this textbook develops students' theoretical understanding of statistical tools and econometric applications. It provides them with the foundation for further econometric studies.

Economic forecasting involves choosing simple yet robust models to best approximate highly complex and evolving data-generating processes. This poses unique challenges for researchers in a host of practical forecasting situations, from forecasting budget deficits and assessing financial risk to predicting inflation and stock market returns. Economic Forecasting presents a comprehensive, unified approach to assessing the costs and benefits of different methods currently available to forecasters. This text approaches forecasting problems from the perspective of decision theory and estimation, and demonstrates the profound implications of this approach for how we understand variable selection, estimation, and combination methods for forecasting models, and how we evaluate the resulting forecasts. Both Bayesian and non-Bayesian methods are covered in depth, as are a range of cutting-edge techniques for producing point, interval, and density forecasts. The book features detailed presentations and empirical examples of a range of forecasting methods and shows how to generate forecasts in the presence of large-dimensional sets of predictor variables. The authors pay special attention to how estimation error, model uncertainty, and model instability affect forecasting performance. * Presents a comprehensive and integrated approach to assessing the strengths and weaknesses of different forecasting methods* Approaches forecasting from a decision theoretic and estimation perspective* Covers Bayesian modeling, including methods for generating density forecasts* Discusses model selection methods as well as forecast combinations* Covers a large range of nonlinear prediction models, including regime switching models, threshold autoregressions, and models with time-varying volatility* Features numerous empirical examples* Examines the latest advances in forecast evaluation* Essential for practitioners and students alike

In the memorable words of Ragnar Frisch, econometrics is 'a unification of the theoretical-quantitative and the empirical-quantitative approach to economic problems'. Beginning to take shape in the 1930s and 1940s, econometrics is now recognized as a vital subdiscipline supported by a vast-and still rapidly growing-body of literature. Following the positive reception of The Rise of Econometrics (2013) (978-0-415-61678-2), Routledge now announces a new collection in its Critical Concepts in Economics series. Edited by the author of the field's leading textbook, Panel Data Econometrics brings together in one 'mini library' the best and most influential scholarship. This four-volume set provides an authoritative, one-stop resource to enable users to understand the econometrics of panel data, from both theoretical and applied viewpoints. With a full index and comprehensive introductions to each volume, newly written by the editor, the collection also provides a synoptic view of many current key debates and issues.

For beginning econometrics students or practitioners interested in updates and a refresher. A thorough and beginner-friendly introduction to econometrics. Using Econometrics: A Practical Guide provides students with a practical introduction that combines single-equation linear regression analysis with real-world examples and exercises. This text also avoids complex matrix algebra and calculus, making it an ideal text for beginner econometrics students. New problem sets and added support make Using Econometrics modern and easier to use.

This book presents the econometric analysis of single equation and simultaneous equation models where the jointly dependent variables can be continuous, categorical, or truncated.

Building on the success of Abadir and Magnus' Matrix Algebra in the Econometric Exercises Series, Statistics serves as a bridge between elementary and specialized statistics. Professors Abadir, Heijmans, and Magnus freely use matrix algebra to cover intermediate to advanced material. Each chapter contains a general introduction, followed by a series of connected exercises which build up knowledge systematically. The characteristic feature of the book (and indeed the series) is that all exercises are fully solved. The authors present many new proofs of established results, along with new results, often involving shortcuts that resort to statistical conditioning arguments.

Whether you're comping a vocal track, restoring an old recording, working with dialogue or sound effects for film, or imposing your own vision with mash-ups or remixes, audio editing is a key skill to successful sound production. Digital Audio Editing gives you the techniques, from the simplest corrective editing like cutting, copying, and pasting to more complex creative editing, such as beat mapping and time-stretching. You'll be able to avoid unnatural-sounding pitch correction and understand the potential pitfalls you face when restoring classic tracks. Author Simon Langford invites you to see editing with his wide-angle view, putting this skill into a broad context that will inform your choices even as you more skillfully manipulate sound. Focusing on techniques applicable to any digital audio workstation, it includes break-outs giving specific keystrokes and instruction in Avid's Pro Tools, Apple's Logic Pro, Steinberg's Cubase, and PreSonus's Studio One. The companion websites includes tutorials in all four software packages to help you immediately apply the broad skills from the book.

This second edition retains the positive features of being clearly written, well organized, and incorporating calculus in the text, while adding expanded coverage on game theory, experimental economics, and behavioural economics. It remains more focused and manageable than similar textbooks, and provides a concise yet comprehensive treatment of the core topics of microeconomics, including theories of the consumer and of the firm, market structure, partial and general equilibrium, and market failures caused by public goods, externalities and asymmetric information. The book includes helpful solved problems in all the substantive chapters, as well as over seventy new mathematical exercises and enhanced versions of the ones in the first edition. The authors make use of the book's full color with sharp and helpful graphs and illustrations. This mathematically rigorous textbook is meant for students at the intermediate level who have already had an introductory course in microeconomics, and a calculus course.