This textbook concisely covers math knowledge and tools useful for business and economics studies, including matrix analysis, basic math concepts, general optimization, dynamic optimization, and ordinary differential equations. Basic math tools, particularly optimization tools, are essential for students in a business school, especially for students in economics, accounting, finance, management, and marketing. It is a standard practice nowadays that a graduate program in a business school requires a short and intense course in math just before or immediately after the students enter the program. Math in Economics aims to be the main textbook for such a crash course.The 1st edition was published by People's University Publisher, China. This new edition contains an added chapter on Probability Theory along with changes and improvements throughout.

The major methodological task for modern economists has been to establish the testability of models. Too often, however, methodological assumptions can make a model virtually impossible to test even under ideal conditions, yet few theorists have examined the requirements and problems of assuring testability in economics. In The Methodology of Economic Model Building, first published in 1989, Lawrence Boland presents the results of a research project that spanned more than twenty years. He examines how economists have applied the philosophy of Karl Popper, relating methodological debates about falsifiability to wider discussions about the truth status of models in natural and social sciences. He concludes that model building in economics reflects more the methodological prescriptions of the economist Paul Samuelson than Popper's 'falsificationism'. This title will prove invaluable to both students and researchers, and represents a substantial contribution to current debates about the scientific status of economics.

The design of trading algorithms requires sophisticated mathematical models backed up by reliable data. In this textbook, the authors develop models for algorithmic trading in contexts such as executing large orders, market making, targeting VWAP and other schedules, trading pairs or collection of assets, and executing in dark pools. These models are grounded on how the exchanges work, whether the algorithm is trading with better informed traders (adverse selection), and the type of information available to market participants at both ultra-high and low frequency. Algorithmic and High-Frequency Trading is the first book that combines sophisticated mathematical modelling, empirical facts and financial economics, taking the reader from basic ideas to cutting-edge research and practice. If you need to understand how modern electronic markets operate, what information provides a trading edge, and how other market participants may affect the profitability of the algorithms, then this is the book for you.

The book provides an extensive discussion of asymptotic theory of M-estimators in the context of dynamic nonlinear models. The class of M-estimators contains least mean distance estimators (including maximum likelihood estimators) and generalized method of moments estimators. In addition to establishing the asymptotic properties of such estimators, the book provides a detailed discussion of the statistical and probabilistic tools necessary for such an analysis. The book also gives a careful treatment of estimators of asymptotic variance covariance matrices for dependent processes.

Change of Time and Change of Measure provides a comprehensive account of two topics that are of particular significance in both theoretical and applied stochastics: random change of time and change of probability law.Random change of time is key to understanding the nature of various stochastic processes, and gives rise to interesting mathematical results and insights of importance for the modeling and interpretation of empirically observed dynamic processes. Change of probability law is a technique for solving central questions in mathematical finance, and also has a considerable role in insurance mathematics, large deviation theory, and other fields.The book comprehensively collects and integrates results from a number of scattered sources in the literature and discusses the importance of the results relative to the existing literature, particularly with regard to mathematical finance.In this Second Edition a Chapter 13 entitled 'A Wider View' has been added. This outlines some of the developments that have taken place in the area of Change of Time and Change of Measure since the publication of the First Edition. Most of these developments have their root in the study of the Statistical Theory of Turbulence rather than in Financial Mathematics and Econometrics, and they form part of the new research area termed 'Ambit Stochastics'.

Bringing together the proceedings of the 1979 and 1980 annual conferences of the Association of University Teachers of Economics the papers in this volume discuss: the effect of social security on private saving; an analysis of aggregate consumer behaviour; the philosophy and objectives of econometrics and other topics in macroeconomic and econometric analysis.

Today, public conversations are increasingly driven by numbers. Although charts, infographics, and diagrams can make us wiser, they can also deceive-intentionally or unintentionally. To be informed citizens, we must all be able to decode and use the visual information that politicians, journalists and even our employers present to us each day. How Charts Lie examines contemporary examples ranging from election result infographics to global GDP maps and box office record charts, demystifying an essential new literacy for our data-driven world. * With a new afterword on the reporting of the Covid-19 statistics.

This book provides a comprehensive and concrete illustration of time series analysis focusing on the state-space model, which has recently attracted increasing attention in a broad range of fields. The major feature of the book lies in its consistent Bayesian treatment regarding whole combinations of batch and sequential solutions for linear Gaussian and general state-space models: MCMC and Kalman/particle filter. The reader is given insight on flexible modeling in modern time series analysis. The main topics of the book deal with the state-space model, covering extensively, from introductory and exploratory methods to the latest advanced topics such as real-time structural change detection. Additionally, a practical exercise using R/Stan based on real data promotes understanding and enhances the reader's analytical capability.

Environmental risk directly affects the financial stability of banks since they bear the financial consequences of the loss of liquidity of the entities to which they lend and of the financial penalties imposed resulting from the failure to comply with regulations and for actions taken that are harmful to the natural environment. This book explores the impact of environmental risk on the banking sector and analyzes strategies to mitigate this risk with a special emphasis on the role of modelling. It argues that environmental risk modelling allows banks to estimate the patterns and consequences of environmental risk on their operations, and to take measures within the context of asset and liability management to minimize the likelihood of losses. An important role here is played by the environmental risk modelling methodology as well as the software and mathematical and econometric models used. It examines banks' responses to macroprudential risk, particularly from the point of view of their adaptation strategies; the mechanisms of its spread; risk management and modelling; and sustainable business models. It introduces the basic concepts, definitions, and regulations concerning this type of risk, within the context of its influence on the banking industry. The book is primarily based on a quantitative and qualitative approach and proposes the delivery of a new methodology of environmental risk management and modelling in the banking sector. As such, it will appeal to researchers, scholars, and students of environmental economics, finance and banking, sociology, law, and political sciences.

This book is an introduction to financial valuation and financial data analyses using econometric methods. It is intended for advanced finance undergraduates and graduates. Most chapters in the book would contain one or more finance application examples where finance concepts, and sometimes theory, are taught.This book is a modest attempt to bring together several important domains in financial valuation theory, in econometrics modelling, and in the empirical analyses of financial data. These domains are highly intertwined and should be properly understood in order to correctly and effectively harness the power of data and statistical or econometrics methods for investment and financial decision-making.The contribution in this book, and at the same time, its novelty, is in employing materials in basic econometrics, particularly linear regression analyses, and weaving into it threads of foundational finance theory, concepts, ideas, and models. It provides a clear pedagogical approach to allow very effective learning by a finance student who wants to be well equipped in both theory and ability to research the data.This is a handy book for finance professionals doing research to easily access the key techniques in data analyses using regression methods. Students learn all 3 skills at once - finance, econometrics, and data analyses. It provides for very solid and useful learning for advanced undergraduate and graduate students who wish to work in financial analyses, risk analyses, and financial research areas.

This new book will be welcomed by econometricians and students of econometrics everywhere. Introducing discrete time modelling techniques and bridging the gap between economics and econometric literature, this ambitious book is sure to be an invaluable resource for all those to whom the terms unit roots, cointegration and error correction forms, chaos theory and random walks are recognisable if not yet fully understood.

This book covers diverse themes, including institutions and efficiency, choice and values, law and economics, development and policy, and social and economic measurement. Written in honour of the distinguished economist Satish K. Jain, this compilation of essays should appeal not only to students and researchers of economic theory but also to those interested in the design and evaluation of institutions and policy.

"Advances in Econometrics and Quantitative Economics" is a comprehensive guide to the statistical methods used in econometrics and quantitative economics. Bringing together contributions from those acknowledged to be amongst the world's leading econometricians and statisticians this volume covers topics such as:

* Semiparametric and non-parametric interference.
* Multivariate analysis.
* Diagnostic tests.
* Time series behavior of commodity prices.
* Applications of Edgeworth expansions and quantitative methods in development economics.

The book is dedicated to Professor C. R. Rao, whose unique contribution to the subject has influenced econometricians for many years.

-Up-to-date with cutting edge topics -Suitable for professional quants and as library reference for students of finance and financial mathematics

Factor Analysis and Dimension Reduction in R provides coverage, with worked examples, of a large number of dimension reduction procedures along with model performance metrics to compare them. Factor analysis in the form of principal components analysis (PCA) or principal factor analysis (PFA) is familiar to most social scientists. However, what is less familiar is understanding that factor analysis is a subset of the more general statistical family of dimension reduction methods. The social scientist's toolkit for factor analysis problems can be expanded to include the range of solutions this book presents. In addition to covering FA and PCA with orthogonal and oblique rotation, this book's coverage includes higher-order factor models, bifactor models, models based on binary and ordinal data, models based on mixed data, generalized low-rank models, cluster analysis with GLRM, models involving supplemental variables or observations, Bayesian factor analysis, regularized factor analysis, testing for unidimensionality, and prediction with factor scores. The second half of the book deals with other procedures for dimension reduction. These include coverage of kernel PCA, factor analysis with multidimensional scaling, locally linear embedding models, Laplacian eigenmaps, diffusion maps, force directed methods, t-distributed stochastic neighbor embedding, independent component analysis (ICA), dimensionality reduction via regression (DRR), non-negative matrix factorization (NNMF), Isomap, Autoencoder, uniform manifold approximation and projection (UMAP) models, neural network models, and longitudinal factor analysis models. In addition, a special chapter covers metrics for comparing model performance. Features of this book include: Numerous worked examples with replicable R code Explicit comprehensive coverage of data assumptions Adaptation of factor methods to binary, ordinal, and categorical data Residual and outlier analysis Visualization of factor results Final chapters that treat integration of factor analysis with neural network and time series methods Presented in color with R code and introduction to R and RStudio, this book will be suitable for graduate-level and optional module courses for social scientists, and on quantitative methods and multivariate statistics courses.

This volume gathers together key new contributions on the subject of the relationship, both empirical and theoretical, between economic oscillations, growth and structural change. Employing a sophisticated level of mathematical modelling, the collection contains articles from, amongst others, William Baumol, Katsuhito Iwai and William Brock.

Contrary to much Marxist thought, Everling does not view socialism as an antithesis to capitalism, and argues that socialism is, among other things, an objective development of capitalism. As capitalism develops it creates the premises for social development which are also the bases for a socialist and democratic construction of society. Drawing on economics, urban geography, political theory and Marxism, Social Economy: * Examines the evolution of capitalism from its early industrial to its present urban and global forms * Shows how Marx understood the economy as a unity of production, distribution, exchange and consumption engaged in social reproduction * Explores the contradictory evolution of US corporations and urban development from 1945 to the present * Argues that urban space involves requirements for social and individual reproduction which extend well beyond limits inherent in transnational corporate private appropriation Using his unique arguments, Everling makes the case that economic expansion can now best be secured by forms of development that take us beyond the limits of capitalism and point towards a democratic and socialist society.

This book is about the concept of "Quality of Life". What is necessary for quality of life, and how can it be measured? The approach is a multicriterial scheme reduction which prevents as much information loss as possible when shifting from the set of partial criteria to their convolution. This book is written for researchers, analysts and graduate and postgraduate students of mathematics and economics.

This Palgrave Pivot re-examines salary formation in Major League Baseball in light of real option theory to clarify the connection between salary and marginal revenue product for professional baseball players. Current literature has tended to treat single-year and multi-year contracts similarly, ignoring the potential option value for teams and for players. Recent work points to the observation that both high-productivity and low-productivity athletes have salaries that systematically differ from their marginal revenue product, and that free agents signing multi-year contracts are overpaid relative to free agents signing one-year contracts. This book argues that the value of signing an athlete to a contract should be determined similarly to the determination of the value of an investment project or a financial asset. This book demonstrates how to calculate the value of real options to the player and the team owner with a simple two-year contract, and offers extensions to the real options model for multiyear contracts or when a player is early or late in his career.

Quantile regression has emerged as an essential statistical tool of contemporary empirical economics and biostatistics. Complementing classical least squares regression methods which are designed to estimate conditional mean models, quantile regression provides an ensemble of techniques for estimating families of conditional quantile models, thus offering a more complete view of the stochastic relationship among variables. This volume collects 12 outstanding empirical contributions in economics and offers an indispensable introduction to interpretation, implementation, and inference aspects of quantile regression.

Written by Lars Peter Hansen (Nobel Laureate in Economics, 2013) and Thomas Sargent (Nobel Laureate in Economics, 2011), Uncertainty within Economic Models includes articles adapting and applying robust control theory to problems in economics and finance. This book extends rational expectations models by including agents who doubt their models and adopt precautionary decisions designed to protect themselves from adverse consequences of model misspecification. This behavior has consequences for what are ordinarily interpreted as market prices of risk, but big parts of which should actually be interpreted as market prices of model uncertainty. The chapters discuss ways of calibrating agents' fears of model misspecification in quantitative contexts.

Are there distinct European traditions in economics? Is modern economics homogenous and American? The volume includes case studies of the UK, Sweden, the Netherlands, Belgium, Germany, France, Italy, Portugal, Spain and Greece. Each of these examines the conditions relating to the supply of, and demand for, economists. These include: the growth of higher education, the development of postgraduate training in economics, international linkages, both within Europe and outside it, economic ideas and professionalization, and involvement in economic policy-making and public affairs. Whilst each chapter is attentive to particular national features, they also place the development of economics in the context of the postwar movement towards European integration.

Understanding why so many people across the world are so poor is one of the central intellectual challenges of our time. This book provides the tools and data that will enable students, researchers and professionals to address that issue. Empirical Development Economics has been designed as a hands-on teaching tool to investigate the causes of poverty. The book begins by introducing the quantitative approach to development economics. Each section uses data to illustrate key policy issues. Part One focuses on the basics of understanding the role of education, technology and institutions in determining why incomes differ so much across individuals and countries. In Part Two, the focus is on techniques to address a number of topics in development, including how firms invest, how households decide how much to spend on their children's education, whether microcredit helps the poor, whether food aid works, who gets private schooling and whether property rights enhance investment. A distinctive feature of the book is its presentation of a range of approaches to studying development questions. Development economics has undergone a major change in focus over the last decade with the rise of experimental methods to address development issues; this book shows how these methods relate to more traditional ones. Please visit the book's website at www.empiricalde.com for online supplements including Stata files and solutions to the exercises.

The volume aims at providing an outlet for some of the best papers presented at the 15th Annual Conference of the African Econometric Society, which is one of the "chapters" of the International Econometric Society. Many of these papers represent the state of the art in financial econometrics and applied econometric modeling, and some also provide useful simulations that shed light on the models' ability to generate meaningful scenarios for forecasting and policy analysis.