Computational finance is increasingly important in the financial industry, as a necessary instrument for applying theoretical models to real-world challenges. Indeed, many models used in practice involve complex mathematical problems, for which an exact or a closed-form solution is not available. Consequently, we need to rely on computational techniques and specific numerical algorithms. This book combines theoretical concepts with practical implementation. Furthermore, the numerical solution of models is exploited, both to enhance the understanding of some mathematical and statistical notions, and to acquire sound programming skills in MATLAB (R), which is useful for several other programming languages also. The material assumes the reader has a relatively limited knowledge of mathematics, probability, and statistics. Hence, the book contains a short description of the fundamental tools needed to address the two main fields of quantitative finance: portfolio selection and derivatives pricing. Both fields are developed here, with a particular emphasis on portfolio selection, where the author includes an overview of recent approaches. The book gradually takes the reader from a basic to medium level of expertise by using examples and exercises to simplify the understanding of complex models in finance, giving them the ability to place financial models in a computational setting. The book is ideal for courses focusing on quantitative finance, asset management, mathematical methods for economics and finance, investment banking, and corporate finance.

High-Performance Computing for Big Data: Methodologies and Applications explores emerging high-performance architectures for data-intensive applications, novel efficient analytical strategies to boost data processing, and cutting-edge applications in diverse fields, such as machine learning, life science, neural networks, and neuromorphic engineering. The book is organized into two main sections. The first section covers Big Data architectures, including cloud computing systems, and heterogeneous accelerators. It also covers emerging 3D IC design principles for memory architectures and devices. The second section of the book illustrates emerging and practical applications of Big Data across several domains, including bioinformatics, deep learning, and neuromorphic engineering. Features Covers a wide range of Big Data architectures, including distributed systems like Hadoop/Spark Includes accelerator-based approaches for big data applications such as GPU-based acceleration techniques, and hardware acceleration such as FPGA/CGRA/ASICs Presents emerging memory architectures and devices such as NVM, STT- RAM, 3D IC design principles Describes advanced algorithms for different big data application domains Illustrates novel analytics techniques for Big Data applications, scheduling, mapping, and partitioning methodologies Featuring contributions from leading experts, this book presents state-of-the-art research on the methodologies and applications of high-performance computing for big data applications. About the Editor Dr. Chao Wang is an Associate Professor in the School of Computer Science at the University of Science and Technology of China. He is the Associate Editor of ACM Transactions on Design Automations for Electronics Systems (TODAES), Applied Soft Computing, Microprocessors and Microsystems, IET Computers & Digital Techniques, and International Journal of Electronics. Dr. Chao Wang was the recipient of Youth Innovation Promotion Association, CAS, ACM China Rising Star Honorable Mention (2016), and best IP nomination of DATE 2015. He is now on the CCF Technical Committee on Computer Architecture, CCF Task Force on Formal Methods. He is a Senior Member of IEEE, Senior Member of CCF, and a Senior Member of ACM.

This book presents recent developments on the theoretical, algorithmic, and application aspects of Big Data in Complex and Social Networks. The book consists of four parts, covering a wide range of topics. The first part of the book focuses on data storage and data processing. It explores how the efficient storage of data can fundamentally support intensive data access and queries, which enables sophisticated analysis. It also looks at how data processing and visualization help to communicate information clearly and efficiently. The second part of the book is devoted to the extraction of essential information and the prediction of web content. The book shows how Big Data analysis can be used to understand the interests, location, and search history of users and provide more accurate predictions of User Behavior. The latter two parts of the book cover the protection of privacy and security, and emergent applications of big data and social networks. It analyzes how to model rumor diffusion, identify misinformation from massive data, and design intervention strategies. Applications of big data and social networks in multilayer networks and multiparty systems are also covered in-depth.

This work examines theoretical issues, as well as practical developments in statistical inference related to econometric models and analysis. This work offers discussions on such areas as the function of statistics in aggregation, income inequality, poverty, health, spatial econometrics, panel and survey data, bootstrapping and time series.

This textbook discusses central statistical concepts and their use in business and economics. To endure the hardship of abstract statistical thinking, business and economics students need to see interesting applications at an early stage. Accordingly, the book predominantly focuses on exercises, several of which draw on simple applications of non-linear theory. The main body presents central ideas in a simple, straightforward manner; the exposition is concise, without sacrificing rigor. The book bridges the gap between theory and applications, with most exercises formulated in an economic context. Its simplicity of style makes the book suitable for students at any level, and every chapter starts out with simple problems. Several exercises, however, are more challenging, as they are devoted to the discussion of non-trivial economic problems where statistics plays a central part.

This book aims to bring together studies using different data types (panel data, cross-sectional data and time series data) and different methods (for example, panel regression, nonlinear time series, chaos approach, deep learning, machine learning techniques among others) and to create a source for those interested in these topics and methods by addressing some selected applied econometrics topics which have been developed in recent years. It creates a common meeting ground for scientists who give econometrics education in Turkey to study, and contribute to the delivery of the authors' knowledge to the people who take interest. This book can also be useful for "Applied Economics and Econometrics" courses in postgraduate education as a material source

The Handbook of U.S. Labor Statistics is recognized as an authoritative resource on the U.S. labor force. It continues and enhances the Bureau of Labor Statistics's (BLS) discontinued publication, Labor Statistics. It allows the user to understand recent developments as well as to compare today's economy with past history. This edition includes new tables on occupational safety and health and income in the United States. The Handbook is a comprehensive reference providing an abundance of data on a variety of topics including: *Employment and unemployment; *Earnings; *Prices; *Productivity; *Consumer expenditures; *Occupational safety and health; *Union membership; *Working poor *And much more! Features of the publication In addition to over 215 tables that present practical data, the Handbook provides: *Introductory material for each chapter that contains highlights of salient data and figures that call attention to noteworthy trends in the data *Notes and definitions, which contain concise descriptions of the data sources, concepts, definitions, and methodology from which the data are derived *References to more comprehensive reports which provide additional data and more extensive descriptions of estimation methods, sampling, and reliability measures

Since the financial crisis, the issue of the 'one percent' has become the centre of intense public debate, unavoidable even for members of the elite themselves. Moreover, inquiring into elites has taken centre-stage once again in both journalistic investigations and academic research. New Directions in Elite Studies attempts to move the social scientific study of elites beyond economic analysis, which has greatly improved our knowledge of inequality, but is restricted to income and wealth. In contrast, this book mobilizes a broad scope of research methods to uncover the social composition of the power elite - the 'field of power'. It reconstructs processes through which people gain access to positions in this particular social space, examines the various forms of capital they mobilize in the process - economic, but also cultural and social capital - and probes changes over time and variations across national contexts. Bringing together the most advanced research into elites by a European and multidisciplinary group of scholars, this book presents an agenda for the future study of elites. It will appeal to all those interested in the study of elites, inequality, class, power, and gender inequality.

The book aims at perfecting the national governance system and improving national governance ability. It evaluates the balance sheets of the state and residents, non-financial corporations, financial institutions and the central bank, the central government, local government and external sectors - the goal being to provide a systematic analysis of the characteristics and trajectory of China's economic expansion and structural adjustment, as well as objective assessments of short and long-term economic operations, debt risks and financial risks with regard to the institutional and structural characteristics of economic development in market-oriented reform. It puts forward a preliminary analysis of China's national and sectoral balance sheets on the basis of scientific estimates of various kinds of data, analyzes from a new perspective the major issues that are currently troubling China - development sustainability, government transformation, local government debt, welfare reform, and the financial opening-up and stability - and explores corresponding policies, measures, and institutional arrangements.

The first part of this book discusses institutions and mechanisms of algorithmic trading, market microstructure, high-frequency data and stylized facts, time and event aggregation, order book dynamics, trading strategies and algorithms, transaction costs, market impact and execution strategies, risk analysis, and management. The second part covers market impact models, network models, multi-asset trading, machine learning techniques, and nonlinear filtering. The third part discusses electronic market making, liquidity, systemic risk, recent developments and debates on the subject.

Suitable for statisticians, mathematicians, actuaries, and students interested in the problems of insurance and analysis of lifetimes, Statistical Methods with Applications to Demography and Life Insurance presents contemporary statistical techniques for analyzing life distributions and life insurance problems. It not only contains traditional material but also incorporates new problems and techniques not discussed in existing actuarial literature. The book mainly focuses on the analysis of an individual life and describes statistical methods based on empirical and related processes. Coverage ranges from analyzing the tails of distributions of lifetimes to modeling population dynamics with migrations. To help readers understand the technical points, the text covers topics such as the Stieltjes, Wiener, and Ito integrals. It also introduces other themes of interest in demography, including mixtures of distributions, analysis of longevity and extreme value theory, and the age structure of a population. In addition, the author discusses net premiums for various insurance policies. Mathematical statements are carefully and clearly formulated and proved while avoiding excessive technicalities as much as possible. The book illustrates how these statements help solve numerous statistical problems. It also includes more than 70 exercises.

First published in 1995. In the current, increasingly global economy, investors require quick access to a wide range of financial and investment-related statistics to assist them in better understanding the macroeconomic environment in which their investments will operate. The International Financial Statistics Locator eliminates the need to search though a number of sources to identify those that contain much of this statistical information. It is intended for use by librarians, students, individual investors, and the business community and provides access to twenty-two resources, print and electronic, that contain current and historical financial and economic statistics investors need to appreciate and profit from evolving and established international markets.

This book describes a system of mathematical models and methods that can be used to analyze real economic and managerial decisions and to improve their effectiveness. Application areas include: management of development and operation budgets, assessment and management of economic systems using an energy entropy approach, equation of exchange rates and forecasting foreign exchange operations, evaluation of innovative projects, monitoring of governmental programs, risk management of investment processes, decisions on the allocation of resources, and identification of competitive industrial clusters. The proposed methods and models were tested on the example of Kazakhstan's economy, but the generated solutions will be useful for applications at other levels and in other countries. Regarding your book "Mathematical Methods and Models in Economics", I am impressed because now it is time when "econometrics" is becoming more appreciated by economists and by schools that are the hosts or employers of modern economists. ... Your presented results really impressed me. John F. Nash, Jr., Princeton University, Nobel Memorial Prize in Economic Sciences The book is within my scope of interest because of its novelty and practicality. First, there is a need for realistic modeling of complex systems, both natural and artificial that conclude computer and economic systems. There has been an ongoing effort in developing models dealing with complexity and incomplete knowledge. Consequently, it is clear to recognize the contribution of Mutanov to encapsulate economic modeling with emphasis on budgeting and innovation. Secondly, the method proposed by Mutanov has been verified by applying to the case of the Republic of Kazakhstan, with her vibrant emerging economy. Thirdly, Chapter 5 of the book is of particular interest for the computer technology community because it deals with innovation. In summary, the book of Mutanov should become one of the outstanding recognized pragmatic guides for dealing with innovative systems. Andrzej Rucinski, University of New Hampshire This book is unique in its theoretical findings and practical applicability. The book is an illuminating study based on an applied mathematical model which uses methods such as linear programming and input-output analysis. Moreover, this work demonstrates the author's great insight and academic brilliance in the fields of finance, technological innovations and marketing vis-a-vis the market economy. From both theoretical and practical standpoint, this work is indeed a great achievement. Yeon Cheon Oh, President of Seoul National University

Originally published in 1978. This book is designed to enable students on main courses in economics to comprehend literature which employs econometric techniques as a method of analysis, to use econometric techniques themselves to test hypotheses about economic relationships and to understand some of the difficulties involved in interpreting results. While the book is mainly aimed at second-year undergraduates undertaking courses in applied economics, its scope is sufficiently wide to take in students at postgraduate level who have no background in econometrics - it integrates fully the mathematical and statistical techniques used in econometrics with micro- and macroeconomic case studies.

How we pay is so fundamental that it underpins everything – from trade to taxation, stocks and savings to salaries, pensions and pocket money. Rich or poor, criminal, communist or capitalist, we all rely on the same payments system, day in, day out. It sits between us and not just economic meltdown, but a total breakdown in law and order. Why then do we know so little about how that system really works?

Leibbrandt and de Terán shine a light on the hidden workings of the humble payment – and reveal both how our payment habits are determined by history as well as where we might go next. From national customs to warring nation states, geopolitics will shape the future of payments every bit as much as technology.

Challenging our understanding about where financial power really lies, The Pay Off shows us that the most important thing about money is the way we move it.

Exotic Betting at the Racetrack is unique as it covers the efficient-inefficient strategy to price and find profitable racetrack bets, along with handicapping that provides actual bets made by the author on essentially all of the major wagers offered at US racetracks. The book starts with efficiency, accuracy of the win odds, arbitrage, and optimal betting strategies. Examples and actual bets are shown for various wagers including win, place and show, exacta, quinella, double, trifecta, superfecta, Pick 3, 4 and 6 and rainbow pick 5 and 6. There are discussions of major races including the Breeders' Cup, Pegasus, Dubai World Cup and the US Triple Crown from 2012-2018. Dosage analysis is also described and used. An additional feature concerns great horses such as the great mares Rachel Alexandra, Zenyatta, Goldikova, Treve, Beholder and Song Bird. There is a discussion of horse ownership and a tour through arguably the world's top trainer Frederico Tesio and his stables and horses in Italy.Related Link(s)

The beginning of the age of artificial intelligence and machine learning has created new challenges and opportunities for data analysts, statisticians, mathematicians, econometricians, computer scientists and many others. At the root of these techniques are algorithms and methods for clustering and classifying different types of large datasets, including time series data. Time Series Clustering and Classification includes relevant developments on observation-based, feature-based and model-based traditional and fuzzy clustering methods, feature-based and model-based classification methods, and machine learning methods. It presents a broad and self-contained overview of techniques for both researchers and students. Features Provides an overview of the methods and applications of pattern recognition of time series Covers a wide range of techniques, including unsupervised and supervised approaches Includes a range of real examples from medicine, finance, environmental science, and more R and MATLAB code, and relevant data sets are available on a supplementary website

Pathwise estimation and inference for diffusion market models discusses contemporary techniques for inferring, from options and bond prices, the market participants' aggregate view on important financial parameters such as implied volatility, discount rate, future interest rate, and their uncertainty thereof. The focus is on the pathwise inference methods that are applicable to a sole path of the observed prices and do not require the observation of an ensemble of such paths. This book is pitched at the level of senior undergraduate students undertaking research at honors year, and postgraduate candidates undertaking Master's or PhD degree by research. From a research perspective, this book reaches out to academic researchers from backgrounds as diverse as mathematics and probability, econometrics and statistics, and computational mathematics and optimization whose interest lie in analysis and modelling of financial market data from a multi-disciplinary approach. Additionally, this book is also aimed at financial market practitioners participating in capital market facing businesses who seek to keep abreast with and draw inspiration from novel approaches in market data analysis. The first two chapters of the book contains introductory material on stochastic analysis and the classical diffusion stock market models. The remaining chapters discuss more special stock and bond market models and special methods of pathwise inference for market parameter for different models. The final chapter describes applications of numerical methods of inference of bond market parameters to forecasting of short rate. Nikolai Dokuchaev is an associate professor in Mathematics and Statistics at Curtin University. His research interests include mathematical and statistical finance, stochastic analysis, PDEs, control, and signal processing. Lin Yee Hin is a practitioner in the capital market facing industry. His research interests include econometrics, non-parametric regression, and scientific computing.

Modern marketing managers need intuitive and effective tools not just for designing strategies but also for general management. This hands-on book introduces a range of contemporary management and marketing tools and concepts with a focus on forecasting, creating stimulating processes, and implementation. Topics addressed range from creating a clear vision, setting goals, and developing strategies, to implementing strategic analysis tools, consumer value models, budgeting, strategic and operational marketing plans. Special attention is paid to change management and digital transformation in the marketing landscape. Given its approach and content, the book offers a valuable asset for all professionals and advanced MBA students looking for 'real-life' tools and applications.

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.

Advanced Statistics for Kinesiology and Exercise Science is the first textbook to cover advanced statistical methods in the context of the study of human performance. Divided into three distinct sections, the book introduces and explores in depth both analysis of variance (ANOVA) and regressions analyses, including chapters on: preparing data for analysis; one-way, factorial, and repeated-measures ANOVA; analysis of covariance and multiple analyses of variance and covariance; diagnostic tests; regression models for quantitative and qualitative data; model selection and validation; logistic regression Drawing clear lines between the use of IBM SPSS Statistics software and interpreting and analyzing results, and illustrated with sport and exercise science-specific sample data and results sections throughout, the book offers an unparalleled level of detail in explaining advanced statistical techniques to kinesiology students. Advanced Statistics for Kinesiology and Exercise Science is an essential text for any student studying advanced statistics or research methods as part of an undergraduate or postgraduate degree programme in kinesiology, sport and exercise science, or health science.

Probability and Statistics have been widely used in various fields of science, including economics. Like advanced calculus and linear algebra, probability and statistics are indispensable mathematical tools in economics. Statistical inference in economics, namely econometric analysis, plays a crucial methodological role in modern economics, particularly in empirical studies in economics.This textbook covers probability theory and statistical theory in a coherent framework that will be useful in graduate studies in economics, statistics and related fields. As a most important feature, this textbook emphasizes intuition, explanations and applications of probability and statistics from an economic perspective.