Data Science For Financial Econometrics

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Data Science for Financial Econometrics

Nguyen Ngoc Thach,Vladik Kreinovich,Nguyen Duc Trung
Data Science for Financial Econometrics Book PDF

Author : Nguyen Ngoc Thach,Vladik Kreinovich,Nguyen Duc Trung
Publisher : Springer Nature
Page : 633 pages
File Size : 49,8 Mb
Release : 2020-11-13
Category : Computers
ISBN : 9783030488536

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Data Science for Financial Econometrics by Nguyen Ngoc Thach,Vladik Kreinovich,Nguyen Duc Trung Pdf

This book offers an overview of state-of-the-art econometric techniques, with a special emphasis on financial econometrics. There is a major need for such techniques, since the traditional way of designing mathematical models – based on researchers’ insights – can no longer keep pace with the ever-increasing data flow. To catch up, many application areas have begun relying on data science, i.e., on techniques for extracting models from data, such as data mining, machine learning, and innovative statistics. In terms of capitalizing on data science, many application areas are way ahead of economics. To close this gap, the book provides examples of how data science techniques can be used in economics. Corresponding techniques range from almost traditional statistics to promising novel ideas such as quantum econometrics. Given its scope, the book will appeal to students and researchers interested in state-of-the-art developments, and to practitioners interested in using data science techniques.

Data Science for Economics and Finance

Sergio Consoli,Diego Reforgiato Recupero,Michaela Saisana
Data Science for Economics and Finance Book PDF

Author : Sergio Consoli,Diego Reforgiato Recupero,Michaela Saisana
Publisher : Springer Nature
Page : 357 pages
File Size : 49,7 Mb
Release : 2021
Category : Application software
ISBN : 9783030668914

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Data Science for Economics and Finance by Sergio Consoli,Diego Reforgiato Recupero,Michaela Saisana Pdf

This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.

Financial Data Analytics

Sinem Derindere Köseoğlu
Financial Data Analytics Book PDF

Author : Sinem Derindere Köseoğlu
Publisher : Springer Nature
Page : 393 pages
File Size : 45,6 Mb
Release : 2022-04-25
Category : Business & Economics
ISBN : 9783030837990

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Financial Data Analytics by Sinem Derindere Köseoğlu Pdf

​This book presents both theory of financial data analytics, as well as comprehensive insights into the application of financial data analytics techniques in real financial world situations. It offers solutions on how to logically analyze the enormous amount of structured and unstructured data generated every moment in the finance sector. This data can be used by companies, organizations, and investors to create strategies, as the finance sector rapidly moves towards data-driven optimization. This book provides an efficient resource, addressing all applications of data analytics in the finance sector. International experts from around the globe cover the most important subjects in finance, including data processing, knowledge management, machine learning models, data modeling, visualization, optimization for financial problems, financial econometrics, financial time series analysis, project management, and decision making. The authors provide empirical evidence as examples of specific topics. By combining both applications and theory, the book offers a holistic approach. Therefore, it is a must-read for researchers and scholars of financial economics and finance, as well as practitioners interested in a better understanding of financial data analytics.

Advances in Econometrics, Operational Research, Data Science and Actuarial Studies

M. Kenan Terzioğlu
Advances in Econometrics Operational Research Data Science and Actuarial Studies Book PDF

Author : M. Kenan Terzioğlu
Publisher : Springer Nature
Page : 607 pages
File Size : 43,5 Mb
Release : 2022-01-17
Category : Business & Economics
ISBN : 9783030852542

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Advances in Econometrics, Operational Research, Data Science and Actuarial Studies by M. Kenan Terzioğlu Pdf

This volume presents techniques and theories drawn from mathematics, statistics, computer science, and information science to analyze problems in business, economics, finance, insurance, and related fields. The authors present proposals for solutions to common problems in related fields. To this end, they are showing the use of mathematical, statistical, and actuarial modeling, and concepts from data science to construct and apply appropriate models with real-life data, and employ the design and implementation of computer algorithms to evaluate decision-making processes. This book is unique as it associates data science - data-scientists coming from different backgrounds - with some basic and advanced concepts and tools used in econometrics, operational research, and actuarial sciences. It, therefore, is a must-read for scholars, students, and practitioners interested in a better understanding of the techniques and theories of these fields.

Big Data Science in Finance

Irene Aldridge,Marco Avellaneda
Big Data Science in Finance Book PDF

Author : Irene Aldridge,Marco Avellaneda
Publisher : John Wiley & Sons
Page : 336 pages
File Size : 50,5 Mb
Release : 2021-01-08
Category : Computers
ISBN : 9781119602972

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Big Data Science in Finance by Irene Aldridge,Marco Avellaneda Pdf

Explains the mathematics, theory, and methods of Big Data as applied to finance and investing Data science has fundamentally changed Wall Street—applied mathematics and software code are increasingly driving finance and investment-decision tools. Big Data Science in Finance examines the mathematics, theory, and practical use of the revolutionary techniques that are transforming the industry. Designed for mathematically-advanced students and discerning financial practitioners alike, this energizing book presents new, cutting-edge content based on world-class research taught in the leading Financial Mathematics and Engineering programs in the world. Marco Avellaneda, a leader in quantitative finance, and quantitative methodology author Irene Aldridge help readers harness the power of Big Data. Comprehensive in scope, this book offers in-depth instruction on how to separate signal from noise, how to deal with missing data values, and how to utilize Big Data techniques in decision-making. Key topics include data clustering, data storage optimization, Big Data dynamics, Monte Carlo methods and their applications in Big Data analysis, and more. This valuable book: Provides a complete account of Big Data that includes proofs, step-by-step applications, and code samples Explains the difference between Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) Covers vital topics in the field in a clear, straightforward manner Compares, contrasts, and discusses Big Data and Small Data Includes Cornell University-tested educational materials such as lesson plans, end-of-chapter questions, and downloadable lecture slides Big Data Science in Finance: Mathematics and Applications is an important, up-to-date resource for students in economics, econometrics, finance, applied mathematics, industrial engineering, and business courses, and for investment managers, quantitative traders, risk and portfolio managers, and other financial practitioners.

Financial Data Analytics

Sinem Derindere Köseoğlu
Financial Data Analytics Book PDF

Author : Sinem Derindere Köseoğlu
Publisher : Unknown
Page : 0 pages
File Size : 51,6 Mb
Release : 2022
Category : Electronic
ISBN : 3030838005

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Financial Data Analytics by Sinem Derindere Köseoğlu Pdf

This book presents both theory of financial data analytics, as well as comprehensive insights into the application of financial data analytics techniques in real financial world situations. It offers solutions on how to logically analyze the enormous amount of structured and unstructured data generated every moment in the finance sector. This data can be used by companies, organizations, and investors to create strategies, as the finance sector rapidly moves towards data-driven optimization. This book provides an efficient resource, addressing all applications of data analytics in the finance sector. International experts from around the globe cover the most important subjects in finance, including data processing, knowledge management, machine learning models, data modeling, visualization, optimization for financial problems, financial econometrics, financial time series analysis, project management, and decision making. The authors provide empirical evidence as examples of specific topics. By combining both applications and theory, the book offers a holistic approach. Therefore, it is a must-read for researchers and scholars of financial economics and finance, as well as practitioners interested in a better understanding of financial data analytics. .

The Elements of Financial Econometrics

Jianqing Fan,Qiwei Yao
The Elements of Financial Econometrics Book PDF

Author : Jianqing Fan,Qiwei Yao
Publisher : Cambridge University Press
Page : 394 pages
File Size : 52,8 Mb
Release : 2017-03-23
Category : Business & Economics
ISBN : 9781107191174

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The Elements of Financial Econometrics by Jianqing Fan,Qiwei Yao Pdf

A compact, master's-level textbook on financial econometrics, focusing on methodology and including real financial data illustrations throughout. The mathematical level is purposely kept moderate, allowing the power of the quantitative methods to be understood without too much technical detail.

Big Data Science in Finance

Irene Aldridge,Marco Avellaneda
Big Data Science in Finance Book PDF

Author : Irene Aldridge,Marco Avellaneda
Publisher : John Wiley & Sons
Page : 336 pages
File Size : 44,6 Mb
Release : 2021-01-27
Category : Computers
ISBN : 9781119602989

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Big Data Science in Finance by Irene Aldridge,Marco Avellaneda Pdf

Explains the mathematics, theory, and methods of Big Data as applied to finance and investing Data science has fundamentally changed Wall Street—applied mathematics and software code are increasingly driving finance and investment-decision tools. Big Data Science in Finance examines the mathematics, theory, and practical use of the revolutionary techniques that are transforming the industry. Designed for mathematically-advanced students and discerning financial practitioners alike, this energizing book presents new, cutting-edge content based on world-class research taught in the leading Financial Mathematics and Engineering programs in the world. Marco Avellaneda, a leader in quantitative finance, and quantitative methodology author Irene Aldridge help readers harness the power of Big Data. Comprehensive in scope, this book offers in-depth instruction on how to separate signal from noise, how to deal with missing data values, and how to utilize Big Data techniques in decision-making. Key topics include data clustering, data storage optimization, Big Data dynamics, Monte Carlo methods and their applications in Big Data analysis, and more. This valuable book: Provides a complete account of Big Data that includes proofs, step-by-step applications, and code samples Explains the difference between Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) Covers vital topics in the field in a clear, straightforward manner Compares, contrasts, and discusses Big Data and Small Data Includes Cornell University-tested educational materials such as lesson plans, end-of-chapter questions, and downloadable lecture slides Big Data Science in Finance: Mathematics and Applications is an important, up-to-date resource for students in economics, econometrics, finance, applied mathematics, industrial engineering, and business courses, and for investment managers, quantitative traders, risk and portfolio managers, and other financial practitioners.

Financial Analytics with R

Mark J. Bennett,Dirk L. Hugen
Financial Analytics with R Book PDF

Author : Mark J. Bennett,Dirk L. Hugen
Publisher : Cambridge University Press
Page : 397 pages
File Size : 51,5 Mb
Release : 2016-10-06
Category : Business & Economics
ISBN : 9781107150751

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Financial Analytics with R by Mark J. Bennett,Dirk L. Hugen Pdf

Financial Analytics with R sharpens readers' skills in time-series, forecasting, portfolio selection, covariance clustering, prediction, and derivative securities.

The Econometrics of Financial Markets

John Y. Campbell,Andrew W. Lo,A. Craig MacKinlay
The Econometrics of Financial Markets Book PDF

Author : John Y. Campbell,Andrew W. Lo,A. Craig MacKinlay
Publisher : Princeton University Press
Page : 630 pages
File Size : 54,8 Mb
Release : 2012-06-28
Category : Business & Economics
ISBN : 9781400830213

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The Econometrics of Financial Markets by John Y. Campbell,Andrew W. Lo,A. Craig MacKinlay Pdf

The past twenty years have seen an extraordinary growth in the use of quantitative methods in financial markets. Finance professionals now routinely use sophisticated statistical techniques in portfolio management, proprietary trading, risk management, financial consulting, and securities regulation. This graduate-level textbook is intended for PhD students, advanced MBA students, and industry professionals interested in the econometrics of financial modeling. The book covers the entire spectrum of empirical finance, including: the predictability of asset returns, tests of the Random Walk Hypothesis, the microstructure of securities markets, event analysis, the Capital Asset Pricing Model and the Arbitrage Pricing Theory, the term structure of interest rates, dynamic models of economic equilibrium, and nonlinear financial models such as ARCH, neural networks, statistical fractals, and chaos theory. Each chapter develops statistical techniques within the context of a particular financial application. This exciting new text contains a unique and accessible combination of theory and practice, bringing state-of-the-art statistical techniques to the forefront of financial applications. Each chapter also includes a discussion of recent empirical evidence, for example, the rejection of the Random Walk Hypothesis, as well as problems designed to help readers incorporate what they have read into their own applications.

Applied Financial Econometrics

Moinak Maiti
Applied Financial Econometrics Book PDF

Author : Moinak Maiti
Publisher : Springer Nature
Page : 287 pages
File Size : 40,7 Mb
Release : 2021-08-31
Category : Business & Economics
ISBN : 9789811640636

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Applied Financial Econometrics by Moinak Maiti Pdf

This textbook gives students an approachable, down to earth resource for the study of financial econometrics. While the subject can be intimidating, primarily due to the mathematics and modelling involved, it is rewarding for students of finance and can be taught and learned in a straightforward way. This book, going from basics to high level concepts, offers knowledge of econometrics that is intended to be used with confidence in the real world. This book will be beneficial for both students and tutors who are associated with econometrics subjects at any level.

Financial, Macro and Micro Econometrics Using R

Hrishikesh D. Vinod
Financial Macro and Micro Econometrics Using R Book PDF

Author : Hrishikesh D. Vinod
Publisher : North Holland
Page : 350 pages
File Size : 44,8 Mb
Release : 2020-01-24
Category : Electronic
ISBN : 9780128202500

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Financial, Macro and Micro Econometrics Using R by Hrishikesh D. Vinod Pdf

Financial, Macro and Micro Econometrics Using R, Volume 42, provides state-of-the-art information on important topics in econometrics, including multivariate GARCH, stochastic frontiers, fractional responses, specification testing and model selection, exogeneity testing, causal analysis and forecasting, GMM models, asset bubbles and crises, corporate investments, classification, forecasting, nonstandard problems, cointegration, financial market jumps and co-jumps, among other topics. Presents chapters authored by distinguished, honored researchers who have received awards from the Journal of Econometrics or the Econometric Society Includes descriptions and links to resources and free open source R Gives readers what they need to jumpstart their understanding on the state-of-the-art

Financial Econometrics

Oliver Linton
Financial Econometrics Book PDF

Author : Oliver Linton
Publisher : Cambridge University Press
Page : 585 pages
File Size : 44,8 Mb
Release : 2019-02-21
Category : Business & Economics
ISBN : 9781107177154

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Financial Econometrics by Oliver Linton Pdf

Presents an up-to-date treatment of the models and methodologies of financial econometrics by one of the world's leading financial econometricians.

Handbook Of Financial Econometrics, Mathematics, Statistics, And Machine Learning (In 4 Volumes)

Cheng Few Lee,John C Lee
Handbook Of Financial Econometrics Mathematics Statistics And Machine Learning In 4 Volumes Book PDF

Author : Cheng Few Lee,John C Lee
Publisher : World Scientific
Page : 5053 pages
File Size : 50,9 Mb
Release : 2020-07-30
Category : Business & Economics
ISBN : 9789811202407

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Handbook Of Financial Econometrics, Mathematics, Statistics, And Machine Learning (In 4 Volumes) by Cheng Few Lee,John C Lee Pdf

This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In both theory and methodology, we need to rely upon mathematics, which includes linear algebra, geometry, differential equations, Stochastic differential equation (Ito calculus), optimization, constrained optimization, and others. These forms of mathematics have been used to derive capital market line, security market line (capital asset pricing model), option pricing model, portfolio analysis, and others.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience.

Financial Econometrics

Svetlozar T. Rachev,Stefan Mittnik,Frank J. Fabozzi,Sergio M. Focardi,Teo Jašić
Financial Econometrics Book PDF

Author : Svetlozar T. Rachev,Stefan Mittnik,Frank J. Fabozzi,Sergio M. Focardi,Teo Jašić
Publisher : John Wiley & Sons
Page : 560 pages
File Size : 49,7 Mb
Release : 2007-03-22
Category : Business & Economics
ISBN : 9780470121528

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Financial Econometrics by Svetlozar T. Rachev,Stefan Mittnik,Frank J. Fabozzi,Sergio M. Focardi,Teo Jašić Pdf

A comprehensive guide to financial econometrics Financial econometrics is a quest for models that describe financial time series such as prices, returns, interest rates, and exchange rates. In Financial Econometrics, readers will be introduced to this growing discipline and the concepts and theories associated with it, including background material on probability theory and statistics. The experienced author team uses real-world data where possible and brings in the results of published research provided by investment banking firms and journals. Financial Econometrics clearly explains the techniques presented and provides illustrative examples for the topics discussed. Svetlozar T. Rachev, PhD (Karlsruhe, Germany) is currently Chair-Professor at the University of Karlsruhe. Stefan Mittnik, PhD (Munich, Germany) is Professor of Financial Econometrics at the University of Munich. Frank J. Fabozzi, PhD, CFA, CFP (New Hope, PA) is an adjunct professor of Finance at Yale University’s School of Management. Sergio M. Focardi (Paris, France) is a founding partner of the Paris-based consulting firm The Intertek Group. Teo Jasic, PhD, (Frankfurt, Germany) is a senior manager with a leading international management consultancy firm in Frankfurt.