Data Science For Financial Econometrics
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Data Science For Financial Econometrics
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Author : Nguyen Ngoc Thach
language : en
Publisher: Springer Nature
Release Date : 2020-11-13
Data Science For Financial Econometrics written by Nguyen Ngoc Thach and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-13 with Computers categories.
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
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Author : Sergio Consoli
language : en
Publisher: Springer Nature
Release Date : 2021-06-09
Data Science For Economics And Finance written by Sergio Consoli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-09 with Computers categories.
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
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Author : Sinem Derindere Köseoğlu
language : en
Publisher: Springer Nature
Release Date : 2022-04-25
Financial Data Analytics written by Sinem Derindere Köseoğlu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-25 with Business & Economics categories.
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.
Big Data Science In Finance
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Author : Irene Aldridge
language : en
Publisher: John Wiley & Sons
Release Date : 2021-01-27
Big Data Science In Finance written by Irene Aldridge and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-27 with Computers categories.
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.
Handbook Of Financial Econometrics Mathematics Statistics And Machine Learning In 4 Volumes
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Author : Cheng Few Lee
language : en
Publisher: World Scientific
Release Date : 2020-07-30
Handbook Of Financial Econometrics Mathematics Statistics And Machine Learning In 4 Volumes written by Cheng Few Lee and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-30 with Business & Economics categories.
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.
The Elements Of Financial Econometrics
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Author : Jianqing Fan
language : en
Publisher: Cambridge University Press
Release Date : 2017-03-23
The Elements Of Financial Econometrics written by Jianqing Fan and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-23 with Business & Economics categories.
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.
Statistics For Business And Financial Economics 2nd Edition
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Author : Cheng Few Lee
language : en
Publisher: World Scientific Publishing Company
Release Date : 1999-08-16
Statistics For Business And Financial Economics 2nd Edition written by Cheng Few Lee and has been published by World Scientific Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-08-16 with Mathematics categories.
News Professor Cheng-Few Lee ranks #1 based on his publications in the 26 core finance journals, and #163 based on publications in the 7 leading finance journals (Source: Most Prolific Authors in the Finance Literature: 1959-2008 by Jean L Heck and Philip L Cooley (Saint Joseph's University and Trinity University).This is an extensively revised edition of a popular statistics textbook for business and economics students. The first edition has been adopted by universities and colleges worldwide, including New York University, Carnegie Mellon University and UCLA.Designed for upper-level undergraduates, MBA and other graduate students, this book closely integrates various statistical techniques with concepts from business, economics and finance and clearly demonstrates the power of statistical methods in the real world of business. While maintaining the essence of the first edition, the new edition places more emphasis on finance, economics and accounting concepts with updated sample data. Students will find this book very accessible with its straightforward language, ample cases, examples, illustrations and real-life applications. The book is also useful for financial analysts and portfolio managers.
Financial Econometrics
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Author : Svetlozar T. Rachev
language : en
Publisher: John Wiley & Sons
Release Date : 2007-03-22
Financial Econometrics written by Svetlozar T. Rachev and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-03-22 with Business & Economics categories.
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.
Applied Financial Econometrics
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Author : Moinak Maiti
language : en
Publisher: Springer Nature
Release Date : 2021-08-31
Applied Financial Econometrics written by Moinak Maiti and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-31 with Business & Economics categories.
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.
Econometrics Of Financial High Frequency Data
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Author : Nikolaus Hautsch
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-10-12
Econometrics Of Financial High Frequency Data written by Nikolaus Hautsch and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-12 with Business & Economics categories.
The availability of financial data recorded on high-frequency level has inspired a research area which over the last decade emerged to a major area in econometrics and statistics. The growing popularity of high-frequency econometrics is driven by technological progress in trading systems and an increasing importance of intraday trading, liquidity risk, optimal order placement as well as high-frequency volatility. This book provides a state-of-the art overview on the major approaches in high-frequency econometrics, including univariate and multivariate autoregressive conditional mean approaches for different types of high-frequency variables, intensity-based approaches for financial point processes and dynamic factor models. It discusses implementation details, provides insights into properties of high-frequency data as well as institutional settings and presents applications to volatility and liquidity estimation, order book modelling and market microstructure analysis.