Statistical Properties in Firms’ Large-scale Data

Statistical Properties in Firms’ Large-scale Data

Author: Atushi Ishikawa

Publisher: Springer Nature

Published: 2021-06-25

Total Pages: 146

ISBN-13: 9811622973

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This is the first book to provide a systematic description of statistical properties of large-scale financial data. Specifically, the power-law and log-normal distributions observed at a given time and their changes using time-reversal symmetry, quasi-time-reversal symmetry, Gibrat's law, and the non-Gibrat's property observed in a short-term period are derived here. The statistical properties observed over a long-term period, such as power-law and exponential growth, are also derived. These subjects have not been thoroughly discussed in the field of economics in the past, and this book is a compilation of the author's series of studies by reconstructing the data analyses published in 15 academic journals with new data. This book provides readers with a theoretical and empirical understanding of how the statistical properties observed in firms’ large-scale data are related along the time axis. It is possible to expand this discussion to understand theoretically and empirically how the statistical properties observed among differing large-scale financial data are related. This possibility provides readers with an approach to microfoundations, an important issue that has been studied in economics for many years.


Statistical Properties in Firms' Large-scale Data

Statistical Properties in Firms' Large-scale Data

Author: Atushi Ishikawa

Publisher:

Published: 2021

Total Pages: 0

ISBN-13: 9789811622984

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This is the first book to provide a systematic description of statistical properties of large-scale financial data. Specifically, the power-law and log-normal distributions observed at a given time and their changes using time-reversal symmetry, quasi-time-reversal symmetry, Gibrat's law, and the non-Gibrat's property observed in a short-term period are derived here. The statistical properties observed over a long-term period, such as power-law and exponential growth, are also derived. These subjects have not been thoroughly discussed in the field of economics in the past, and this book is a compilation of the author's series of studies by reconstructing the data analyses published in 15 academic journals with new data. This book provides readers with a theoretical and empirical understanding of how the statistical properties observed in firms' large-scale data are related along the time axis. It is possible to expand this discussion to understand theoretically and empirically how the statistical properties observed among differing large-scale financial data are related. This possibility provides readers with an approach to microfoundations, an important issue that has been studied in economics for many years.


Frontiers in Massive Data Analysis

Frontiers in Massive Data Analysis

Author: National Research Council

Publisher: National Academies Press

Published: 2013-09-03

Total Pages: 191

ISBN-13: 0309287812

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Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.


Federal Statistics, Multiple Data Sources, and Privacy Protection

Federal Statistics, Multiple Data Sources, and Privacy Protection

Author: National Academies of Sciences, Engineering, and Medicine

Publisher: National Academies Press

Published: 2018-01-27

Total Pages: 195

ISBN-13: 0309465370

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The environment for obtaining information and providing statistical data for policy makers and the public has changed significantly in the past decade, raising questions about the fundamental survey paradigm that underlies federal statistics. New data sources provide opportunities to develop a new paradigm that can improve timeliness, geographic or subpopulation detail, and statistical efficiency. It also has the potential to reduce the costs of producing federal statistics. The panel's first report described federal statistical agencies' current paradigm, which relies heavily on sample surveys for producing national statistics, and challenges agencies are facing; the legal frameworks and mechanisms for protecting the privacy and confidentiality of statistical data and for providing researchers access to data, and challenges to those frameworks and mechanisms; and statistical agencies access to alternative sources of data. The panel recommended a new approach for federal statistical programs that would combine diverse data sources from government and private sector sources and the creation of a new entity that would provide the foundational elements needed for this new approach, including legal authority to access data and protect privacy. This second of the panel's two reports builds on the analysis, conclusions, and recommendations in the first one. This report assesses alternative methods for implementing a new approach that would combine diverse data sources from government and private sector sources, including describing statistical models for combining data from multiple sources; examining statistical and computer science approaches that foster privacy protections; evaluating frameworks for assessing the quality and utility of alternative data sources; and various models for implementing the recommended new entity. Together, the two reports offer ideas and recommendations to help federal statistical agencies examine and evaluate data from alternative sources and then combine them as appropriate to provide the country with more timely, actionable, and useful information for policy makers, businesses, and individuals.


OECD Digital Economy Outlook 2024 (Volume 1) Embracing the Technology Frontier

OECD Digital Economy Outlook 2024 (Volume 1) Embracing the Technology Frontier

Author: OECD

Publisher: OECD Publishing

Published: 2024-05-14

Total Pages: 161

ISBN-13: 9264654267

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The OECD Digital Economy Outlook 2024, Volume 1: Embracing the Technology Frontier provides new insights on key technologies that underpin the digital technology ecosystem and their impacts. Using big data and machine-learning techniques, Volume 1 provides new estimates of the growth rate of the ecosystem’s core – the information and communications technology (ICT) sector.


Classical Econophysics

Classical Econophysics

Author: Allin F. Cottrell

Publisher: Routledge

Published: 2009-06-02

Total Pages: 385

ISBN-13: 1134020767

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This book sets out to address some basic questions drawing from classical political economy and information theory and using an econophysics methodology: What is information? Why is it valuable? What is the relationship between money and information?


Plunkett's Almanac of Middle Market Companies: Middle Market Research, Statistics & Leading Companies

Plunkett's Almanac of Middle Market Companies: Middle Market Research, Statistics & Leading Companies

Author: Jack W. Plunkett

Publisher: Plunkett Research, Ltd.

Published: 2007-07

Total Pages: 660

ISBN-13: 159392092X

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Plunkett's Almanac of Middle Market Companies 2008 is designed to be time-saving business development tool for professionals, marketers, sales directors, consultants and strategists seeking to understand and reach middle market American companies. It will also be of great use to placement, recruiting and human resources professionals, as well as professionals working in economic development, lending and media. It covers competitive intelligence, market research and business analysis--everything you need to identify and develop strategies for middle market corporations. Coverage includes all major business sectors, from InfoTech to health care to telecommunications and much more. (We have intentionally omitted retail companies and banks.) These profiles and details on over 500 middle market firms are pulled from our extensive company and industry databases. We also include a business glossary and a listing of business contacts, such as industry associations and government agencies. Next, we profile hundreds of leading middle market companies. Our company profiles include complete business descriptions and up to 27 executives by name and title. Purchasers of either the book or PDF version can receive a free copy of the company profiles database on CD-ROM, enabling key word search and export of key information, addresses, phone numbers and executive names with titles for every company profiled.


Research Anthology on Big Data Analytics, Architectures, and Applications

Research Anthology on Big Data Analytics, Architectures, and Applications

Author: Management Association, Information Resources

Publisher: IGI Global

Published: 2021-09-24

Total Pages: 1988

ISBN-13: 1668436639

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Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.