Alternative Data Finance
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The Book Of Alternative Data
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Author : Alexander Denev
language : en
Publisher: John Wiley & Sons
Release Date : 2020-07-21
The Book Of Alternative Data written by Alexander Denev 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 2020-07-21 with Business & Economics categories.
The first and only book to systematically address methodologies and processes of leveraging non-traditional information sources in the context of investing and risk management Harnessing non-traditional data sources to generate alpha, analyze markets, and forecast risk is a subject of intense interest for financial professionals. A growing number of regularly-held conferences on alternative data are being established, complemented by an upsurge in new papers on the subject. Alternative data is starting to be steadily incorporated by conventional institutional investors and risk managers throughout the financial world. Methodologies to analyze and extract value from alternative data, guidance on how to source data and integrate data flows within existing systems is currently not treated in literature. Filling this significant gap in knowledge, The Book of Alternative Data is the first and only book to offer a coherent, systematic treatment of the subject. This groundbreaking volume provides readers with a roadmap for navigating the complexities of an array of alternative data sources, and delivers the appropriate techniques to analyze them. The authors—leading experts in financial modeling, machine learning, and quantitative research and analytics—employ a step-by-step approach to guide readers through the dense jungle of generated data. A first-of-its kind treatment of alternative data types, sources, and methodologies, this innovative book: Provides an integrated modeling approach to extract value from multiple types of datasets Treats the processes needed to make alternative data signals operational Helps investors and risk managers rethink how they engage with alternative datasets Features practical use case studies in many different financial markets and real-world techniques Describes how to avoid potential pitfalls and missteps in starting the alternative data journey Explains how to integrate information from different datasets to maximize informational value The Book of Alternative Data is an indispensable resource for anyone wishing to analyze or monetize different non-traditional datasets, including Chief Investment Officers, Chief Risk Officers, risk professionals, investment professionals, traders, economists, and machine learning developers and users.
Handbook Of Alternative Data In Finance Volume I
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Author : Gautam Mitra
language : en
Publisher: CRC Press
Release Date : 2023-07-12
Handbook Of Alternative Data In Finance Volume I written by Gautam Mitra and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-12 with Business & Economics categories.
Handbook of Alternative Data in Finance, Volume I motivates and challenges the reader to explore and apply Alternative Data in finance. The book provides a robust and in-depth overview of Alternative Data, including its definition, characteristics, difference from conventional data, categories of Alternative Data, Alternative Data providers, and more. The book also offers a rigorous and detailed exploration of process, application and delivery that should be practically useful to researchers and practitioners alike. Features Includes cutting edge applications in machine learning, fintech, and more Suitable for professional quantitative analysts, and as a resource for postgraduates and researchers in financial mathematics Features chapters from many leading researchers and practitioners
Alternative Data Finance
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Author : Gerardus Blokdyk
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2018-05-16
Alternative Data Finance written by Gerardus Blokdyk and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-16 with categories.
Why should we adopt a Alternative data (finance) framework? What tools and technologies are needed for a custom Alternative data (finance) project? Are there any constraints known that bear on the ability to perform Alternative data (finance) work? How is the team addressing them? Is there a Alternative data (finance) management charter, including business case, problem and goal statements, scope, milestones, roles and responsibilities, communication plan? How did the Alternative data (finance) manager receive input to the development of a Alternative data (finance) improvement plan and the estimated completion dates/times of each activity? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Alternative data (finance) investments work better. This Alternative data (finance) All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Alternative data (finance) Self-Assessment. Featuring new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Alternative data (finance) improvements can be made. In using the questions you will be better able to: - diagnose Alternative data (finance) projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Alternative data (finance) and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Alternative data (finance) Scorecard, you will develop a clear picture of which Alternative data (finance) areas need attention. Your purchase includes access details to the Alternative data (finance) self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. Your exclusive instant access details can be found in your book.
Handbook Of Alternative Data In Finance
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Author : Gautam Mitra
language : en
Publisher: C&h/CRC Press
Release Date : 2023
Handbook Of Alternative Data In Finance written by Gautam Mitra and has been published by C&h/CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with Finance categories.
"Handbook of Alternative Data in Finance, Volume I Handbook of Alternative Data in Finance, Volume I motivates and challenges the reader to explore and apply Alternative Data in finance. The book provides a robust and in-depth overview of Alternative Data, including its definition, characteristics, difference from conventional data, categories of Alternative Data, Alternative Data providers, and more. The book also offers a rigorous and detailed exploration of process, application and delivery that should be practically useful to researchers and practitioners alike. Features Includes cutting edge applications in machine learning, fintech, and more Suitable for professional quantitative analysts, and as a resource for postgraduates and researchers in financial mathematics Features chapters from many leading researchers and practitioners"--
Fintech With Artificial Intelligence Big Data And Blockchain
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Author : Paul Moon Sub Choi
language : en
Publisher: Springer Nature
Release Date : 2021-03-08
Fintech With Artificial Intelligence Big Data And Blockchain written by Paul Moon Sub Choi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-08 with Technology & Engineering categories.
This book introduces readers to recent advancements in financial technologies. The contents cover some of the state-of-the-art fields in financial technology, practice, and research associated with artificial intelligence, big data, and blockchain—all of which are transforming the nature of how products and services are designed and delivered, making less adaptable institutions fast become obsolete. The book provides the fundamental framework, research insights, and empirical evidence in the efficacy of these new technologies, employing practical and academic approaches to help professionals and academics reach innovative solutions and grow competitive strengths.
Adventures In Financial Data Science The Empirical Properties Of Financial And Economic Data Second Edition
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Author : Graham L Giller
language : en
Publisher: World Scientific
Release Date : 2022-06-27
Adventures In Financial Data Science The Empirical Properties Of Financial And Economic Data Second Edition written by Graham L Giller and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-27 with Business & Economics categories.
This book provides insights into the true nature of financial and economic data, and is a practical guide on how to analyze a variety of data sources. The focus of the book is on finance and economics, but it also illustrates the use of quantitative analysis and data science in many different areas. Lastly, the book includes practical information on how to store and process data and provides a framework for data driven reasoning about the world.The book begins with entertaining tales from Graham Giller's career in finance, starting with speculating in UK government bonds at the Oxford Post Office, accidentally creating a global instant messaging system that went 'viral' before anybody knew what that meant, on being the person who forgot to hit 'enter' to run a hundred-million dollar statistical arbitrage system, what he decoded from his brief time spent with Jim Simons, and giving Michael Bloomberg a tutorial on Granger Causality.The majority of the content is a narrative of analytic work done on financial, economics, and alternative data, structured around both Dr Giller's professional career and some of the things that just interested him. The goal is to stimulate interest in predictive methods, to give accurate characterizations of the true properties of financial, economic and alternative data, and to share what Richard Feynman described as 'The Pleasure of Finding Things Out.'
Big Data For Twenty First Century Economic Statistics
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Author : Katharine G. Abraham
language : en
Publisher: University of Chicago Press
Release Date : 2022-03-11
Big Data For Twenty First Century Economic Statistics written by Katharine G. Abraham and has been published by University of Chicago Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-11 with Business & Economics categories.
Introduction.Big data for twenty-first-century economic statistics: the future is now /Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro --Toward comprehensive use of big data in economic statistics.Reengineering key national economic indicators /Gabriel Ehrlich, John Haltiwanger, Ron S. Jarmin, David Johnson, and Matthew D. Shapiro ;Big data in the US consumer price index: experiences and plans /Crystal G. Konny, Brendan K. Williams, and David M. Friedman ;Improving retail trade data products using alternative data sources /Rebecca J. Hutchinson ;From transaction data to economic statistics: constructing real-time, high-frequency, geographic measures of consumer spending /Aditya Aladangady, Shifrah Aron-Dine, Wendy Dunn, Laura Feiveson, Paul Lengermann, and Claudia Sahm ;Improving the accuracy of economic measurement with multiple data sources: the case of payroll employment data /Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz --Uses of big data for classification.Transforming naturally occurring text data into economic statistics: the case of online job vacancy postings /Arthur Turrell, Bradley Speigner, Jyldyz Djumalieva, David Copple, and James Thurgood ;Automating response evaluation for franchising questions on the 2017 economic census /Joseph Staudt, Yifang Wei, Lisa Singh, Shawn Klimek, J. Bradford Jensen, and Andrew Baer ;Using public data to generate industrial classification codes /John Cuffe, Sudip Bhattacharjee, Ugochukwu Etudo, Justin C. Smith, Nevada Basdeo, Nathaniel Burbank, and Shawn R. Roberts --Uses of big data for sectoral measurement.Nowcasting the local economy: using Yelp data to measure economic activity /Edward L. Glaeser, Hyunjin Kim, and Michael Luca ;Unit values for import and export price indexes: a proof of concept /Don A. Fast and Susan E. Fleck ;Quantifying productivity growth in the delivery of important episodes of care within the Medicare program using insurance claims and administrative data /John A. Romley, Abe Dunn, Dana Goldman, and Neeraj Sood ;Valuing housing services in the era of big data: a user cost approach leveraging Zillow microdata /Marina Gindelsky, Jeremy G. Moulton, and Scott A. Wentland --Methodological challenges and advances.Off to the races: a comparison of machine learning and alternative data for predicting economic indicators /Jeffrey C. Chen, Abe Dunn, Kyle Hood, Alexander Driessen, and Andrea Batch ;A machine learning analysis of seasonal and cyclical sales in weekly scanner data /Rishab Guha and Serena Ng ;Estimating the benefits of new products /W. Erwin Diewert and Robert C. Feenstra.
Alternative Data And Artificial Intelligence Techniques
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Author : Qingquan Tony Zhang
language : en
Publisher: Springer Nature
Release Date : 2022-10-31
Alternative Data And Artificial Intelligence Techniques written by Qingquan Tony Zhang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-31 with Business & Economics categories.
This book introduces a state-of-art approach in evaluating portfolio management and risk based on artificial intelligence and alternative data. The book covers a textual analysis of news and social media, information extraction from GPS and IoTs data, and risk predictions based on small transaction data, etc. The book summarizes and introduces the advancement in each area and highlights the machine learning and deep learning techniques utilized to achieve the goals. As a complement, it also illustrates examples on how to leverage the python package to visualize and analyze the alternative datasets, and will be of interest to academics, researchers, and students of risk evaluation, risk management, data, AI, and financial innovation.
Outside Insight
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Author : Jorn Lyseggen
language : en
Publisher: Penguin UK
Release Date : 2017-10-12
Outside Insight written by Jorn Lyseggen and has been published by Penguin UK this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-12 with Business & Economics categories.
Is your business looking out? The world today is drowning in data. There is a treasure trove of valuable and underutilized insights that can be gleaned from information companies and people leave behind on the internet - our 'digital breadcrumbs' - from job postings, to online news, social media, online ad spend, patent applications and more. As a result, we're at the cusp of a major shift in the way businesses are managed and governed - moving from a focus solely on lagging, internal data, toward analyses that also encompass industry-wide, external data to paint a more complete picture of a brand's opportunities and threats and uncover forward-looking insights, in real time. Tomorrow's most successful brands are already embracing Outside Insight, benefitting from an information advantage while their competition is left behind. Drawing on practical examples of transformative, data-led decisions made by brands like Apple, Facebook, Barack Obama and many more, in Outside Insight, Meltwater CEO Jorn Lyseggen illustrates the future of corporate decision-making and offers a detailed plan for business leaders to implement Outside Insight thinking into their company mindset and processes.
Big Data Science In Finance
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Author : Irene Aldridge
language : en
Publisher: John Wiley & Sons
Release Date : 2021-01-08
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 2021-01-08 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.