The Book of Alternative Data

The Book of Alternative Data
Author: Alexander Denev
Publisher: John Wiley & Sons
Total Pages: 416
Release: 2020-07-21
Genre: Business & Economics
ISBN: 1119601797
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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.

Big Data for Twenty-First-Century Economic Statistics

Big Data for Twenty-First-Century Economic Statistics
Author: Katharine G. Abraham
Publisher: University of Chicago Press
Total Pages: 502
Release: 2022-03-11
Genre: Business & Economics
ISBN: 022680125X
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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

Alternative Data
Author: Mani Mahjouri
Publisher: Wiley
Total Pages: 0
Release: 2024-06-12
Genre: Business & Economics
ISBN: 9781119465003
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Shift the balance of power from company to investor through intensified use of data Alternative Data opens a gateway to the future of investing, using Open Halo technology to provide real-time performance analysis and breathtaking data visualization. Once solely available to the elites, this technology utilizes observational and transactional data covering vast numbers of stocks to analyze and forecast a company’s performance, often months ahead of any official announcement. This book shows you how to leverage this capability to make smarter investment decisions and predict market moves based on much more than conjecture. Imagine if you could access satellite imagery showing that a particular store’s parking lot was always full, correlated with credit card transactions showing a spike in sales, alongside social media analysis indicating an unprecedented rate of content generation from inside the store—what would you do with that information? A month later, when the company announces a breakthrough in sales, you’re ahead of the game. This granular level of analysis is set to become the de facto standard for smart investors, and now is a great time to start getting out in front of the pack. This book takes you inside the datasets and shows you how to turn them into profit. The companion website features interactive videos that reinforce major topics, giving you everything you need to start getting creative with data. Leverage Open Halo technology to visualize highly complex market phenomena Learn how to turn transactional and observational data into smart investing moves Get ahead of the curve by conducting a more granular analysis Forecast performance in real time with systematic evaluation of large swaths of stocks Today’s investors have access to data at an unprecedented scale; failing to leverage that data is like leaving money on the table. Alternative Data is your key guide for getting up and running with next-level visualizations that fuel smart decisions in any market.

Alternate Data Storage Forensics

Alternate Data Storage Forensics
Author: Amber Schroader
Publisher: Elsevier
Total Pages: 337
Release: 2011-04-18
Genre: Computers
ISBN: 008055475X
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Learn to pull "digital fingerprints from alternate data storage (ADS) devices including: iPod, Xbox, digital cameras and more from the cyber sleuths who train the Secret Service, FBI, and Department of Defense in bleeding edge digital forensics techniques. This book sets a new forensic methodology standard for investigators to use.This book begins by describing how alternate data storage devices are used to both move and hide data. From here a series of case studies using bleeding edge forensic analysis tools demonstrate to readers how to perform forensic investigations on a variety of ADS devices including: Apple iPods, Digital Video Recorders, Cameras, Gaming Consoles (Xbox, PS2, and PSP), Bluetooth devices, and more using state of the art tools. Finally, the book takes a look into the future at "not yet every day devices which will soon be common repositories for hiding and moving data for both legitimate and illegitimate purposes. - Authors are undisputed leaders who train the Secret Service, FBI, and Department of Defense - Book presents "one of a kind" bleeding edge information that absolutely can not be found anywhere else - Today the industry has exploded and cyber investigators can be found in almost every field

The AI Book

The AI Book
Author: Ivana Bartoletti
Publisher: John Wiley & Sons
Total Pages: 304
Release: 2020-06-29
Genre: Business & Economics
ISBN: 1119551900
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Written by prominent thought leaders in the global fintech space, The AI Book aggregates diverse expertise into a single, informative volume and explains what artifical intelligence really means and how it can be used across financial services today. Key industry developments are explained in detail, and critical insights from cutting-edge practitioners offer first-hand information and lessons learned. Coverage includes: · Understanding the AI Portfolio: from machine learning to chatbots, to natural language processing (NLP); a deep dive into the Machine Intelligence Landscape; essentials on core technologies, rethinking enterprise, rethinking industries, rethinking humans; quantum computing and next-generation AI · AI experimentation and embedded usage, and the change in business model, value proposition, organisation, customer and co-worker experiences in today’s Financial Services Industry · The future state of financial services and capital markets – what’s next for the real-world implementation of AITech? · The innovating customer – users are not waiting for the financial services industry to work out how AI can re-shape their sector, profitability and competitiveness · Boardroom issues created and magnified by AI trends, including conduct, regulation & oversight in an algo-driven world, cybersecurity, diversity & inclusion, data privacy, the ‘unbundled corporation’ & the future of work, social responsibility, sustainability, and the new leadership imperatives · Ethical considerations of deploying Al solutions and why explainable Al is so important

Handbook of Alternative Data in Finance, Volume I

Handbook of Alternative Data in Finance, Volume I
Author: Gautam Mitra
Publisher: CRC Press
Total Pages: 488
Release: 2023-07-12
Genre: Business & Economics
ISBN: 1000897982
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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

The Book of Alternative Data

The Book of Alternative Data
Author: Alexander Denev
Publisher: John Wiley & Sons
Total Pages: 415
Release: 2020-07-02
Genre: Business & Economics
ISBN: 1119601819
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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.

Data-Driven Investing, + Website

Data-Driven Investing, + Website
Author: Matei Zatreanu
Publisher: Wiley
Total Pages: 0
Release: 2025-04-29
Genre: Business & Economics
ISBN: 9781119429630
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Implement a data-driven investment strategy The investing landscape is increasingly driven by big data and artificial intelligence. For most finance professionals, big data, statistics, and programming are outside their comfort zone. Yet, proficiency in these areas is becoming a prerequisite for successful investing. And while there are plenty of resources on these individual topics, what is missing is a framework for combining these disciplines for investment purposes. Data-Driven Investing shows readers how investment decisions can be made or improved through the use of alternative datasets and inference techniques. The author covers artificial intelligence algorithms, data visualization, and data sourcing to show how these components come together to form a more robust investment strategy. The goal is to help finance professionals prepare for an investing landscape increasingly driven by big data and artificial intelligence. Shows how investing wisdom can be harnessed through science and augmented by data Demonstrates how an augmented investing philosophy promises a deeper understanding of future economic performance Is essential reading for fund managers, research analysts, quantitative investors, data scientists, and general finance professionals Includes a companion website with code, data sets, and videos providing more in-depth information on augmented/data-driven investing This book comes at a time of increasing investor anxiety with lackluster hedge fund performance, which is causing many funds to explore data-driven investing as a possible evolution of their strategies.

Fintech with Artificial Intelligence, Big Data, and Blockchain

Fintech with Artificial Intelligence, Big Data, and Blockchain
Author: Paul Moon Sub Choi
Publisher: Springer Nature
Total Pages: 306
Release: 2021-03-08
Genre: Technology & Engineering
ISBN: 9813361379
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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.

Alternative Data and Artificial Intelligence Techniques

Alternative Data and Artificial Intelligence Techniques
Author: Qingquan Tony Zhang
Publisher: Springer Nature
Total Pages: 340
Release: 2022-10-31
Genre: Business & Economics
ISBN: 3031116127
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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.