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.

The Book of Alternative Data

The Book of Alternative Data
Author: Alexander Denev
Publisher: John Wiley & Sons
Total Pages: 416
Release: 2020-06-29
Genre: Business & Economics
ISBN: 1119601800
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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.

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

The Only Guide to Alternative Investments You'll Ever Need

The Only Guide to Alternative Investments You'll Ever Need
Author: Larry E. Swedroe
Publisher: John Wiley and Sons
Total Pages: 238
Release: 2010-05-13
Genre: Business & Economics
ISBN: 0470885335
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The rewards of carefully chosen alternative investments can be great. But many investors don’t know enough about unfamiliar investments to make wise choices. For that reason, financial advisers Larry Swedroe and Jared Kizer designed this book to bring investors up to speed on the twenty most popular alternative investments: Real estate, Inflation-protected securities, Commodities, International equities, Fixed annuities, Stable-value funds, High-yield (junk) bonds, Private equity (venture capital), Covered calls, Socially responsible mutual funds, Precious metals equities, Preferred stocks, Convertible bonds, Emerging market bonds, Hedge funds, Leveraged buyouts, Variable annuities, Equity-indexed annuities, Structured investment products, Leveraged funds The authors describe how the investments work, the pros and cons of each, which to consider, which to avoid, and how to get started. Swedroe and Kizer evaluate each investment in terms of: Expected returns Volatility Distribution of returns Diversification potential Fees Trading and operating expenses Liquidity Tax efficiency Account location Role in an asset-allocation program Any investor who is considering or just curious about investment opportunities outside the traditional world of stocks, bonds, and bank certificates of deposit would be well-advised to read this book.

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.

The Little Book of Alternative Investments

The Little Book of Alternative Investments
Author: Ben Stein
Publisher: John Wiley & Sons
Total Pages: 288
Release: 2011-02-25
Genre: Business & Economics
ISBN: 1118075269
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Praise For THE LITTLE BOOK OF ALTERNATIVE INVESTMENTS "Ben and Phil have done it again. Another lucid, insightful book, designed to enhance your wealth! In today's stock-addled cult of equities, there is a gaping hole in most investors' portfolios...the whole panoply of alternative investments that can simultaneously help us cut our risk, better hedge our inflation risk, and boost our return. This Little Book is filled with big ideas on how to make these markets and strategies a treasured part of our investing toolkit." —Robert Arnott, Chairman, Research Affiliates "I have been reading Ben Stein for thirty-five years and Phil DeMuth since he joined up with Ben ten years ago. They do solid work, and this latest is no exception." —Jim Rogers, author of A Gift to My Children "If anyone can make hedge funds sexy, Stein and DeMuth can, and they've done it with style in this engaging, instructive, and tasteful how-to guide for investing in alternatives. But you should read this Kama Sutra of investment manuals not just for the thrills, but also to learn how to avoid the hazards of promiscuous and unprotected investing." —Andrew Lo, Professor and Director, MIT Laboratory for Financial Engineering

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.

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.

Big Data and Machine Learning in Quantitative Investment

Big Data and Machine Learning in Quantitative Investment
Author: Tony Guida
Publisher: John Wiley & Sons
Total Pages: 308
Release: 2019-03-25
Genre: Business & Economics
ISBN: 1119522196
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Get to know the ‘why’ and ‘how’ of machine learning and big data in quantitative investment Big Data and Machine Learning in Quantitative Investment is not just about demonstrating the maths or the coding. Instead, it’s a book by practitioners for practitioners, covering the questions of why and how of applying machine learning and big data to quantitative finance. The book is split into 13 chapters, each of which is written by a different author on a specific case. The chapters are ordered according to the level of complexity; beginning with the big picture and taxonomy, moving onto practical applications of machine learning and finally finishing with innovative approaches using deep learning. • Gain a solid reason to use machine learning • Frame your question using financial markets laws • Know your data • Understand how machine learning is becoming ever more sophisticated Machine learning and big data are not a magical solution, but appropriately applied, they are extremely effective tools for quantitative investment — and this book shows you how.

Big Data Science in Finance

Big Data Science in Finance
Author: Irene Aldridge
Publisher: John Wiley & Sons
Total Pages: 336
Release: 2021-01-08
Genre: Computers
ISBN: 1119602971
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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.