Handbook of Alternative Data in Finance, Volume I (CRC Press/OptiRis... Hardback

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Item specifics

Condition
Like New: A book that looks new but has been read. Cover has no visible wear, and the dust jacket ...
ISBN
1032276487
EAN
9781032276489
Date of Publication
2023-07-12
Release Title
Handbook of Alternative Data in Finance, Volume I (CRC Press/O...
Artist
various
Brand
N/A
Colour
N/A
Book Title
Handbook of Alternative Data in Finance, Volume I (CRC Press/O...
Subject Area
Mathematics, Business & Economics
Publication Name
Handbook of Alternative Data in Finance, Volume I
Publisher
CRC Press LLC
Item Length
10 in
Subject
Finance / Financial Engineering, Applied
Publication Year
2023
Series
Crc Press/Optirisk Finance Ser.
Type
Textbook
Format
Hardcover
Language
English
Author
Christina Erlwein-Sayer
Item Width
7 in
Number of Pages
576 Pages

About this product

Product Identifiers

Publisher
CRC Press LLC
ISBN-10
1032276487
ISBN-13
9781032276489
eBay Product ID (ePID)
11060715422

Product Key Features

Number of Pages
576 Pages
Language
English
Publication Name
Handbook of Alternative Data in Finance, Volume I
Subject
Finance / Financial Engineering, Applied
Publication Year
2023
Type
Textbook
Subject Area
Mathematics, Business & Economics
Author
Christina Erlwein-Sayer
Series
Crc Press/Optirisk Finance Ser.
Format
Hardcover

Dimensions

Item Length
10 in
Item Width
7 in

Additional Product Features

Intended Audience
Trade
LCCN
2022-060251
Dewey Edition
23
Reviews
"Alternative data has become a hot topic in finance. New kinds of data, new data sources, and of course new tools for processing such data offer the possibility of new and previously unsuspected signals. In short alternative data lead to the promise of enhanced predictive power. But such advance does not come without its challenges - in terms of the quality of the data, the length of its history, reliable data capture, the development of appropriate statistical, AI, machine learning, and data mining tools, and, of course, the ethical challenges in the face of increasingly tough data protection regimes. Gautam Mitra and his colleagues have put together a superb collection of chapters discussing these topics, and more, to show how alternative data, used with care and expertise, can reveal the bigger picture." - Professor David J. Hand, Emeritus Professor of Mathematics and Senior Research Investigator, Imperial College, London "Digital capital is now so important that it can rightly be viewed as a factor of production, especially in the financial sector. This handbook does for the field of alternative data what vendors of alternative data do for data itself; and that is to provide structure, filter noise, and bring clarity. It is an indispensable work which every financial professional can consult, be it for an overview of the field or for specific details about alternative data." - Professor Hersh Shefrin, Mario L. Belotti Professor of Finance, Santa Clara University An impressive and timely contribution to the fast developing discipline of data driven decisions in the trading and management of financial risk. Automated data collection, organization, and dissemination is part and parcel of Data Science and the Handbook covers the current breadth of these activities, their risks, rewards, and costs. A welcome addition to the landscape of quantitative finance. -Professor Dilip Madan, Professor of Finance, Robert H. Smith School of Business"The Handbook of Alternative Data in Finance is the most comprehensive guide to alternative data I have seen. It could be called the Encyclopaedia of Alternative Data. It belongs to the desktop, not the bookshelf, of every investor." - Ernest Chan, Respected Academic, Author, Practicing Fund Manager, Entrepreneur and Founder of PredictNow.AI "Professor Gautam Mitra and his team unpack the topic of alternative data in finance, an ambitious endeavor given the fast-expanding nature of this new and exciting space. Alternative data powered by Natural Language Processing and Machine Learning has emerged as a new source of insights that can help investors make more informed decisions, stay ahead of competition and mitigate emerging risks. This handbook provides a strong validation of the substantial added value that alternative data brings. It also helps promote the idea that data driven decisions are better and more sustainable - something we, at RavenPack, firmly believe." - Armando Gonzalez, CEO and Founder of RavenPack "As the 1 st Duke of Marlborough, John Churchill, wrote in 1715: ''No war can be conducted successfully without early and good intelligence.'' The same can be said for successful trading. In that light, the Handbook of Alternative Data in Finance contains vital insights about how to gather and use alternative data --in short, intelligence --to facilitate successful trading." - Professor Steve H. Hanke, Professor of Applied Economics, The Johns Hopkins University, Baltimore, USA " The Handbook of Alternative Data in Finance is cutting edge and it bridges a huge gap in the representative studies on emerging areas of finance where alternative data can be profitably utilised for better informed decisions. The practical insights in the book would come very handy to both investors and researchers who look for fresh ideas." - Ashok Banerjee, Director, Indian Institute of Management Udaipur, Formerly Dean, and Faculty-in-charge of the Finance Lab at Indian Institute of Management Calcutta
Illustrated
Yes
Dewey Decimal
332.028541
Synopsis
This book motivates and challenges the reader to explore and apply Alternative Data in finance. It 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., 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.
LC Classification Number
HG101.H34 2023

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