1st Edition

Coronavirus News, Markets and AI
The COVID-19 Diaries




  • Available for pre-order. Item will ship after December 23, 2020
ISBN 9780367687724
December 23, 2020 Forthcoming by Routledge India
260 Pages 85 B/W Illustrations

USD $51.95

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Book Description

Coronavirus News, Markets and AI explores the analysis of unstructured data from coronavirus related news and the underlying sentiment during its real-time impact on the world and on global financial markets, in particular. In an age where information, both real and fake, travels in the blink of an eye and significantly alters market sentiment daily, this book is a blow by blow account of economic impact of the COVID-19 pandemic.

The volume:  

— Details how AI driven machines capture, analyse and score relevant on-ground news sentiment to analyse the dynamics of market sentiment, how markets react to good or bad news across ‘short term’ and ‘long term’;

— Investigates what have been the most prevalent news sentiment during the pandemic, and its linkages to crude oil prices, high profile cases, impact of local news, and even the impact of Trump’s policies;

— Discusses the impact on what people think and discuss, how the COVID-19 crisis differs from the Global Financial Crisis of 2008, the unprecedented disruptions in supply chains and our daily lives;

— Showcases how easy accessibility to big data methods, cloud computing, and computational methods and the universal applicability of these tool to any topic can help analyse extract the related news sentiment in allied fields.

Accessible, nuanced and insightful, this book will be invaluable for business professionals, bankers, media professionals, traders, investors, and investment consultants. It will also be of great interest to scholars and researchers of economics, commerce, science and technology studies, computer science, media and culture studies, public policy and digital humanities.

Table of Contents

About this book. Introduction. Part I: The Method 1. How to Read this Book? 2. Reading Coronavirus News 3. Sentiment Analysis, Big Data and AI 4. Unstructured Data. How to tame the beast? Part II: The Results 5. Ebbing in May. ‘Are we celebrating too early?’ 6. The Deadly April. ‘Blame Game and Search for a Coronavirus Vaccine’ 7. Coronavirus goes Global in March. ‘Oops…It is getting serious’ 8. Build-up in February. ‘Come on, Don’t worry too much’ Part III: The Samples 9. Politics, Conspiracy Theories and Religion 10. Coronavirus Pandemic’s Economic Impact 11. Disease, Devastation and Hope 12. The Human Nature and Impact on Normal Life 13. Bizarre, Funny and Fake News Part IV: The Inference 14. Country Sentiment for Coronavirus News 15. COVID-19 has turned the world upside down 16. What is seen more often in Coronavirus News? 17. How do we use Sentiment Analysis. Case Study 18. Conclusion

 

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Author(s)

Biography

Pankaj Sharma is a partner at EMAlpha, a data analytics and investment management firm focused on making Emerging Markets (EMs) accessible to global investors and unlocking EM investing using machines. EMAlpha’s focus is on Unstructured Data as the EMs are particularly susceptible to swings in news flow driven investor sentiment. Pankaj has 20 years of diverse work experience in various leadership roles with global investment banks, Indian equity brokerages, state-owned enterprises and start-ups. Earlier, he was a ranked equity analyst and tracked multiple sectors at UBS, Citi and JP Morgan. Pankaj has also been a regular contributor to print and electronic media. For Routledge, he has so far co-authored the following two titles; Artificial Intelligence: Evolution, Ethics and Public Policy and Big Data: A Beginner's Introduction. Pankaj published his first two books in 2017 and they were: Demonetization: Modi’s Political Masterstroke and 2019: Will Modi Win? This was followed by Rafale, Raga, Reuniting Forces for 2019 and The Anatomy of an Indian General Election. Pankaj is an engineer from IIT Kharagpur, India, with an MBA from the Faculty of Management Studies, University of Delhi, India.