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Adventures in Financial Data Science.Graham Giller

Adventures-in-Financial.pdf
ISBN:9781666203851 |430 pages |11 Mb

• Adventures in Financial Data Science
• Graham Giller
• Page:430
• Format: pdf, ePub, fb2, mobi
• ISBN:9781666203851
• Publisher:Barnes & Noble Press

Download Adventures in Financial Data Science

Ebooks for mobileAdventures in Financial Data Science9781666203851 byGraham Giller

Overview

Graham Giller is one of Wall Street's original data scientists. Starting his career at Morgan Stanley in the UK, he was an early member of Peter Muller's famous PDT group and went on to run his own investment firm. He was Bloomberg LP's original data science hire and set up the data science team in the Global Data division there. He them moved to J.P. Morgan to take the role of Chief Data Scientist, New Product Development, and was subsequently Head of Data Science Research at J.P. Morgan and Head of Primary Research at Deutsche Bank. The book begins with entertaining tales from his career in finance, starting with speculating in UK government bonds at 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 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, economic, and alternative data, structured around both Graham'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." When viewing a draft of the manuscript, ex-Morgan Stanley colleague remarked "I might pay you quite a lot to not publish —that's a lot of insight into what works and what doesn't."

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