图书简介
This book provides insights into the true nature of financial and economic data, and is a practical guide on how to analyze a variety of data sources. The focus of the book is on finance and economics, but it also illustrates the use of quantitative analysis and data science in many different areas. Lastly, the book includes practical information on how to store and process data and provides a framework for data driven reasoning about the world.The book begins with entertaining tales from Graham Giller’s career in finance, starting with speculating in UK government bonds at the 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 his 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, economics, and alternative data, structured around both Dr Giller’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."Key FeaturesA systematic analysis of the properties of financial distributions that are enduringly true, applied both to equity prices and interest ratesA derivation of the optimal portfolio strategy in the presence of leptokurtotic probability distributionsExtensive discussion of the use of many types of "alternative data" in financial and economic contexts, particularly for "nowcasting."
Preface to the Second Edition; Biography and Beginnings; Financial Data; Economic Data and Other Time-Series Analysis; Politics, Schools, Public Health, and Language; Demographics and Survey Research; Coronavirus; Theory; Epilogue; Appendices: How I Store and Process Data; Some of the Data Sources I’ve Used for this Book
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