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Quantitative Trading with R offers readers a glimpse into the daily activities of quants/traders who deal with financial data analysis and the formulation of model-driven trading strategies.
Based on the author's own experience as a quant, lecturer, and high-frequency trader, this book illuminates many of the problems that these professionals encounter on a daily basis. Answers to some of the more relevant questions are provided, and the easy-to-follow examples show the reader how to build functional R computer code in the process.
Georgakopoulos has written an invaluable introductory work for students, researchers, and practitioners alike. Anyone interested in applying programming, mathematical, and financial concepts to the creation and analysis of simple trading strategies will benefit from the lessons provided in this book. Accessible yet comprehensive, Quantitative Trading with R focuses on helping readers achieve practical competency in utilizing the popular R language for data exploration and strategy development.
Engaging and straightforward in his explanations, Georgakopoulos outlines basic trading concepts and walks the reader through the necessary math, data analysis, finance, and programming that quants/traders rely on. To increase retention and impact, individual case studies are split up into smaller modules. Chapters contain a balanced mix of mathematics, finance, and programming theory, and cover such diverse topics such as statistics, data analysis, time series manipulation, back-testing, and R-programming.
In Quantitative Trading with R, Georgakopoulos offers up a highly readable yet in-depth guidebook. Readers will emerge better acquainted with the R language and the relevant packages that are used by academics and practitioners in the quantitative trading realm.
Harry Georgakopoulos is Professor of Quantitative Finance at Loyola University and Quantitative Trader at XR Trading, LLC. He has been working as a quantitative trader in Chicago, IL in the high frequency space since 2007. Prior to that, he was employed at Motorola and Andrew Corp. as an Electrical Engineer, where he designed and tested microwave transceivers for 3G mobile technologies, as well as at Milliman where he served as a Quantitative Financial Consultant. His main area of expertise is in the research and development of high-frequency, automated trading systems for futures and equities. He received his PhD in Financial Mathematics from The University of Chicago.
Table of Contents
1. Introduction 2. What Do Traders Do? 3. What Tools Do Traders Use? 4. A Sample Trading Strategy 5. Tools That We Need to Implement a Trading Strategy 6. What is R? (History and Basic Instructions) 7. Datatypes in R 8. Functions in R 9. Linear Algebra 10. Statistics 11. Probability 12. What is Risk 13. Where to Get Financial Data 14. How to Analyze Financial Data 15. Time Series Analysis 16. Regression Analysis 17. Monte Carlo Analysis 18. Formulating a Strategy 19. Backtesting a Strategy 20. Validating a Strategy 21. Presentation of Results 22. Advanced Concepts