Research Catalog

Quantitative trading with R : understanding mathematical and computational tools from a quant's perspective

Title

Quantitative trading with R : understanding mathematical and computational tools from a quant's perspective / Harry Georgakopoulos.

Author

Georgakopoulos, Harry

Publication

New York : Palgrave Macmillan, 2015.

Supplementary Content

Items in the Library & Off-site

Filter by

2 Items

Item details
Status	Format	Access	Call Number	Item Location
Available - Can be used on site. Please visit New York Public Library - Check with Staff to submit a request in person.	Text	No restrictions	*R-SIBL HG4661 .G46	Check with Staff
Not available - Please for assistance.	Text			Check with Staff

Holdings

Details

Description

xiii, 272 pages : illustrations; 25 cm

Summary

"Quantitative Trading with R offers readers a winning strategy for devising expertly-crafted and workable trading models using the R open-source programming language. Based on the author's own experience as a professor and high-frequency trader, this book provides a step-by-step approach to understanding complex quantitative finance problems and building functional computer code. This is an introductory work for students, researchers, and practitioners interested in applying statistical-programming, mathematical, and financial concepts to the creation and analysis of simple and practical trading strategies. No prior programming knowledge is assumed on the part of the reader. Georgakopoulos outlines basic trading concepts and walks the reader through the necessary math, data analysis, finance, and programming concepts necessary to successfully implement a strategy. Multiple examples are included throughout the work containing useful computer code that can be applied directly to real-world trading models. Individual case studies are split up into smaller modules for impact and retention. Chapters contain a balanced mix of mathematics, finance, and programming theory, and cover such topics as linear algebra, matrix manipulations, statistics, data analysis, and programming constructs. Upon completion of the book, readers will know how to research, analyze, backtest, and code up a successful trading strategy. "--

Subject

Bibliography (note)

Includes bibliographical references and index.

Contents

Machine generated contents note: -- 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.

Call Number