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

By:

Georgakopoulos, Harry

Material type: Text

TextPublication details: New York Palgrave Macmillian 2015Description: xiii,272p. illustrations 25 cmISBN:

9781137354075

Subject(s):

DDC classification:

332.6402855133 23 GE-Q

LOC classification:

HG4661 .G46 2015

Other classification:

BUS017000 | BUS027000 | BUS028000

Online resources:

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.

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. "--

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Holdings
Item type	Home library	Collection	Shelving location	Call number	Materials specified	Status	Date due	Barcode
Print	OPJGU Sonepat- Campus	General Books	Main Library	332.6402855133 GE-Q (Browse shelf(Opens below))		Available		132680

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Previous	332.64 HA-T Trading & exchanges market microstructure for practitioners	332.64 LO-A Adaptive Markets Financial Evolution at the Speed of Thought	332.64019 KI-M Mental strategies of top traders the psychological determinants of trading success	332.6402855133 GE-Q Quantitative trading with R understanding mathematical and computational tools from a quant's perspective	332.640973 SC-M Market wizards interviews with top traders	332.640973 SC-N New market wizards conversations with America's top traders	332.640973 SC-N New market wizards conversations with America's top traders	Next

Includes bibliographical references and index.

"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. "--

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