000 03804cam a2200397 i 4500
001 18318790
005 20230215020016.0
008 140929s2015 nyua b 001 0 eng
010 _a 2014028408
020 _a9781137354075
040 _aDLC
_beng
_cDLC
_erda
_dDLC
042 _apcc
050 0 0 _aHG4661
_b.G46 2015
084 _aBUS017000
_aBUS027000
_aBUS028000
_2bisacsh
100 1 _aGeorgakopoulos, Harry
_931394
245 1 0 _aQuantitative trading with R
_bunderstanding mathematical and computational tools from a quant's perspective
260 _aNew York
_bPalgrave Macmillian
_c2015
504 _aIncludes bibliographical references and index.
505 8 _aMachine 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.
520 _a"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. "--
650 0 _aStocks
_xMathematical models.
_931395
650 0 _aInvestment analysis
_xMathematical models.
_931396
650 0 _aCorporations
_xFinance
_xComputer programs.
_931397
650 0 _aCommodity exchanges.
_91084
856 4 2 _3Cover image
_uhttp://www.netread.com/jcusers2/bk1388/075/9781137354075/image/lgcover.9781137354075.jpg
856 4 2 _3Contributor biographical information
_uhttp://www.loc.gov/catdir/enhancements/fy1413/2014028408-b.html
856 4 2 _3Publisher description
_uhttp://www.loc.gov/catdir/enhancements/fy1413/2014028408-d.html
856 4 1 _3Table of contents only
_uhttp://www.loc.gov/catdir/enhancements/fy1413/2014028408-t.html
906 _a7
_bcbc
_corignew
_d1
_eecip
_f20
_gy-gencatlg
999 _c215045
_d215045