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