000 03161cam a22002898a 4500
999 _c26763
_d26763
001 60765
010 _a 2014028408
020 _a9781137354075
020 _a1137354070 ()
040 _aDLC
082 0 0 _a332.640285/5133
100 1 _aGeorgakopoulos, Harry
_949153
245 1 0 _aQuantitative trading with R :
_bunderstanding mathematical and computational tools from a quant's perspective
_cHarry Georgakopoulos
260 _aNew York :
_bPalgrave Macmillan,
_cc2015.
300 _axiii,272 p. ;
_bill. ;
_c26 cm.
505 0 _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
_948826
650 0 _aInvestment analysis
_xMathematical models
_948950
650 0 _aCorporations
_xFinance
_xComputer programs
_938232
650 0 _aCommodity exchanges
_948842
650 7 _aBUSINESS & ECONOMICS / Corporate Finance
_922684
650 7 _aBUSINESS & ECONOMICS / Finance
_9396
650 7 _aBUSINESS & ECONOMICS / Foreign Exchange
_949154
856 4 2 _uhttps://uowd.box.com/s/erf8ef475rmvuebm5wn6m7gtbp6wws1g
_zLocation Map
942 _cREGULAR
_2ddc