03773nam a2200421Ia 450000100070000000500170000700800410002401000170006502000290008202000260011102000300013704000280016704100080019504200080020305000240021108200240023508400450025910000270030424501570033126400440048830000650053233600080059733700160060533800190062150400510064050506750069152014600136665000400282665000610286665000520292765000620297965000310304165000540307265000530312665500350317971000160321485601210323033382320170126101534.0140929s2015    nyua     b    001 0 eng    a  2014028408  z9781137354075 (hardback)  z1137354070 (hardback)  a978117437471 (electronic)  aDLCbengcDLCerdadDLC  aspa  apcc00aHG4661b.G46 2015eb00a332.640285/5133223  aBUS017000aBUS027000aBUS0280002bisacsh1 aGeorgakopoulos, Harry.10aQuantitative trading with Rh[electronic resource]bunderstanding mathematical and computational tools from a quant's perspectivecHarry Georgakopoulos. 1aNew York, NYbPalgrave Macmillanc2015.  aone online resource (xiii, 272 pages )billustrationsc25 cm  btxt  bn2rdamedia  bnc2rdacarrier  aIncludes bibliographical references and index.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.  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. "--zProvided by publisher. 0aStocksxMathematical models.2Local 7aBUSINESS & ECONOMICS / Foreign Exchange.2bisacsh2Local 7aBUSINESS & ECONOMICS / Finance.2bisacsh2Local 7aBUSINESS & ECONOMICS / Corporate Finance.2bisacsh2Local 0aCommodity exchanges2Local 0aCorporations.xFinancexComputer programs.2Local 0aInvestment AnalysisxMathematical models.2Local07aElectronic books2local2Local2 aEbrary inc.40uhttp://site.ebrary.com/lib/pucpr/docDetail.action?docID=110319203ebraryzPresione para acceder el libro en línea.