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04122aam a2200457 i 4500 001 DABF1EAC6B5611E69AFE1DDBDAD10320 003 SILO 005 20160826010517 008 140929s2015 nyua b 001 0 eng 010 $a 2014028408 020 $a 1137354070 020 $a 9781137354075 035 $a (OCoLC)885228590 040 $a DLC $e rda $b eng $c DLC $d YDX $d BTCTA $d BDX $d UUM $d YDXCP $d NYP $d CDX $d SILO 042 $a pcc 050 00 $a HG4661 .G46 2015 082 00 $a 332.640285/5133 $2 23 084 $a BUS028000 $a BUS027000 $a BUS028000 $2 bisacsh 100 1 $a Georgakopoulos, Harry, $e author. 245 10 $a Quantitative trading with R : $b understanding mathematical and computational tools from a quant's perspective / $c Harry Georgakopoulos. 250 $a First edition. 264 1 $a New York, NY : $b Palgrave Macmillan, $c 2015. 300 $a xiii, 272 pages : $b illustrations ; $c 25 cm 504 $a Includes bibliographical references and index. 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. "-- $c Provided by publisher. 505 8 $a 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. 650 0 $a Stocks $x Mathematical models. 650 0 $a Investment analysis $x Mathematical models. 650 0 $a Corporations $x Computer programs. $x Computer programs. 650 0 $a Commodity exchanges. 650 7 $a BUSINESS & ECONOMICS / Corporate Finance. $2 bisacsh 650 7 $a BUSINESS & ECONOMICS / Finance. $2 bisacsh 650 7 $a BUSINESS & ECONOMICS / Foreign Exchange. $2 bisacsh 856 42 $3 Cover image $u http://www.netread.com/jcusers2/bk1388/075/9781137354075/image/lgcover.9781137354075.jpg 856 42 $3 Contributor biographical information $u http://catdir.loc.gov/catdir/enhancements/fy1413/2014028408-b.html 856 42 $3 Publisher description $u http://catdir.loc.gov/catdir/enhancements/fy1413/2014028408-d.html 856 41 $3 Table of contents only $u http://catdir.loc.gov/catdir/enhancements/fy1413/2014028408-t.html 941 $a 1 952 $l USUX851 $d 20190502032202.0 956 $a http://locator.silo.lib.ia.us/search.cgi?index_0=id&term_0=DABF1EAC6B5611E69AFE1DDBDAD10320 994 $a 92 $b IWAInitiate Another SILO Locator Search