Quantitative trading with R : understanding mathematical and computational tools from a quant's perspective
| 000 | 00000cam u2200205 a 4500 | |
| 001 | 000045825262 | |
| 005 | 20251113111813 | |
| 008 | 150302s2015 nyua b 001 0 eng d | |
| 010 | ▼a 2014028408 | |
| 020 | ▼a 9781137354075 (hardback) | |
| 020 | ▼a 1137354070 () | |
| 035 | ▼a (KERIS)REF000017559882 | |
| 040 | ▼a DLC ▼b eng ▼c DLC ▼d DLC ▼e rda ▼d 211009 | |
| 050 | 0 0 | ▼a HG4661 ▼b .G46 2015 |
| 082 | 0 0 | ▼a 332.640285/5133 ▼2 23 |
| 084 | ▼a 332.640285 ▼2 DDCK | |
| 090 | ▼a 332.640285 ▼b G346q | |
| 100 | 1 | ▼a Georgakopoulos, Harry ▼0 AUTH(211009)175597. |
| 245 | 1 0 | ▼a Quantitative trading with R : ▼b understanding mathematical and computational tools from a quant's perspective / ▼c Harry Georgakopoulos. |
| 260 | ▼a New York : ▼b Palgrave Macmillan, ▼c 2015. | |
| 300 | ▼a xiii, 272 p. : ▼b ill. ; ▼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. | |
| 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. | |
| 650 | 0 | ▼a Stocks ▼x Mathematical models. |
| 650 | 0 | ▼a Investment analysis ▼x Mathematical models. |
| 650 | 0 | ▼a Corporations ▼x Finance ▼x Computer programs. |
| 650 | 0 | ▼a Commodity exchanges. |
| 945 | ▼a KLPA |
소장정보
| No. | 소장처 | 청구기호 | 등록번호 | 도서상태 | 반납예정일 | 예약 | 서비스 |
|---|---|---|---|---|---|---|---|
| No. 1 | 소장처 중앙도서관/서고6층/ | 청구기호 332.640285 G346q | 등록번호 111731654 (5회 대출) | 도서상태 대출가능 | 반납예정일 | 예약 | 서비스 |
컨텐츠정보
책소개
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.
정보제공 :
저자소개
해리 조가코퓰러스(지은이)
로욜라(Loyola) 대학교의 계량 금융 담당 교수이자 Blue Fire Capital, LLC의 퀀트 트레이더다. 2007년부터 일리노이 주 시카코에서 고빈도 매매 분야의 퀀트 트레이더로 일하고 있다. 이전에는 모토로라(Motorola)와 앤드류(Andrew Corp.)에서 전자공학자로 일하며 3G 모바일용 마이크로파 송수신기를 만들었고, 밀리만(Milliman)에서 퀀트 컨설턴트로 일했다. 주된 연구 분야는 선물, 주식의 고빈도 자동 매매 시스템 개발이다. 시카코 대학교에서 금융 수학 박사 학위를 받았다.
목차
1 An Overview 2 Tools of the Trade 3 Working with Data 4 Basic Statistics and Probability 5 Intermediate Statistics and Probability 6 Spreads, Betas and Risk 7 Backtesting with Quantstrat 8 High-Frequency Data 9 Options 10 Optimization
정보제공 :