Automated Trading with R Automated Trading with R

Automated Trading with R

Quantitative Research and Platform Development

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출판사 설명

All the tools you need are provided in this book to trade algorithmically with your existing brokerage, from data management, to strategy optimization, to order execution, using free and publicly available data. Connect to your brokerage’s API, and the source code is plug-and-play.

Automated Trading with R explains the broad topic of automated trading, starting with its mathematics and moving to its computation and execution. Readers will gain a unique insight into the mechanics and computational considerations taken in building a back-tester, strategy optimizer, and fully functional trading platform.

The platform built in this book can serve as a complete replacement for commercially available platforms used by retail traders and small funds. Software components are strictly decoupled and easily scalable, providing opportunity to substitute any data source, trading algorithm, or brokerage. This book will:
Provide a flexible alternative to common strategy automation frameworks, like Tradestation, Metatrader, and CQG, to small funds and retail tradersOffer an understanding of the internal mechanisms of an automated trading systemStandardize discussion and notation of real-world strategy optimization problems
What You’ll Learn:
To optimize strategies, generate real-time trading decisions, and minimize computation time while programming an automated strategy in R and using its package libraryHow to best simulate strategy performance in its specific use case to derive accurate performance estimatesImportant optimization criteria for statistical validity in the context of a time seriesAn understanding of critical real-world variables pertaining to portfolio management and performance assessment, including latency, drawdowns, varying trade size, portfolio growth, and penalization of unused capital

장르
컴퓨터 및 인터넷
출시일
2016년
9월 28일
언어
EN
영어
길이
230
페이지
출판사
Apress
판매자
Springer Nature B.V.
크기
2.5
MB
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