Automated Trading with R: Quantitative Research and Platform Development

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9781484221778: Automated Trading with R: Quantitative Research and Platform Development

Learn 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 automated trading, starting with its mathematics and moving to its computation and execution. You 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 traders
  • Offer an understanding of the internal mechanisms of an automated trading system
  • Standardize discussion and notation of real-world strategy optimization problems

What You Will Learn

  • Understand machine-learning criteria for statistical validity in the context of time-series
  • Optimize strategies, generate real-time trading decisions, and minimize computation time while programming an automated strategy in R and using its package library
  • Best simulate strategy performance in its specific use case to derive accurate performance estimates
  • Understand critical real-world variables pertaining to portfolio management and performance assessment, including latency, drawdowns, varying trade size, portfolio growth, and penalization of unused capital

Who This Book Is For

Traders/practitioners at the retail or small fund level with at least an undergraduate background in finance or computer science; graduate level finance or data science students

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From the Back Cover:

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 traders
  • Offer an understanding of the internal mechanisms of an automated trading system
  • Standardize 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 library
  • How to best simulate strategy performance in its specific use case to derive accurate performance estimates
  • Important optimization criteria for statistical validity in the context of a time series
  • An 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

About the Author:

Chris Conlan began his career as an independent data scientist specializing in trading algorithms. He attended the University of Virginia where he completed his undergraduate statistics coursework in three semesters. During his time at UVA, he secured initial fundraising for a privately held high-frequency forex group as president and chief trading strategist. He is currently managing the development of private technology companies in high-frequency forex, machine vision, and dynamic reporting.

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Chris Conlan
Editorial: aPress, United States (2016)
ISBN 10: 148422177X ISBN 13: 9781484221778
Nuevos Paperback Primera edición Cantidad: 10
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The Book Depository
(London, Reino Unido)
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Descripción aPress, United States, 2016. Paperback. Estado de conservación: New. 1st ed.. Language: English . Brand New Book. Learn 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 automated trading, starting with its mathematics and moving to its computation and execution. You 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 problemsWhat You Will LearnUnderstand machine-learning criteria for statistical validity in the context of time-seriesOptimize strategies, generate real-time trading decisions, and minimize computation time while programming an automated strategy in R and using its package libraryBest simulate strategy performance in its specific use case to derive accurate performance estimatesUnderstand critical real-world variables pertaining to portfolio management and performance assessment, including latency, drawdowns, varying trade size, portfolio growth, and penalization of unused capitalWho This Book Is ForTraders/practitioners at the retail or small fund level with at least an undergraduate background in finance or computer science; graduate level finance or data science students. Nº de ref. de la librería SPR9781484221778

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Chris Conlan
Editorial: aPress, United States (2016)
ISBN 10: 148422177X ISBN 13: 9781484221778
Nuevos Paperback Primera edición Cantidad: 10
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The Book Depository US
(London, Reino Unido)
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Descripción aPress, United States, 2016. Paperback. Estado de conservación: New. 1st ed.. Language: English . Brand New Book. Learn 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 automated trading, starting with its mathematics and moving to its computation and execution. You 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 problemsWhat You Will LearnUnderstand machine-learning criteria for statistical validity in the context of time-seriesOptimize strategies, generate real-time trading decisions, and minimize computation time while programming an automated strategy in R and using its package libraryBest simulate strategy performance in its specific use case to derive accurate performance estimatesUnderstand critical real-world variables pertaining to portfolio management and performance assessment, including latency, drawdowns, varying trade size, portfolio growth, and penalization of unused capitalWho This Book Is ForTraders/practitioners at the retail or small fund level with at least an undergraduate background in finance or computer science; graduate level finance or data science students. Nº de ref. de la librería SPR9781484221778

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Chris Conlan
Editorial: Apress 2016-09-29, New York (2016)
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Descripción Apress 2016-09-29, New York, 2016. paperback. Estado de conservación: New. Nº de ref. de la librería 9781484221778

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Descripción Apress 9/29/2016, 2016. Paperback or Softback. Estado de conservación: New. Automated Trading with R: Quantitative Research and Platform Development. Book. Nº de ref. de la librería BBS-9781484221778

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Descripción Apress, 2016. Paperback. Estado de conservación: NEW. 9781484221778 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. For all enquiries, please contact Herb Tandree Philosophy Books directly - customer service is our primary goal. Nº de ref. de la librería HTANDREE01118588

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