Apress | Automated Trading With R (2016 EN)

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  1. Kanka

    Kanka Well-Known Member Loyal User

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    Author: Christopher Conlan
    Full Title: Automated Trading With R: Quantitative Research And Platform Development
    Publisher: Apress; 1st ed. edition (September 29, 2016)
    Year: 2016
    ISBN-13: 9781484221785 (978-1-4842-2178-5), 9781484221778 (978-1-4842-2177-8)
    ISBN-10: 1484221788, 148422177X
    Pages: 205
    Language: English
    Genre: Programming
    File type: EPUB (True), PDF (True)
    Quality: 10/10
    Price: 44.99 €


    This book 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 backtester, strategy optimizer, and fully functional trading platform.

    Automated Trading with R provides automated traders with all the tools they need to trade algorithmically with their existing brokerage, from data management, to strategy optimization, to order execution, using free and publically available data. If your brokerage’s API is supported, the source code is plug-and-play.

    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.


    Learn:
    ✓ Programming an automated strategy in R gives the trader access to R and its package library for optimizing strategies, generating real-time trading decisions, and minimizing computation time.
    ✓ How to best simulate strategy performance in their specific use case to derive accurate performance estimates.
    ✓ Important machine-learning criteria for statistical validity in the context of 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.

    Features:
    ✓ Full source code and step-by-step explanation for a plug-and-play trading platform; the platform can be used in independent simulation, brokerage-assisted simulation, or end-to-end production trading
    ✓ Includes lengthy tables and descriptions of performance metrics, indicators, rule sets, and brokerage plans, helping users get to production quicker
    ✓ Includes performance assessments of popular strategies implemented on multi-asset portfolios, allowing users to swap components to customize, research, and deploy automated strategies

    Who This Book Is For:
    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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    Last edited by a moderator: Mar 8, 2022