{"product_id":"automated-trading-with-r-quantitative-research-and-platform-development-paperback","title":"Automated Trading with R: Quantitative Research and Platform Development - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eChris Conlan\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eLearn 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.\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cem\u003eAutomated Trading with R\u003c\/em\u003e 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.\u003c\/p\u003e\u003cp\u003eThe 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: \u003cbr\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eProvide a flexible alternative to common strategy automation frameworks, like Tradestation, Metatrader, and CQG, to small funds and retail traders\u003cbr\u003e\n\u003c\/li\u003e\n\u003cli\u003eOffer an understanding of the internal mechanisms of an automated trading system\u003cbr\u003e\n\u003c\/li\u003e\n\u003cli\u003eStandardize discussion and notation of real-world strategy optimization problems\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eWhat You Will Learn\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eUnderstand machine-learning criteria for statistical validity in the context of time-series\u003c\/li\u003e\n\u003cli\u003eOptimize strategies, generate real-time trading decisions, and minimize computation time while programming an automated strategy in R and using its package library\u003cbr\u003e\n\u003c\/li\u003e\n\u003cli\u003eBest simulate strategy performance in its specific use case to derive accurate performance estimates\u003cbr\u003e\n\u003c\/li\u003e\n\u003cli\u003eUnderstand critical real-world variables pertaining to portfolio management and performance assessment, including latency, drawdowns, varying trade size, portfolio growth, and penalization of unused capital\u003cbr\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eWho This Book Is For\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003eTraders\/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\u003cbr\u003e\u003c\/p\u003e\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eAll 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.\u003c\/p\u003e\u003cp\u003e\u003cem\u003eAutomated Trading with R\u003c\/em\u003e 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.\u003c\/p\u003e\u003cp\u003eThe 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: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eProvide a flexible alternative to common strategy automation frameworks, like Tradestation, Metatrader, and CQG, to small funds and retail traders\u003c\/li\u003eOffer an understanding of the internal mechanisms of an automated trading system\u003cli\u003eStandardize discussion and notation of real-world strategy optimization problems\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eWhat You'll Learn: \u003c\/p\u003e\u003cul\u003eTo optimize strategies, generate real-time trading decisions, and minimize computation time while programming an automated strategy in R and using its package library\u003cli\u003eHow to best simulate strategy performance in its specific use case to derive accurate performance estimates\u003c\/li\u003e\n\u003cli\u003eImportant optimization criteria for statistical validity in the context of a time series\u003c\/li\u003eAn 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\u003c\/ul\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eChris Conlan\u003c\/b\u003e 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.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 205\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.5 x 10 x 7 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e September 29, 2016\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":52492491948339,"sku":"9781484221778","price":93.38,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0300\/5595\/6612\/files\/Q0x6NWdSYUM1ZEQvQ2NZNDRaR3c1dz09.webp?v=1759935508","url":"https:\/\/www.vysn.com\/en-ca\/products\/automated-trading-with-r-quantitative-research-and-platform-development-paperback","provider":"VYSN","version":"1.0","type":"link"}