automated trading with r quantitative research and platform development

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Automated Trading With R

Author : Chris Conlan
ISBN : 9781484221785
Genre : Computers
File Size : 35. 15 MB
Format : PDF
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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

Automated Trading With R

Author : Christopher Conlan
ISBN : 148422177X
Genre : Computers
File Size : 77. 77 MB
Format : PDF, Kindle
Download : 252
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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. The book’s three objectives are: To provide a flexible alternative to common strategy automation frameworks, like Tradestation, Metatrader, and CQG, to small funds and retail traders. To offer an understanding the internal mechanisms of an automated trading system. To standardize discussion and notation of real-world strategy optimization problems. What you’ll 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. 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.

Quantitative Trading With R

Author : Harry Georgakopoulos
ISBN : 9781137437471
Genre : Business & Economics
File Size : 76. 47 MB
Format : PDF, Kindle
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Quantitative Finance with R offers a winning strategy for devising expertly-crafted and workable trading models using the R open source programming language, providing readers with a step-by-step approach to understanding complex quantitative finance problems and building functional computer code.

Building Trading Bots Using Java

Author : Shekhar Varshney
ISBN : 9781484225202
Genre : Computers
File Size : 67. 91 MB
Format : PDF
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Build an automated currency trading bot from scratch with java. In this book, you will learn about the nitty-gritty of automated trading and have a closer look at Java, the Spring Framework, event-driven programming, and other open source APIs, notably Google's Guava API. And of course, development will all be test-driven with unit testing coverage. The central theme of Building Trading Bots Using Java is to create a framework that can facilitate automated trading on most of the brokerage platforms, with minimum changes. At the end of the journey, you will have a working trading bot, with a sample implementation using the OANDA REST API, which is free to use. What You'll Learn Find out about trading bots Discover the details of tradeable instruments and apply bots to them Track and use market data events Place orders and trades Work with trade/order and account events Who This Book Is For Experienced programmers new to bots and other algorithmic trading and finance techniques.

Financial Analytics With R

Author : Mark J. Bennett
ISBN : 9781107150751
Genre : Business & Economics
File Size : 88. 32 MB
Format : PDF, ePub, Docs
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Financial Analytics with R sharpens readers' skills in time-series, forecasting, portfolio selection, covariance clustering, prediction, and derivative securities.

Introduction To R For Quantitative Finance

Author : Gergely Daróczi
ISBN : 9781783280940
Genre : Computers
File Size : 45. 5 MB
Format : PDF, ePub, Mobi
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This book is a tutorial guide for new users that aims to help you understand the basics of and become accomplished with the use of R for quantitative finance.If you are looking to use R to solve problems in quantitative finance, then this book is for you. A basic knowledge of financial theory is assumed, but familiarity with R is not required. With a focus on using R to solve a wide range of issues, this book provides useful content for both the R beginner and more experience users.

Professional Automated Trading

Author : Eugene A. Durenard
ISBN : 9781118419298
Genre : Business & Economics
File Size : 21. 79 MB
Format : PDF, Kindle
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An insider's view of how to develop and operate an automated proprietary trading network Reflecting author Eugene Durenard's extensive experience in this field, Professional Automated Trading offers valuable insights you won't find anywhere else. It reveals how a series of concepts and techniques coming from current research in artificial life and modern control theory can be applied to the design of effective trading systems that outperform the majority of published trading systems. It also skillfully provides you with essential information on the practical coding and implementation of a scalable systematic trading architecture. Based on years of practical experience in building successful research and infrastructure processes for purpose of trading at several frequencies, this book is designed to be a comprehensive guide for understanding the theory of design and the practice of implementation of an automated systematic trading process at an institutional scale. Discusses several classical strategies and covers the design of efficient simulation engines for back and forward testing Provides insights on effectively implementing a series of distributed processes that should form the core of a robust and fault-tolerant automated systematic trading architecture Addresses trade execution optimization by studying market-pressure models and minimization of costs via applications of execution algorithms Introduces a series of novel concepts from artificial life and modern control theory that enhance robustness of the systematic decision making—focusing on various aspects of adaptation and dynamic optimal model choice Engaging and informative, Proprietary Automated Trading covers the most important aspects of this endeavor and will put you in a better position to excel at it.

Algorithmic Trading

Author : Ernie Chan
ISBN : 9781118460146
Genre : Business & Economics
File Size : 60. 35 MB
Format : PDF, Kindle
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Markets are now almost always electronic, and as a result of decimalization, algorithmic trading is booming. Algorithmic trading (or "algo trading" as it is referred) is the use of computer programs (such as Excel or MatLab) for entering and executing trading orders with the computer algorithm deciding on certain aspects of the order, such as the timing, price, or even the final quantity of the order. Algorithmic trading may be used in any investment strategy, including market-making, inter-market spreading, arbitrage, or pure speculation (including trend following). The investment decision and implementation may be augmented at any stage with algorithmic support or may operate completely automatically. Algorithmic Trading provides an understanding of the core concepts in quantitative trading, an understanding of the process of using mathematics and statistics to analyze the profitability of a trading model, a “hands on” experience of how backtesting is done, and an understanding of pair trading in stocks, ETFs, futures and currencies. Chan shows investors how to use Excel and MatLab to build their own algo trading tools, as well as FX1, an FX trading platform growing in popularity.He also shows investors how to conduct quantitative research and analysis, and turn quantitative trading strategies into profits using stocks, ETFs, futures, and other financial instruments.

Handbook Of Multi Commodity Markets And Products

Author : Andrea Roncoroni
ISBN : 9780470661833
Genre : Business & Economics
File Size : 46. 68 MB
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The comprehensive guide to working more effectively within the multi-commodity market. The Handbook of Multi-Commodity Markets and Products is the definitive desktop reference for traders, structurers, and risk managers who wish to broaden their knowledge base. This non-technical yet sophisticated manual covers everything the professional needs to become acquainted with the structure, function, rules, and practices across a wide spectrum of commodity markets. Contributions from a global team of renowned industry experts provide real-world examples for each market, along with tools for analyzing, pricing, and risk managing deals. The discussion focuses on convergence, including arbitrage valuation, econometric modeling, market structure analysis, contract engineering, and risk, while simulated scenarios help readers understand the practical application of the methods and models presented. Gradual deregulation and the resulting increase in diversity and activity have driven the evolution of the traditionally segmented market toward integration, raising important questions about opportunity identification and analysis in multi-commodity deals. This book helps professionals navigate the shift, providing in-depth information and practical advice. Structure and manage both simple and sophisticated multi-commodity deals Exploit pay-off profiles and trading strategies with a diversified set of commodity prices Develop more accurate forecasting models by considering additional metrics Price energy products and other commodities in segmented markets with an eye toward specific structural features As one of the only markets strong enough to boom during the credit crunch, the commodities markets are growing rapidly. Combined with increasing convergence, this transition presents potentially valuable opportunities for the development of a robust multi-commodity portfolio. For the professional seeking deeper understanding and a more effective strategy, the Handbook of Multi-Commodity Markets and Products offers complete information and expert guidance.

The Blender Python Api

Author : Chris Conlan
ISBN : 9781484228029
Genre : Computers
File Size : 88. 28 MB
Format : PDF
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Understand Blender's Python API to allow for precision 3D modeling and add-on development. Follow detailed guidance on how to create precise geometries, complex texture mappings, optimized renderings, and much more. This book is a detailed, user-friendly guide to understanding and using Blender’s Python API for programmers and 3D artists. Blender is a popular open source 3D modeling software used in advertising, animation, data visualization, physics simulation, photorealistic rendering, and more. Programmers can produce extremely complex and precise models that would be impossible to replicate by hand, while artists enjoy numerous new community-built add-ons. The Blender Python API is an unparalleled programmable visualization environment. Using the API is made difficult due to its complex object hierarchy and vast documentation. Understanding the Blender Python API clearly explains the interface. You will become familiar with data structures and low-level concepts in both modeling and rendering with special attention given to optimizing procedurally generated models. In addition, the book: Discusses modules of the API as analogs to human input modes in Blender Reviews low-level and data-level manipulation of 3D objects in Blender Python Details how to deploy and extend projects with external libraries Provides organized utilities of novel and mature API abstractions for general use in add-on development What You’ll Learn Generate 3D data visualizations in Blender to better understand multivariate data and mathematical patterns. Create precision object models in Blender of architectural models, procedurally generated landscapes, atomic models, etc. Develop and distribute a Blender add-on, with special consideration given to careful development practices Pick apart Blender’s 3D viewport and Python source code to learn about API behaviors Develop a practical knowledge of 3D modeling and rendering concepts Have a practical reference to an already powerful and vast API Who This Book Is For Python programmers with an interest in data science, game development, procedural generation, and open-source programming as well as programmers of all types with a need to generate precise 3D models. Also for 3D artists with an interest in programming or with programming experience and Blender artists regardless of programming experience.

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