Search Results: automated-trading-with-r

Automated Trading with R

Quantitative Research and Platform Development

Author: Chris Conlan

Publisher: Apress

ISBN: 1484221788

Category: Computers

Page: 205

View: 2689

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

Quantitative Research and Platform Development

Author: Christopher Conlan

Publisher: Apress

ISBN: 9781484221778

Category: Computers

Page: 205

View: 6320

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

Understanding Mathematical and Computational Tools from a Quant’s Perspective

Author: Harry Georgakopoulos

Publisher: Springer

ISBN: 1137437472

Category: Business & Economics

Page: 272

View: 8131

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 Automated Trading Systems

With an Introduction to Visual C++.NET 2005

Author: Benjamin Van Vliet

Publisher: Elsevier

ISBN: 9780080476254

Category: Business & Economics

Page: 336

View: 4244

Over the next few years, the proprietary trading and hedge fund industries will migrate largely to automated trade selection and execution systems. Indeed, this is already happening. While several finance books provide C++ code for pricing derivatives and performing numerical calculations, none approaches the topic from a system design perspective. This book will be divided into two sections—programming techniques and automated trading system ( ATS ) technology—and teach financial system design and development from the absolute ground up using Microsoft Visual C++.NET 2005. MS Visual C++.NET 2005 has been chosen as the implementation language primarily because most trading firms and large banks have developed and continue to develop their proprietary algorithms in ISO C++ and Visual C++.NET provides the greatest flexibility for incorporating these legacy algorithms into working systems. Furthermore, the .NET Framework and development environment provide the best libraries and tools for rapid development of trading systems. The first section of the book explains Visual C++.NET 2005 in detail and focuses on the required programming knowledge for automated trading system development, including object oriented design, delegates and events, enumerations, random number generation, timing and timer objects, and data management with STL.NET and .NET collections. Furthermore, since most legacy code and modeling code in the financial markets is done in ISO C++, this book looks in depth at several advanced topics relating to managed/unmanaged/COM memory management and interoperability. Further, this book provides dozens of examples illustrating the use of database connectivity with ADO.NET and an extensive treatment of SQL and FIX and XML/FIXML. Advanced programming topics such as threading, sockets, as well as using C++.NET to connect to Excel are also discussed at length and supported by examples. The second section of the book explains technological concerns and design concepts for automated trading systems. Specifically, chapters are devoted to handling real-time data feeds, managing orders in the exchange order book, position selection, and risk management. A .dll is included in the book that will emulate connection to a widely used industry API ( Trading Technologies, Inc.’s XTAPI ) and provide ways to test position and order management algorithms. Design patterns are presented for market taking systems based upon technical analysis as well as for market making systems using intermarket spreads. As all of the chapters revolve around computer programming for financial engineering and trading system development, this book will educate traders, financial engineers, quantitative analysts, students of quantitative finance and even experienced programmers on technological issues that revolve around development of financial applications in a Microsoft environment and the construction and implementation of real-time trading systems and tools. * Teaches financial system design and development from the ground up using Microsoft Visual C++.NET 2005. * Provides dozens of examples illustrating the programming approaches in the book * Chapters are supported by screenshots, equations, sample Excel spreadsheets, and programming code

Expert Advisor Programming for MetaTrader 4

Creating Automated Trading Systems in the MQL4 Language

Author: Andrew R. Young

Publisher: N.A

ISBN: 9780982645932


Page: 290

View: 4065

Brand new and fully updated for the latest versions of MetaTrader 4, "Expert Advisor Programming for MetaTrader 4" is a practical guide to programming expert advisors in the MQL4 language. Leverage the latest features imported from the MQL5 language, including object-oriented programming, enumerations, structures and more. This book will teach you the following concepts: The basics of the MQL4 language, including variables and data types, operations, conditional and loop operators, functions, classes and objects, event handlers and more. Place, modify and close market and pending orders. Add a stop loss and/or take profit price to an individual order, or to multiple orders. Close orders individually or by order type. Get a total of all currently opened orders. Work with OHLC bar data, and locate basic candlestick patterns. Find the highest high and lowest low of recent bars. Work with MetaTrader's built-in indicators, as well as custom indicators. Add a trailing stop or break even stop feature to an expert advisor. Use money management and lot size verification techniques. Add a flexible trading timer to an expert advisor. Construct several types of trading systems, including trend, counter-trend and breakout systems. Add alerts, emails, sounds and other notifications. Add and manipulate chart objects. Read and write to CSV files. Construct basic indicators, scripts and libraries. Learn how to effectively debug your programs, and use the Strategy Tester to test your strategies. All of the source code in this book is available for download, including an expert advisor framework that allows you to build robust and fully-featured expert advisors with minimal effort. Whether you're a new trader with limited programming experience, or an experienced programmer who has worked in other languages, "Expert Advisor Programming for MetaTrader 4" is the easiest way to get up and running in MQL4.

Building Trading Bots Using Java

Author: Shekhar Varshney

Publisher: Apress

ISBN: 1484225201

Category: Computers

Page: 281

View: 6703

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.

Expert Advisor Programming

Creating Automated Trading Systems in MQL for MetaTrader 4

Author: Gerard Desjardins,Andrew R. Young

Publisher: N.A

ISBN: 9780982645901

Category: Business & Economics

Page: 214

View: 3639

Finally, the first comprehensive guide to MQL programming is here! Expert Advisor Programming guides you through the process of developing robust automated forex trading systems for the popular MetaTrader 4 platform. In this book, the author draws on several years of experience coding hundreds of expert advisors for retail traders worldwide. You'll learn how to program these common trading tasks, and much more: - Place market, stop and limit orders. - Accurately calculate stop loss and take profit prices. - Calculate lot size based on risk. - Add flexible trailing stops to your orders. - Count, modify and close multiple orders at once. - Verify trading conditions using indicators and price data. - Create flexible and reusable source code functions. - Add advanced features such as timers, email alerts and Martingale lot sizing. - Avoid common trading errors and easily troubleshoot your programs. - Adjustments for fractional pip brokers and FIFO. - Plus, learn how to create your own custom indicators and scripts! Whether you're a beginner or an experienced programmer, Expert Advisor Programming can help you realize your automated trading ideas in the shortest amount of time. This book features dozens of code examples with detailed explanations, fully-functioning example programs, and reusable functions that you can use in your own expert advisors!

The Blender Python API

Precision 3D Modeling and Add-on Development

Author: Chris Conlan

Publisher: Apress

ISBN: 1484228022

Category: Computers

Page: 138

View: 3760

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.

Machine Trading

Deploying Computer Algorithms to Conquer the Markets

Author: Ernest P. Chan

Publisher: John Wiley & Sons

ISBN: 1119219604

Category: Business & Economics

Page: 264

View: 9486

Dive into algo trading with step-by-step tutorials and expert insight Machine Trading is a practical guide to building your algorithmic trading business. Written by a recognized trader with major institution expertise, this book provides step-by-step instruction on quantitative trading and the latest technologies available even outside the Wall Street sphere. You'll discover the latest platforms that are becoming increasingly easy to use, gain access to new markets, and learn new quantitative strategies that are applicable to stocks, options, futures, currencies, and even bitcoins. The companion website provides downloadable software codes, and you'll learn to design your own proprietary tools using MATLAB. The author's experiences provide deep insight into both the business and human side of systematic trading and money management, and his evolution from proprietary trader to fund manager contains valuable lessons for investors at any level. Algorithmic trading is booming, and the theories, tools, technologies, and the markets themselves are evolving at a rapid pace. This book gets you up to speed, and walks you through the process of developing your own proprietary trading operation using the latest tools. Utilize the newer, easier algorithmic trading platforms Access markets previously unavailable to systematic traders Adopt new strategies for a variety of instruments Gain expert perspective into the human side of trading The strength of algorithmic trading is its versatility. It can be used in any strategy, including market-making, inter-market spreading, arbitrage, or pure speculation; decision-making and implementation can be augmented at any stage, or may operate completely automatically. Traders looking to step up their strategy need look no further than Machine Trading for clear instruction and expert solutions.

Introduction to R for Quantitative Finance

Author: Gergely Daróczi,Michael Puhle,Edina Berlinger,Péter Csóka,Daniel Havran,Márton Michaletzky,Zsolt Tulassay,Kata Váradi,Agnes Vidovics-Dancs

Publisher: Packt Publishing Ltd

ISBN: 1783280948

Category: Computers

Page: 164

View: 6583

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.

Financial Analytics with R

Author: Mark J. Bennett,Dirk L. Hugen

Publisher: Cambridge University Press

ISBN: 1107150752

Category: Business & Economics

Page: 390

View: 4280

Financial Analytics with R sharpens readers' skills in time-series, forecasting, portfolio selection, covariance clustering, prediction, and derivative securities.

Mastering R for Quantitative Finance

Author: Edina Berlinger,Ferenc Illés,Milán Badics,Ádám Banai,Gergely Daróczi,Barbara Dömötör,Gergely Gabler,Dániel Havran,Péter Juhász,István Margitai,Balázs Márkus,Péter Medvegyev,Julia Molnár,Balázs Árpád Szűcs,Ágnes Tuza,Tamás Vadász,Kata Váradi,Ágnes Vidovics-Dancs

Publisher: Packt Publishing Ltd

ISBN: 1783552085

Category: Computers

Page: 362

View: 1733

This book is intended for those who want to learn how to use R's capabilities to build models in quantitative finance at a more advanced level. If you wish to perfectly take up the rhythm of the chapters, you need to be at an intermediate level in quantitative finance and you also need to have a reasonable knowledge of R.

Python for Finance

Analyze Big Financial Data

Author: Yves Hilpisch

Publisher: "O'Reilly Media, Inc."

ISBN: 1491945389

Category: Computers

Page: 606

View: 8683

The financial industry has adopted Python at a tremendous rate recently, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. This hands-on guide helps both developers and quantitative analysts get started with Python, and guides you through the most important aspects of using Python for quantitative finance. Using practical examples through the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks, with topics that include: Fundamentals: Python data structures, NumPy array handling, time series analysis with pandas, visualization with matplotlib, high performance I/O operations with PyTables, date/time information handling, and selected best practices Financial topics: mathematical techniques with NumPy, SciPy and SymPy such as regression and optimization; stochastics for Monte Carlo simulation, Value-at-Risk, and Credit-Value-at-Risk calculations; statistics for normality tests, mean-variance portfolio optimization, principal component analysis (PCA), and Bayesian regression Special topics: performance Python for financial algorithms, such as vectorization and parallelization, integrating Python with Excel, and building financial applications based on Web technologies

The Leverage Space Trading Model

Reconciling Portfolio Management Strategies and Economic Theory

Author: Ralph Vince

Publisher: John Wiley and Sons

ISBN: 9780470496022

Category: Business & Economics

Page: 224

View: 731

Praise for The Leverage Space Trading Model "As Warren Buffett said, 'It's only when the tide goes out that you learn who's been swimming naked.' We now know that most have been. It's too bad that Ralph Vince did not finish his book in 2005 or 2006, it would have helped save institutional investors and our nation trillions of dollars; few people understand the rewards of leverage and its inherent risks like Ralph. As we found out, most hedge funds and banks use leverage without knowing how to quantify its risks or rewards. This book is a must-read for anyone using or being responsible for risk. Leverage is one of our greatest empowerments." —Salomon Konig, member of the board of directors, Hedge Fund Association, Partner and Chief Investment Officer, Artemis Capital Partners, LLC "Ralph Vince is almost alone in his study of trade sizing, but that doesn't mean he isn't right. Traders should read this book." —Euan Sinclair, option trader and author of Volatility Trading "As we've seen recently, the gross misuse of leverage has been a hard lesson for institutions. But position sizing is critical to the success of all traders, big and small, and Ralph Vince brings fresh thinking to an area that badly needs it. He challenges the status quo and makes you think about what you're doing. He attacks the major flaws of MPT. There is no doubt that you'll benefit from Ralph's ideas." —Perry Kaufman, author of New Trading Systems and Methods, Fourth Edition and A Short Course in Technical Trading "If Ralph Vince writes it, I read it...every word, every thought this guy has produced has led me to additional market profits. Money management is clearly the way to the kingdom of wealth in the investment world and Ralph gives you the keys in this book." —Larry Williams, trader, fund manager, and author of Trade Stocks & Commodities with the Insiders: Secrets of the COT Report and Long-Term Secrets to Short-Term Trading

Nonlinear Time Series Analysis with R

Author: Ray Huffaker,Marco Bittelli,Rodolfo Rosa

Publisher: Oxford University Press

ISBN: 0191085790

Category: Mathematics

Page: 312

View: 6270

Nonlinear Time Series Analysis with R provides a practical guide to emerging empirical techniques allowing practitioners to diagnose whether highly fluctuating and random appearing data are most likely driven by random or deterministic dynamic forces. It joins the chorus of voices recommending 'getting to know your data' as an essential preliminary evidentiary step in modelling. Time series are often highly fluctuating with a random appearance. Observed volatility is commonly attributed to exogenous random shocks to stable real-world systems. However, breakthroughs in nonlinear dynamics raise another possibility: highly complex dynamics can emerge endogenously from astoundingly parsimonious deterministic nonlinear models. Nonlinear Time Series Analysis (NLTS) is a collection of empirical tools designed to aid practitioners detect whether stochastic or deterministic dynamics most likely drive observed complexity. Practitioners become 'data detectives' accumulating hard empirical evidence supporting their modelling approach. This book is targeted to professionals and graduate students in engineering and the biophysical and social sciences. Its major objectives are to help non-mathematicians—with limited knowledge of nonlinear dynamics—to become operational in NLTS; and in this way to pave the way for NLTS to be adopted in the conventional empirical toolbox and core coursework of the targeted disciplines. Consistent with modern trends in university instruction, the book makes readers active learners with hands-on computer experiments in R code directing them through NLTS methods and helping them understand the underlying logic. The computer code is explained in detail so that readers can adjust it for use in their own work. The book also provides readers with an explicit framework—condensed from sound empirical practices recommended in the literature—that details a step-by-step procedure for applying NLTS in real-world data diagnostics.

Text Mining with R

A Tidy Approach

Author: Julia Silge,David Robinson

Publisher: "O'Reilly Media, Inc."

ISBN: 1491981628

Category: Computers

Page: 194

View: 2502

Much of the data available today is unstructured and text-heavy, making it challenging for analysts to apply their usual data wrangling and visualization tools. With this practical book, you’ll explore text-mining techniques with tidytext, a package that authors Julia Silge and David Robinson developed using the tidy principles behind R packages like ggraph and dplyr. You’ll learn how tidytext and other tidy tools in R can make text analysis easier and more effective. The authors demonstrate how treating text as data frames enables you to manipulate, summarize, and visualize characteristics of text. You’ll also learn how to integrate natural language processing (NLP) into effective workflows. Practical code examples and data explorations will help you generate real insights from literature, news, and social media. Learn how to apply the tidy text format to NLP Use sentiment analysis to mine the emotional content of text Identify a document’s most important terms with frequency measurements Explore relationships and connections between words with the ggraph and widyr packages Convert back and forth between R’s tidy and non-tidy text formats Use topic modeling to classify document collections into natural groups Examine case studies that compare Twitter archives, dig into NASA metadata, and analyze thousands of Usenet messages

Building Algorithmic Trading Systems

A Trader's Journey From Data Mining to Monte Carlo Simulation to Live Trading

Author: Kevin Davey

Publisher: John Wiley & Sons

ISBN: 111877888X

Category: Business & Economics

Page: 288

View: 9979

Develop your own trading system with practical guidance and expert advice In Building Algorithmic Trading Systems: A Trader's Journey From Data Mining to Monte Carlo Simulation to Live Training, award-winning trader Kevin Davey shares his secrets for developing trading systems that generate triple-digit returns. With both explanation and demonstration, Davey guides you step-by-step through the entire process of generating and validating an idea, setting entry and exit points, testing systems, and implementing them in live trading. You'll find concrete rules for increasing or decreasing allocation to a system, and rules for when to abandon one. The companion website includes Davey's own Monte Carlo simulator and other tools that will enable you to automate and test your own trading ideas. A purely discretionary approach to trading generally breaks down over the long haul. With market data and statistics easily available, traders are increasingly opting to employ an automated or algorithmic trading system—enough that algorithmic trades now account for the bulk of stock trading volume. Building Algorithmic Trading Systems teaches you how to develop your own systems with an eye toward market fluctuations and the impermanence of even the most effective algorithm. Learn the systems that generated triple-digit returns in the World Cup Trading Championship Develop an algorithmic approach for any trading idea using off-the-shelf software or popular platforms Test your new system using historical and current market data Mine market data for statistical tendencies that may form the basis of a new system Market patterns change, and so do system results. Past performance isn't a guarantee of future success, so the key is to continually develop new systems and adjust established systems in response to evolving statistical tendencies. For individual traders looking for the next leap forward, Building Algorithmic Trading Systems provides expert guidance and practical advice.

Electronic and Algorithmic Trading Technology

The Complete Guide

Author: Kendall Kim

Publisher: Academic Press

ISBN: 9780080548869

Category: Business & Economics

Page: 224

View: 7439

Electronic and algorithmic trading has become part of a mainstream response to buy-side traders’ need to move large blocks of shares with minimum market impact in today’s complex institutional trading environment. This book illustrates an overview of key providers in the marketplace. With electronic trading platforms becoming increasingly sophisticated, more cost effective measures handling larger order flow is becoming a reality. The higher reliance on electronic trading has had profound implications for vendors and users of information and trading products. Broker dealers providing solutions through their products are facing changes in their business models such as: relationships with sellside customers, relationships with buyside customers, the importance of broker neutrality, the role of direct market access, and the relationship with prime brokers. Electronic and Algorithmic Trading Technology: The Complete Guide is the ultimate guide to managers, institutional investors, broker dealers, and software vendors to better understand innovative technologies that can cut transaction costs, eliminate human error, boost trading efficiency and supplement productivity. As economic and regulatory pressures are driving financial institutions to seek efficiency gains by improving the quality of software systems, firms are devoting increasing amounts of financial and human capital to maintaining their competitive edge. This book is written to aid the management and development of IT systems for financial institutions. Although the book focuses on the securities industry, its solution framework can be applied to satisfy complex automation requirements within very different sectors of financial services – from payments and cash management, to insurance and securities. Electronic and Algorithmic Trading: The Complete Guide is geared toward all levels of technology, investment management and the financial service professionals responsible for developing and implementing cutting-edge technology. It outlines a complete framework for successfully building a software system that provides the functionalities required by the business model. It is revolutionary as the first guide to cover everything from the technologies to how to evaluate tools to best practices for IT management. First book to address the hot topic of how systems can be designed to maximize the benefits of program and algorithmic trading Outlines a complete framework for developing a software system that meets the needs of the firm's business model Provides a robust system for making the build vs. buy decision based on business requirements

Professional Automated Trading

Theory and Practice

Author: Eugene A. Durenard

Publisher: John Wiley & Sons

ISBN: 1118419294

Category: Business & Economics

Page: 384

View: 5129

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.

Handbook of High Frequency Trading

Author: Greg N. Gregoriou

Publisher: Academic Press

ISBN: 0128023627

Category: Business & Economics

Page: 494

View: 9545

This comprehensive examination of high frequency trading looks beyond mathematical models, which are the subject of most HFT books, to the mechanics of the marketplace. In 25 chapters, researchers probe the intricate nature of high frequency market dynamics, market structure, back-office processes, and regulation. They look deeply into computing infrastructure, describing data sources, formats, and required processing rates as well as software architecture and current technologies. They also create contexts, explaining the historical rise of automated trading systems, corresponding technological advances in hardware and software, and the evolution of the trading landscape. Developed for students and professionals who want more than discussions on the econometrics of the modelling process, The Handbook of High Frequency Trading explains the entirety of this controversial trading strategy. Answers all questions about high frequency trading without being limited to mathematical modelling Illuminates market dynamics, processes, and regulations Explains how high frequency trading evolved and predicts its future developments

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