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Author: Shekhar Varshney
Publisher: Apress
ISBN: 1484225201
Category : Computers
Languages : en
Pages : 283
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Book Description
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.
Author: Shekhar Varshney
Publisher: Apress
ISBN: 1484225201
Category : Computers
Languages : en
Pages : 283
Get Book Here
Book Description
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.
Author: Stefan Jansen
Publisher: Packt Publishing Ltd
ISBN: 1839216786
Category : Business & Economics
Languages : en
Pages : 822
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Book Description
Leverage machine learning to design and back-test automated trading strategies for real-world markets using pandas, TA-Lib, scikit-learn, LightGBM, SpaCy, Gensim, TensorFlow 2, Zipline, backtrader, Alphalens, and pyfolio. Purchase of the print or Kindle book includes a free eBook in the PDF format. Key FeaturesDesign, train, and evaluate machine learning algorithms that underpin automated trading strategiesCreate a research and strategy development process to apply predictive modeling to trading decisionsLeverage NLP and deep learning to extract tradeable signals from market and alternative dataBook Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This revised and expanded second edition enables you to build and evaluate sophisticated supervised, unsupervised, and reinforcement learning models. This book introduces end-to-end machine learning for the trading workflow, from the idea and feature engineering to model optimization, strategy design, and backtesting. It illustrates this by using examples ranging from linear models and tree-based ensembles to deep-learning techniques from cutting edge research. This edition shows how to work with market, fundamental, and alternative data, such as tick data, minute and daily bars, SEC filings, earnings call transcripts, financial news, or satellite images to generate tradeable signals. It illustrates how to engineer financial features or alpha factors that enable an ML model to predict returns from price data for US and international stocks and ETFs. It also shows how to assess the signal content of new features using Alphalens and SHAP values and includes a new appendix with over one hundred alpha factor examples. By the end, you will be proficient in translating ML model predictions into a trading strategy that operates at daily or intraday horizons, and in evaluating its performance. What you will learnLeverage market, fundamental, and alternative text and image dataResearch and evaluate alpha factors using statistics, Alphalens, and SHAP valuesImplement machine learning techniques to solve investment and trading problemsBacktest and evaluate trading strategies based on machine learning using Zipline and BacktraderOptimize portfolio risk and performance analysis using pandas, NumPy, and pyfolioCreate a pairs trading strategy based on cointegration for US equities and ETFsTrain a gradient boosting model to predict intraday returns using AlgoSeek's high-quality trades and quotes dataWho this book is for If you are a data analyst, data scientist, Python developer, investment analyst, or portfolio manager interested in getting hands-on machine learning knowledge for trading, this book is for you. This book is for you if you want to learn how to extract value from a diverse set of data sources using machine learning to design your own systematic trading strategies. Some understanding of Python and machine learning techniques is required.
Author: Nick Cano
Publisher: No Starch Press
ISBN: 1593276699
Category : Computers
Languages : en
Pages : 305
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Book Description
You don’t need to be a wizard to transform a game you like into a game you love. Imagine if you could give your favorite PC game a more informative heads-up display or instantly collect all that loot from your latest epic battle. Bring your knowledge of Windows-based development and memory management, and Game Hacking will teach you what you need to become a true game hacker. Learn the basics, like reverse engineering, assembly code analysis, programmatic memory manipulation, and code injection, and hone your new skills with hands-on example code and practice binaries. Level up as you learn how to: –Scan and modify memory with Cheat Engine –Explore program structure and execution flow with OllyDbg –Log processes and pinpoint useful data files with Process Monitor –Manipulate control flow through NOPing, hooking, and more –Locate and dissect common game memory structures You’ll even discover the secrets behind common game bots, including: –Extrasensory perception hacks, such as wallhacks and heads-up displays –Responsive hacks, such as autohealers and combo bots –Bots with artificial intelligence, such as cave walkers and automatic looters Game hacking might seem like black magic, but it doesn’t have to be. Once you understand how bots are made, you’ll be better positioned to defend against them in your own games. Journey through the inner workings of PC games with Game Hacking, and leave with a deeper understanding of both game design and computer security.
Author: Sourav Ghosh
Publisher:
ISBN: 9781789348347
Category : Computers
Languages : en
Pages : 394
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Book Description
Understand the fundamentals of algorithmic trading to apply algorithms to real market data and analyze the results of real-world trading strategies Key Features Understand the power of algorithmic trading in financial markets with real-world examples Get up and running with the algorithms used to carry out algorithmic trading Learn to build your own algorithmic trading robots which require no human intervention Book Description It's now harder than ever to get a significant edge over competitors in terms of speed and efficiency when it comes to algorithmic trading. Relying on sophisticated trading signals, predictive models and strategies can make all the difference. This book will guide you through these aspects, giving you insights into how modern electronic trading markets and participants operate. You'll start with an introduction to algorithmic trading, along with setting up the environment required to perform the tasks in the book. You'll explore the key components of an algorithmic trading business and aspects you'll need to take into account before starting an automated trading project. Next, you'll focus on designing, building and operating the components required for developing a practical and profitable algorithmic trading business. Later, you'll learn how quantitative trading signals and strategies are developed, and also implement and analyze sophisticated trading strategies such as volatility strategies, economic release strategies, and statistical arbitrage. Finally, you'll create a trading bot from scratch using the algorithms built in the previous sections. By the end of this book, you'll be well-versed with electronic trading markets and have learned to implement, evaluate and safely operate algorithmic trading strategies in live markets. What you will learn Understand the components of modern algorithmic trading systems and strategies Apply machine learning in algorithmic trading signals and strategies using Python Build, visualize and analyze trading strategies based on mean reversion, trend, economic releases and more Quantify and build a risk management system for Python trading strategies Build a backtester to run simulated trading strategies for improving the performance of your trading bot Deploy and incorporate trading strategies in the live market to maintain and improve profitability Who this book is for This book is for software engineers, financial traders, data analysts, and entrepreneurs. Anyone who wants to get started with algorithmic trading and understand how it works; and learn the components of a trading system, protocols and algorithms required for black box and gray box trading, and techniques for building a completely automated and profitable trading business will also find this book useful.
Author: Yves Hilpisch
Publisher: "O'Reilly Media, Inc."
ISBN: 1492055387
Category : Business & Economics
Languages : en
Pages : 445
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Book Description
The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies are combined with the programmatic availability of historical and real-time financial data, the financial industry will also change fundamentally. With this practical book, you'll learn how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading. Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science practical ways to apply machine learning and deep learning algorithms to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book. In five parts, this guide helps you: Learn central notions and algorithms from AI, including recent breakthroughs on the way to artificial general intelligence (AGI) and superintelligence (SI) Understand why data-driven finance, AI, and machine learning will have a lasting impact on financial theory and practice Apply neural networks and reinforcement learning to discover statistical inefficiencies in financial markets Identify and exploit economic inefficiencies through backtesting and algorithmic trading--the automated execution of trading strategies Understand how AI will influence the competitive dynamics in the financial industry and what the potential emergence of a financial singularity might bring about
Author: Paul Raines
Publisher: "O'Reilly Media, Inc."
ISBN: 0596555792
Category : Computers
Languages : en
Pages : 458
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Book Description
The Tcl language and Tk graphical toolkit are simple and powerful building blocks for custom applications. The Tcl/Tk combination is increasingly popular because it lets you produce sophisticated graphical interfaces with a few easy commands, develop and change scripts quickly, and conveniently tie together existing utilities or programming libraries.One of the attractive features of Tcl/Tk is the wide variety of commands, many offering a wealth of options. Most of the things you'd like to do have been anticipated by the language's creator, John Ousterhout, or one of the developers of Tcl/Tk's many powerful extensions. Thus, you'll find that a command or option probably exists to provide just what you need.And that's why it's valuable to have a quick reference that briefly describes every command and option in the core Tcl/Tk distribution as well as the most popular extensions. Keep this book on your desk as you write scripts, and you'll be able to find almost instantly the particular option you need.Most chapters consist of alphabetical listings. Since Tk and mega-widget packages break down commands by widget, the chapters on these topics are organized by widget along with a section of core commands where appropriate. Contents include: Core Tcl and Tk commands and Tk widgets C interface (prototypes) Expect [incr Tcl] and [incr Tk] Tix TclX BLT Oratcl, SybTcl, and Tclodbc
Author: Donald G. Firesmith
Publisher: Pearson Education
ISBN: 9780201675108
Category : Computers
Languages : en
Pages : 366
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Book Description
"[The authors] have done an excellent job of bringing forth the power and the flexibility of this most useful framework in an easy to read and understand introduction. Although it has been written to be an introductory text in OPF, I found [it] also readily useable as a handbook for initial process definition, an accessible treatment of important issues in software process design, and a textbook in OPF." Houman Younessi Associate Professor of Computer Science, Rensselaer Polytechnic Institute The OPEN Process Framework provides a template for generating flexible, yet disciplined, processes for developing high-quality software and system applications within a predictable schedule and budget. Using this framework as a starting point, you can create and tailor a process to meet the specific needs of the project.
Author: Andreas F. Clenow
Publisher:
ISBN: 9781091983786
Category :
Languages : en
Pages : 442
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Book Description
Systematic trading allows you to test and evaluate your trading ideas before risking your money. By formulating trading ideas as concrete rules, you can evaluate past performance and draw conclusions about the viability of your trading plan. Following systematic rules provides a consistent approach where you will have some degree of predictability of returns, and perhaps more importantly, it takes emotions and second guessing out of the equation. From the onset, getting started with professional grade development and backtesting of systematic strategies can seem daunting. Many resort to simplified software which will limit your potential. Trading Evolved will guide you all the way, from getting started with the industry standard Python language, to setting up a professional backtesting environment of your own. The book will explain multiple trading strategies in detail, with full source code, to get you well on the path to becoming a professional systematic trader. This is a highly practical book, where every aspect is explained, all source code shown and no holds barred. Written by Andreas F. Clenow, author of the international best sellers Following the Trend and Stocks on the Move, Trading Evolved goes into greater depth and covers strategies for trading both futures and equities. "Trading Evolved is an incredible resource for aspiring quants. Clenow does an excellent job making complex subjects easy to access and understand. Bravo." -- Wes Gray, PhD, CEO Alpha Architect
Author: Chris Conlan
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 126
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Book Description
Algorithmic Trading with Python discusses modern quant trading methods in Python with a heavy focus on pandas, numpy, and scikit-learn. After establishing an understanding of technical indicators and performance metrics, readers will walk through the process of developing a trading simulator, strategy optimizer, and financial machine learning pipeline. This book maintains a high standard of reprocibility. All code and data is self-contained in a GitHub repo. The data includes hyper-realistic simulated price data and alternative data based on real securities. Algorithmic Trading with Python (2020) is the spiritual successor to Automated Trading with R (2016). This book covers more content in less time than its predecessor due to advances in open-source technologies for quantitative analysis.
Author: James Butler
Publisher: CreateSpace
ISBN: 9781511432115
Category :
Languages : en
Pages : 190
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Book Description
The Betfair exchange, coupled with its API, permits a suitably skilled trader to code complex trading applications, which would not look out of place in the financial markets. This book offers a sports trader the chance to build their own trading applications, regardless of their programming ability. Each chapter of Programming for Betfair contains snippets of code that combine to create a complete trading application. The application is geared towards horse racing but can easily be adapted to other sports on Betfair's exchange. Using Microsoft's Visual Studio (downloadable for free) the reader is shown how to code an application that will gather prices for any market on Betfair's exchange and then place bets into that market. The reader is shown how to automate their trading so that they can remove emotion from their trades and scale up their trading for increased profits. Further development of the application permits it to save data from Betfair onto the reader's hard drive for offline analysis and visualisation in a spreadsheet for the purpose of building trading algorithms. Also covered is an enhancement of Betfair's charts so that charts can be automatically updated and compared. The final chapter of the book discusses ideas for taking the application and the reader's skills to the next level. Topics discussed include constructing your own trading indicators, volume analysis, trend following, arbitrage, low-latency trading and many more.
