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Data Driven Trading
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Book Synopsis Data-Driven Trading by : William Johnson
Download or read book Data-Driven Trading written by William Johnson and published by HiTeX Press. This book was released on 2024-10-14 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Data-Driven Trading: Leveraging Big Data for Quantitative Advantage" offers a transformative guide through the modern complexities of financial markets. As the landscape of trading evolves with unprecedented speed, this book equips readers with the essential principles and tools to harness the power of big data, quantitative finance, and advanced analytics. Each chapter methodically unpacks core concepts, from foundational financial instruments and exploratory data analysis to regulatory considerations and emerging technological trends, ensuring a comprehensive understanding for novices and seasoned traders alike. Readers will uncover the intricacies of building successful algorithmic trading strategies, employing machine learning techniques, and mastering risk management to optimize their trading portfolios. The book also ventures into real-world case studies, providing tangible examples of how data-driven methodologies are reshaping the financial domain. With a strong emphasis on both knowledge acquisition and practical application, "Data-Driven Trading" serves as a vital handbook for anyone aspiring to excel in the dynamic sphere of trading by leveraging quantitative insights and technological advancements.
Book Synopsis Applications of Computational Intelligence in Data-Driven Trading by : Cris Doloc
Download or read book Applications of Computational Intelligence in Data-Driven Trading written by Cris Doloc and published by John Wiley & Sons. This book was released on 2019-10-29 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Life on earth is filled with many mysteries, but perhaps the most challenging of these is the nature of Intelligence.” – Prof. Terrence J. Sejnowski, Computational Neurobiologist The main objective of this book is to create awareness about both the promises and the formidable challenges that the era of Data-Driven Decision-Making and Machine Learning are confronted with, and especially about how these new developments may influence the future of the financial industry. The subject of Financial Machine Learning has attracted a lot of interest recently, specifically because it represents one of the most challenging problem spaces for the applicability of Machine Learning. The author has used a novel approach to introduce the reader to this topic: The first half of the book is a readable and coherent introduction to two modern topics that are not generally considered together: the data-driven paradigm and Computational Intelligence. The second half of the book illustrates a set of Case Studies that are contemporarily relevant to quantitative trading practitioners who are dealing with problems such as trade execution optimization, price dynamics forecast, portfolio management, market making, derivatives valuation, risk, and compliance. The main purpose of this book is pedagogical in nature, and it is specifically aimed at defining an adequate level of engineering and scientific clarity when it comes to the usage of the term “Artificial Intelligence,” especially as it relates to the financial industry. The message conveyed by this book is one of confidence in the possibilities offered by this new era of Data-Intensive Computation. This message is not grounded on the current hype surrounding the latest technologies, but on a deep analysis of their effectiveness and also on the author’s two decades of professional experience as a technologist, quant and academic.
Book Synopsis Machine Learning for Algorithmic Trading by : Stefan Jansen
Download or read book Machine Learning for Algorithmic Trading written by Stefan Jansen and published by Packt Publishing Ltd. This book was released on 2020-07-31 with total page 822 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis MACHINE LEARNING FOR ALGORITHMIC TRADING by : Jason Test
Download or read book MACHINE LEARNING FOR ALGORITHMIC TRADING written by Jason Test and published by . This book was released on 2020-11-20 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the best methods for PYTHON. Learn how to programming as a pro and get positive ROI in 7 days with data science and machine learning Are you looking for a super-fast computer programming course? Would you like to learn the Python Programming Language in 7 days? Do you want to increase your trading thanks to the artificial intelligence? If so, keep reading: this bundle book is for you! Today, thanks to computer programming and PYTHON we can work with sophisticated machines that can study human behavior and identify underlying human behavioral patterns. Scientists can predict effectively what products and services consumers are interested in. You can also create various quantitative and algorithmic trading strategies using Python. It is getting increasingly challenging for traditional businesses to retain their customers without adopting one or more of the cutting-edge technology explained in this book. MACHINE LEARNING FOR ALGORITHM TRADING will introduce you many selected tips and breaking down the basics of coding applied to finance. You will discover as a beginner the world of data science, machine learning and artificial intelligence with step-by-step guides that will guide you during the code-writing learning process. The following list is just a tiny fraction of what you will learn in this bundle PYTHON FOR BEGINNERS ✅ Differences among programming languages: Vba, SQL, R, Python ✅ 3 reasons why Python is fundamental for Data Science ✅ Introduction to some Python libraries like NumPy, Pandas, Matplotlib, ✅ 3 step system why Python is fundamental for Data Science ✅Describe the steps required to develop and test an ML-driven trading strategy. PYTHON DATA SCIENCE ✅ A Proven Method to Write your First Program in 7 Days ✅ 3 Common Mistakes to Avoid when You Start Coding ✅ Fit Python Data Analysis to your business ✅ 7 Most effective Machine Learning Algorithms ✅ Describe the methods used to optimize an ML-driven trading strategy. OPTIONS TRADING FOR BEGINNERS ✅ Options Trading Strategies that guarantee real results in all market conditions ✅ Top 7 endorsed indicators of a successful investment ✅ The Bull & Bear Game ✅ Learn about the 3 best charts patterns to fluctuations of stock prices DAY AND SWING TRADING ✅ How Swing trading differs from Day trading in terms of risk-aversion ✅ How your money should be invested and which trade is more profitable ✅ Swing and Day trading proven indicators to learn investment timing ✅ The secret DAY trading strategies leading to a gain of $ 9,000 per month and more than $100,000 per year. Even if you have never written a programming code before, you will quickly grasp the basics thanks to visual charts and guidelines for coding. Today is the best day to start programming like a pro. For those trading with leverage, looking for a way to take a controlled approach and manage risk, a properly designed trading system is the answer If you really wish to learn MACHINE LEARNING FOR ALGORITHMIC TRADING and master its language, please click the BUY NOW button.
Book Synopsis Financial Data Resampling for Machine Learning Based Trading by : Tomé Almeida Borges
Download or read book Financial Data Resampling for Machine Learning Based Trading written by Tomé Almeida Borges and published by Springer Nature. This book was released on 2021-02-22 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a system that combines the expertise of four algorithms, namely Gradient Tree Boosting, Logistic Regression, Random Forest and Support Vector Classifier to trade with several cryptocurrencies. A new method for resampling financial data is presented as alternative to the classical time sampled data commonly used in financial market trading. The new resampling method uses a closing value threshold to resample the data creating a signal better suited for financial trading, thus achieving higher returns without increased risk. The performance of the algorithm with the new resampling method and the classical time sampled data are compared and the advantages of using the system developed in this work are highlighted.
Book Synopsis Data Driven Investing by : Mitchell R. Hardy
Download or read book Data Driven Investing written by Mitchell R. Hardy and published by COGNITION CAPITAL MANAGEMEN. This book was released on 2004 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Python for Algorithmic Trading by : Yves Hilpisch
Download or read book Python for Algorithmic Trading written by Yves Hilpisch and published by O'Reilly Media. This book was released on 2020-11-12 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithmic trading, once the exclusive domain of institutional players, is now open to small organizations and individual traders using online platforms. The tool of choice for many traders today is Python and its ecosystem of powerful packages. In this practical book, author Yves Hilpisch shows students, academics, and practitioners how to use Python in the fascinating field of algorithmic trading. You'll learn several ways to apply Python to different aspects of algorithmic trading, such as backtesting trading strategies and interacting with online trading platforms. Some of the biggest buy- and sell-side institutions make heavy use of Python. By exploring options for systematically building and deploying automated algorithmic trading strategies, this book will help you level the playing field. Set up a proper Python environment for algorithmic trading Learn how to retrieve financial data from public and proprietary data sources Explore vectorization for financial analytics with NumPy and pandas Master vectorized backtesting of different algorithmic trading strategies Generate market predictions by using machine learning and deep learning Tackle real-time processing of streaming data with socket programming tools Implement automated algorithmic trading strategies with the OANDA and FXCM trading platforms
Book Synopsis Evidence-Based Technical Analysis by : David Aronson
Download or read book Evidence-Based Technical Analysis written by David Aronson and published by John Wiley & Sons. This book was released on 2011-07-11 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evidence-Based Technical Analysis examines how you can apply the scientific method, and recently developed statistical tests, to determine the true effectiveness of technical trading signals. Throughout the book, expert David Aronson provides you with comprehensive coverage of this new methodology, which is specifically designed for evaluating the performance of rules/signals that are discovered by data mining.
Book Synopsis McMillan on Options by : Lawrence G. McMillan
Download or read book McMillan on Options written by Lawrence G. McMillan and published by John Wiley & Sons. This book was released on 2011-02-15 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt: Legendary trader Larry McMillan does it-again-offering his personal options strategies for consistently enhancing trading profits Larry McMillan's name is virtually synonymous with options. This "Trader's Hall of Fame" recipient first shared his personal options strategies and techniques in the original McMillan on Options. Now, in a revised and Second Edition, this indispensable guide to the world of options addresses a myriad of new techniques and methods needed for profiting consistently in today's fast-paced investment arena. This thoroughly new Second Edition features updates in almost every chapter as well as enhanced coverage of many new and increasingly popular products. It also offers McMillan's personal philosophy on options, and reveals many of his previously unpublished personal insights. Readers will soon discover why Yale Hirsch of the Stock Trader's Almanac says, "McMillan is an options guru par excellence."
Book Synopsis Python for Finance by : Yves Hilpisch
Download or read book Python for Finance written by Yves Hilpisch and published by "O'Reilly Media, Inc.". This book was released on 2018-12-05 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. Updated for Python 3, the second edition of this hands-on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics. Using practical examples throughout 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.
Book Synopsis Trading for a Living by : Alexander Elder
Download or read book Trading for a Living written by Alexander Elder and published by John Wiley & Sons. This book was released on 1993-03-22 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Trading for a Living Successful trading is based on three M's: Mind, Method, and Money. Trading for a Living helps you master all of those three areas: * How to become a cool, calm, and collected trader * How to profit from reading the behavior of the market crowd * How to use a computer to find good trades * How to develop a powerful trading system * How to find the trades with the best odds of success * How to find entry and exit points, set stops, and take profits Trading for a Living helps you discipline your Mind, shows you the Methods for trading the markets, and shows you how to manage Money in your trading accounts so that no string of losses can kick you out of the game. To help you profit even more from the ideas in Trading for a Living, look for the companion volume--Study Guide for Trading for a Living. It asks over 200 multiple-choice questions, with answers and 11 rating scales for sharpening your trading skills. For example: Question Markets rise when * there are more buyers than sellers * buyers are more aggressive than sellers * sellers are afraid and demand a premium * more shares or contracts are bought than sold * I and II * II and III * II and IV * III and IV Answer B. II and III. Every change in price reflects what happens in the battle between bulls and bears. Markets rise when bulls feel more strongly than bears. They rally when buyers are confident and sellers demand a premium for participating in the game that is going against them. There is a buyer and a seller behind every transaction. The number of stocks or futures bought and sold is equal by definition.
Download or read book Quantitative Trading written by Xin Guo and published by CRC Press. This book was released on 2017-01-06 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first part of this book discusses institutions and mechanisms of algorithmic trading, market microstructure, high-frequency data and stylized facts, time and event aggregation, order book dynamics, trading strategies and algorithms, transaction costs, market impact and execution strategies, risk analysis, and management. The second part covers market impact models, network models, multi-asset trading, machine learning techniques, and nonlinear filtering. The third part discusses electronic market making, liquidity, systemic risk, recent developments and debates on the subject.
Book Synopsis Systematic Trading by : Robert Carver
Download or read book Systematic Trading written by Robert Carver and published by Harriman House Limited. This book was released on 2015-09-14 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is not just another book with yet another trading system. This is a complete guide to developing your own systems to help you make and execute trading and investing decisions. It is intended for everyone who wishes to systematise their financial decision making, either completely or to some degree. Author Robert Carver draws on financial theory, his experience managing systematic hedge fund strategies and his own in-depth research to explain why systematic trading makes sense and demonstrates how it can be done safely and profitably. Every aspect, from creating trading rules to position sizing, is thoroughly explained. The framework described here can be used with all assets, including equities, bonds, forex and commodities. There is no magic formula that will guarantee success, but cutting out simple mistakes will improve your performance. You'll learn how to avoid common pitfalls such as over-complicating your strategy, being too optimistic about likely returns, taking excessive risks and trading too frequently. Important features include: - The theory behind systematic trading: why and when it works, and when it doesn't. - Simple and effective ways to design effective strategies. - A complete position management framework which can be adapted for your needs. - How fully systematic traders can create or adapt trading rules to forecast prices. - Making discretionary trading decisions within a systematic framework for position management. - Why traditional long only investors should use systems to ensure proper diversification, and avoid costly and unnecessary portfolio churn. - Adapting strategies depending on the cost of trading and how much capital is being used. - Practical examples from UK, US and international markets showing how the framework can be used. Systematic Trading is detailed, comprehensive and full of practical advice. It provides a unique new approach to system development and a must for anyone considering using systems to make some, or all, of their investment decisions.
Book Synopsis The Risk of Trading by : Michael Toma
Download or read book The Risk of Trading written by Michael Toma and published by John Wiley & Sons. This book was released on 2012-03-23 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Develop the skills to manage risk in the high-stakes world of financial speculation The Risk of Trading is a practical resource that takes an in-depth look at one of the most challenging factors of trading—risk management. The book puts a magnifying glass on the issue of risk, something that every trader needs to understand in order to be successful. Most traders look at risk in terms of a "stop-loss" that enables them to exit a losing trade quickly. In The Risk of Trading, Michael Toma explains that risk is ever-present in every aspect of trading and advocates that traders adopt a more comprehensive view of risk that encompasses the strategic trading plan, account size, drawdowns, maximum possible losses, psychological capital, and crisis management. Shows how to conduct a detailed statistical analysis of an individual's trading methodology through back-testing and real-time results so as to identify when the methodology may be breaking down in actual trading Reveals why traders should think of themselves as project managers who are strategically managing risk The book is based on the author's unique 'focus on the risk' approach to trading using data-driven risk statistical analytics Using this book as a guide, traders can operate more as business managers and learn how to avoid market-busting losses while achieving consistently good results.
Book Synopsis Trading with Confluence by : Michael Toma Crm
Download or read book Trading with Confluence written by Michael Toma Crm and published by Outskirts Press. This book was released on 2010-02 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Success is all about managing risk, not profits." In Trading With Confluence, Michael Toma takes a unique risk-based approach to succeeding in trading futures. "The one single reason that separates success and failure in trading is the ability to focus on and assess risk," says Toma, who admits throughout the book that his risk management expertise, not his trading skills, propelled his success as a trader. The author provides all the information needed to succeed including his ten most profitable trading setups in an easy-to-understand format. The author also explains his unique methodology on how to self-assess your own trading performance by using key performance indicators specific to trading futures. Additional topics in the book include: -The importance of managing risk and how to identify high probability opportunities. -The 'Big 4 and Little 3' - the 7 key elements to trading success. -Step-by-step instruction on how to setup your trading business. -How to create your trading plan and trade journal. -Learn how to measure and assess your trading activity like a professional risk manager. -Development of key performance indicators allowing you to monitor your success and identify areas of improvement. -Learning the 'graduation plan' method of managing your trading capital. -Explanation of high probability setups to use immediately. -Specific tips on how to overcome the demons of trading psychology. -A chapter on the realities of trading and how to minimize mistakes. -Characteristics of a successful trading coach and how to select the right one for you. Trading With Confluence provides trade setups you can use from the 1st day you start your trading business and will help reduce the learning curve time that most traders struggle through before becoming consistently profitable. After spending several years as a corporate risk manager, Michael Toma takes the same risk principles used in his teaching of risk theory and combines it with his passion for trading into a no-nonsense yet intuitive understanding of why markets move through areas of 'confluence'. In Trading With Confluence, Toma provides the trader with all they need to know to trade e-mini futures by minimizing risk of capital. Packed with valuable trade setups, trading templates and platform charting tips, Trading With Confluence is a must read for the novice trader hungry for success trading the e-mini futures markets.
Book Synopsis The Risk of Trading by : Michael Toma
Download or read book The Risk of Trading written by Michael Toma and published by John Wiley & Sons. This book was released on 2012-04-17 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Develop the skills to manage risk in the high-stakes world of financial speculation The Risk of Trading is a practical resource that takes an in-depth look at one of the most challenging factors of trading—risk management. The book puts a magnifying glass on the issue of risk, something that every trader needs to understand in order to be successful. Most traders look at risk in terms of a "stop-loss" that enables them to exit a losing trade quickly. In The Risk of Trading, Michael Toma explains that risk is ever-present in every aspect of trading and advocates that traders adopt a more comprehensive view of risk that encompasses the strategic trading plan, account size, drawdowns, maximum possible losses, psychological capital, and crisis management. Shows how to conduct a detailed statistical analysis of an individual's trading methodology through back-testing and real-time results so as to identify when the methodology may be breaking down in actual trading Reveals why traders should think of themselves as project managers who are strategically managing risk The book is based on the author's unique 'focus on the risk' approach to trading using data-driven risk statistical analytics Using this book as a guide, traders can operate more as business managers and learn how to avoid market-busting losses while achieving consistently good results.
Book Synopsis Alpha Machines: Inside the AI-Driven Future of Finance by : Gaurav Garg
Download or read book Alpha Machines: Inside the AI-Driven Future of Finance written by Gaurav Garg and published by Gaurav Garg. This book was released on with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: The world of finance has been transformed by the emergence of artificial intelligence and machine learning. Advanced algorithms are now routinely applied across the industry for everything from high frequency trading to credit risk modeling. Yet despite its widespread impact, AI trading remains an often misunderstood field full of misconceptions. This book aims to serve as an accessible introduction and guide to the real-world practices, opportunities, and challenges associated with applying artificial intelligence to financial markets. Across different chapters, we explore major applications of AI in algorithmic trading, common technologies and techniques, practical implementation considerations, and case studies of successes and failures. Key topics covered include data analysis, feature engineering, major machine learning models, neural networks and deep learning, natural language processing, reinforcement learning, portfolio optimization, algorithmic trading strategies, backtesting methods, and risk management best practices when deploying AI trading systems. Each chapter provides sufficient technical detail for readers new to computer science and machine learning while emphasizing practical aspects relevant to practitioners. Code snippets and mathematical derivations illustrate key concepts. Significant attention is dedicated to real-world challenges, risks, regulatory constraints, and procedures required to operationalize AI in live trading. The goal is to provide readers with an accurate picture of current best practices that avoids overstating capabilities or ignoring pitfalls. Ethics and responsible AI development are highlighted given societal impacts. Ultimately this book aims to dispel myths, ground discussions in data-driven evidence, and present a balanced perspective on leveraging AI safely and effectively in trading. Whether an experienced practitioner looking to enhance trading strategies with machine learning or a curious student interested in exploring this intriguing field, readers across backgrounds will find an accessible synthesis of core topics and emerging developments in AI-powered finance. The book distills decades of research and industry lessons into a compact guide. Complimented by references for further reading, it serves as a valuable launchpad for readers seeking to gain a holistic understanding of this future-oriented domain at the nexus of computing and financial markets.
