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The Evaluation And Optimization Of Trading Strategies
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Book Synopsis The Evaluation and Optimization of Trading Strategies by : Robert Pardo
Download or read book The Evaluation and Optimization of Trading Strategies written by Robert Pardo and published by John Wiley & Sons. This book was released on 2011-01-11 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: A newly expanded and updated edition of the trading classic, Design, Testing, and Optimization of Trading Systems Trading systems expert Robert Pardo is back, and in The Evaluation and Optimization of Trading Strategies, a thoroughly revised and updated edition of his classic text Design, Testing, and Optimization of Trading Systems, he reveals how he has perfected the programming and testing of trading systems using a successful battery of his own time-proven techniques. With this book, Pardo delivers important information to readers, from the design of workable trading strategies to measuring issues like profit and risk. Written in a straightforward and accessible style, this detailed guide presents traders with a way to develop and verify their trading strategy no matter what form they are currently using–stochastics, moving averages, chart patterns, RSI, or breakout methods. Whether a trader is seeking to enhance their profit or just getting started in testing, The Evaluation and Optimization of Trading Strategies offers practical instruction and expert advice on the development, evaluation, and application of winning mechanical trading systems.
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 Trading Systems by : Emilio Tomasini
Download or read book Trading Systems written by Emilio Tomasini and published by Harriman House Pub. This book was released on 2009 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Trading Systems" offers an insight into what a trader should know and do in order to achieve success on the markets.
Book Synopsis Trading Systems 2nd Edition by : Urban Jaekle
Download or read book Trading Systems 2nd Edition written by Urban Jaekle and published by Harriman House Limited. This book was released on 2019-12-17 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: Completely revised and updated second edition, with new AmiBroker codes and new complete portfolio tests Every day, there are traders who make a fortune. It may seem that it seldom happens, but it does – as William Eckhardt, Ed Seykota, Jim Simons, and many others remind us. You can join them by using systems to manage your trading. This book explains how you can build a winning trading system. It is an insight into what a trader should know and do in order to achieve success in the markets, and it will show you why you don't need to be a rocket scientist to become successful. It shows how to adapt existing codes to the current market conditions, how to build a portfolio, and how to know when the moment has come to stop one system and use another one. There are three main parts to Trading Systems. Part One is a short, practical guide to trading systems development and evaluation. It condenses the authors' years of experience into a number of practical tips. It also forms the theoretical basis for Part Two, in which readers will find a step-by-step development process for building a trading system, covering everything from writing initial code to walk-forward analysis and money management. Two examples are provided, including a new beginning of the month trading system that works on over 20 different stock indices worldwide – from the US, to Europe, to Asian indices. Part Three shows you how to build portfolios in two different ways. The first method is to combine a number of different trading systems, for a number of different markets, into an effective portfolio of systems. The second method is a new approach to system development: it provides step-by-step instructions to trade a portfolio of hundreds of stocks using a Bollinger Band trading strategy. A trader can never really say they were successful, but only that they survived to trade another day; the black swan is always just around the corner. Trading Systems will help you find your way through the uncharted waters of systematic trading and show you what it takes to be among those that survive.
Book Synopsis Hands-On Machine Learning for Algorithmic Trading by : Stefan Jansen
Download or read book Hands-On Machine Learning for Algorithmic Trading written by Stefan Jansen and published by Packt Publishing Ltd. This book was released on 2018-12-31 with total page 668 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras Key FeaturesImplement machine learning algorithms to build, train, and validate algorithmic modelsCreate your own algorithmic design process to apply probabilistic machine learning approaches to trading decisionsDevelop neural networks for algorithmic trading to perform time series forecasting and smart analyticsBook Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies. This book shows how to access market, fundamental, and alternative data via API or web scraping and offers a framework to evaluate alternative data. You'll practice the ML workflow from model design, loss metric definition, and parameter tuning to performance evaluation in a time series context. You will understand ML algorithms such as Bayesian and ensemble methods and manifold learning, and will know how to train and tune these models using pandas, statsmodels, sklearn, PyMC3, xgboost, lightgbm, and catboost. This book also teaches you how to extract features from text data using spaCy, classify news and assign sentiment scores, and to use gensim to model topics and learn word embeddings from financial reports. You will also build and evaluate neural networks, including RNNs and CNNs, using Keras and PyTorch to exploit unstructured data for sophisticated strategies. Finally, you will apply transfer learning to satellite images to predict economic activity and use reinforcement learning to build agents that learn to trade in the OpenAI Gym. What you will learnImplement machine learning techniques to solve investment and trading problemsLeverage market, fundamental, and alternative data to research alpha factorsDesign and fine-tune supervised, unsupervised, and reinforcement learning modelsOptimize portfolio risk and performance using pandas, NumPy, and scikit-learnIntegrate machine learning models into a live trading strategy on QuantopianEvaluate strategies using reliable backtesting methodologies for time seriesDesign and evaluate deep neural networks using Keras, PyTorch, and TensorFlowWork with reinforcement learning for trading strategies in the OpenAI GymWho this book is for Hands-On Machine Learning for Algorithmic Trading is for data analysts, data scientists, and Python developers, as well as investment analysts and portfolio managers working within the finance and investment industry. If you want to perform efficient algorithmic trading by developing smart investigating strategies using machine learning algorithms, this is the book for you. Some understanding of Python and machine learning techniques is mandatory.
Book Synopsis Cybernetic Trading Strategies by : Murray A. Ruggiero
Download or read book Cybernetic Trading Strategies written by Murray A. Ruggiero and published by John Wiley & Sons. This book was released on 1997-07-01 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ein Überblick über die aktuellsten Technologien zum Aufbau einer Handelsstrategie: neuronale Netzwerke, genetische Algorithmen, Expertensysteme, Fuzzy logic und statistische Mustererkennung. Gezeigt wird, wie diese neuen Methoden in klassische Analysenverfahren integriert werden können. Auch Erläuterungen zur Prüfung und Bewertung existierender Systeme kommen nicht zu kurz.
Book Synopsis The Science of Algorithmic Trading and Portfolio Management by : Robert Kissell
Download or read book The Science of Algorithmic Trading and Portfolio Management written by Robert Kissell and published by Academic Press. This book was released on 2013-10-01 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Science of Algorithmic Trading and Portfolio Management, with its emphasis on algorithmic trading processes and current trading models, sits apart from others of its kind. Robert Kissell, the first author to discuss algorithmic trading across the various asset classes, provides key insights into ways to develop, test, and build trading algorithms. Readers learn how to evaluate market impact models and assess performance across algorithms, traders, and brokers, and acquire the knowledge to implement electronic trading systems. This valuable book summarizes market structure, the formation of prices, and how different participants interact with one another, including bluffing, speculating, and gambling. Readers learn the underlying details and mathematics of customized trading algorithms, as well as advanced modeling techniques to improve profitability through algorithmic trading and appropriate risk management techniques. Portfolio management topics, including quant factors and black box models, are discussed, and an accompanying website includes examples, data sets supplementing exercises in the book, and large projects. Prepares readers to evaluate market impact models and assess performance across algorithms, traders, and brokers. Helps readers design systems to manage algorithmic risk and dark pool uncertainty. Summarizes an algorithmic decision making framework to ensure consistency between investment objectives and trading objectives.
Book Synopsis Automated Option Trading by : Sergey Izraylevich Ph.D.
Download or read book Automated Option Trading written by Sergey Izraylevich Ph.D. and published by FT Press. This book was released on 2012-03-12 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first and only book of its kind, Automated Options Trading describes a comprehensive, step-by-step process for creating automated options trading systems. Using the authors’ techniques, sophisticated traders can create powerful frameworks for the consistent, disciplined realization of well-defined, formalized, and carefully-tested trading strategies based on their specific requirements. Unlike other books on automated trading, this book focuses specifically on the unique requirements of options, reflecting philosophy, logic, quantitative tools, and valuation procedures that are completely different from those used in conventional automated trading algorithms. Every facet of the authors’ approach is optimized for options, including strategy development and optimization; capital allocation; risk management; performance measurement; back-testing and walk-forward analysis; and trade execution. The authors’ system reflects a continuous process of valuation, structuring and long-term management of investment portfolios (not just individual instruments), introducing systematic approaches for handling portfolios containing option combinations related to different underlying assets. With these techniques, it is finally possible to effectively automate options trading at the portfolio level. This book will be an indispensable resource for serious options traders working individually, in hedge funds, or in other institutions.
Book Synopsis Building Winning Algorithmic Trading Systems by : Kevin J. Davey
Download or read book Building Winning Algorithmic Trading Systems written by Kevin J. Davey and published by John Wiley & Sons. This book was released on 2014-06-11 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis The Art and Science of Technical Analysis by : Adam Grimes
Download or read book The Art and Science of Technical Analysis written by Adam Grimes and published by John Wiley & Sons. This book was released on 2012-05-31 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: A breakthrough trading book that provides powerful insights on profitable technical patterns and strategies The Art and Science of Technical Analysis is a groundbreaking work that bridges the gaps between the academic view of markets, technical analysis, and profitable trading. The book explores why randomness prevails in markets most, but not all, of the time and how technical analysis can be used to capture statistically validated patterns in certain types of market conditions. The belief of the book is that buying and selling pressure causes patterns in prices, but that these technical patterns are only effective in the presence of true buying/selling imbalance. The Art and Science of Technical Analysis is supported by extensive statistical analysis of the markets, which will debunk some tools and patterns such as Fibonacci analysis, and endorse other tools and trade setups. In addition, this reliable resource discusses trader psychology and trader learning curves based on the author's extensive experience as a trader and trainer of traders. Offers serious traders a way to think about market problems, understand their own performance, and help find a more productive path forward Includes extensive research to validate specific money-making patterns and strategies Written by an experienced market practitioner who has trained and worked with many top traders Filled with in-depth insights and practical advice, The Art and Science of Technical Analysis will give you a realistic sense of how markets behave, when and how technical analysis works, and what it really takes to trade successfully.
Book Synopsis The Encyclopedia of Trading Strategies by : Jeffrey Owen Katz
Download or read book The Encyclopedia of Trading Strategies written by Jeffrey Owen Katz and published by McGraw Hill Professional. This book was released on 2000-03-21 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Encyclopedia of Trading Strategies is for traders who want to take the next step to consistently profitable trading. The authors--themselves seasoned veterans of the futures trading arena--pinpoint the trading methods and strategies that have been shown to produce market-beating returns. Their rigorous and systematic backtesting of each method, using the same sets of markets and analytic techniques, provides a scientific, system-based approach to system development...to help you assemble the trading system that will put you on the road to becoming a more consistently profitable trader.
Book Synopsis Weekend Trend Trader by : Nick Radge
Download or read book Weekend Trend Trader written by Nick Radge and published by Radge Publishing. This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The Weekend Trend Trader is a trading strategy designed for people who want a simple to follow trading plan that trades just once a week. An ideal investment strategy for people who work full time but are actively planning for their retirement. Weekend Trend Trader is designed for and tested on the US stock Market. The Weekend Trend Trader strategy is a turnkey strategy that uses no discretion. In other words the strategy has a set of rules and users should understand why they entered a trade and when and how they will exit. Because the rules are strictly and mathematically defined we are able to back test the strategy on historical data. This enables us to understand the strategy’s nuances and therefore better understand how the journey to success will be travelled. The strategy is a combination of several tools that: * ensures you will always be aligned with the trend of the broader market * enters positions at specific points and with reasonable confirmation * manages existing positions with a trailing stop loss * defends existing positions if the trend of the broader market reverses * outlines how much to invest in each position. We will fully step through each of these points in detail and slowly build the system from the ground up.
Book Synopsis Algorithmic Trading and Quantitative Strategies by : Raja Velu
Download or read book Algorithmic Trading and Quantitative Strategies written by Raja Velu and published by CRC Press. This book was released on 2020-08-12 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithmic Trading and Quantitative Strategies provides an in-depth overview of this growing field with a unique mix of quantitative rigor and practitioner’s hands-on experience. The focus on empirical modeling and practical know-how makes this book a valuable resource for students and professionals. The book starts with the often overlooked context of why and how we trade via a detailed introduction to market structure and quantitative microstructure models. The authors then present the necessary quantitative toolbox including more advanced machine learning models needed to successfully operate in the field. They next discuss the subject of quantitative trading, alpha generation, active portfolio management and more recent topics like news and sentiment analytics. The last main topic of execution algorithms is covered in detail with emphasis on the state of the field and critical topics including the elusive concept of market impact. The book concludes with a discussion on the technology infrastructure necessary to implement algorithmic strategies in large-scale production settings. A git-hub repository includes data-sets and explanatory/exercise Jupyter notebooks. The exercises involve adding the correct code to solve the particular analysis/problem.
Book Synopsis Tradings Systems That Work: Building and Evaluating Effective Trading Systems by : Thomas Stridsman
Download or read book Tradings Systems That Work: Building and Evaluating Effective Trading Systems written by Thomas Stridsman and published by McGraw Hill Professional. This book was released on 2001 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: Trading Systems That Work evaluates many of today's most influential techniques and, emphasizing trading software programs TradeStation and Excel, covers all aspects of researching, building, understanding, and evaluating your own trading system.".
Book Synopsis Quantitative Trading by : Ernie Chan
Download or read book Quantitative Trading written by Ernie Chan and published by Wiley. This book was released on 2008-11-17 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: While institutional traders continue to implement quantitative (or algorithmic) trading, many independent traders have wondered if they can still challenge powerful industry professionals at their own game? The answer is "yes," and in Quantitative Trading, Dr. Ernest Chan, a respected independent trader and consultant, will show you how. Whether you're an independent "retail" trader looking to start your own quantitative trading business or an individual who aspires to work as a quantitative trader at a major financial institution, this practical guide contains the information you need to succeed.
Book Synopsis Commodity Trading Advisors by : Greg N. Gregoriou
Download or read book Commodity Trading Advisors written by Greg N. Gregoriou and published by John Wiley & Sons. This book was released on 2011-09-02 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Authoritative, up-to-date research and analysis that provides a dramatic new understanding of the rewards-and risks-of investing in CTAs Commodity Trading Advisors (CTAs) are an increasingly popular and potentially profitable investment alternative for institutional investors and high-net-worth individuals. Commodity Trading Advisors is one of the first books to study their performance in detail and analyze the "survivorship bias" present in CTA performance data. This book investigates the many benefits and risks associated with CTAs, examining the risk/return characteristics of a number of different strategies deployed by CTAs from a sophisticated investor's perspective. A contributed work, its editors and contributing authors are among today's leading voices on the topic of commodity trading advisors and a veritable "Who's Who" in hedge fund and CTA research. Greg N. Gregoriou (Plattsburgh, NY) is a Visiting Assistant Professor of Finance and Research Coordinator in the School of Business and Economics at the State University of New York. Vassilios N. Karavas (Amherst, MA) is Director of Research at Schneeweis Partners. Francois-Serge Lhabitant (Coppet, Switzerland) is a FAME Research Fellow, and a Professor of Finance at EDHEC (France) and at HEC University of Lausanne (Switzerland). Fabrice Rouah (Montreal, Quebec) is Institut de Finance Mathématique de Montréal Scholar in the finance program at McGill University.
