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Information and Learning in Markets

Author: Xavier Vives

Publisher: Princeton University Press

Published: 2010-01-25

Total Pages: 422

ISBN-13: 140082950X

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The ways financial analysts, traders, and other specialists use information and learn from each other are of fundamental importance to understanding how markets work and prices are set. This graduate-level textbook analyzes how markets aggregate information and examines the impacts of specific market arrangements--or microstructure--on the aggregation process and overall performance of financial markets. Xavier Vives bridges the gap between the two primary views of markets--informational efficiency and herding--and uses a coherent game-theoretic framework to bring together the latest results from the rational expectations and herding literatures. Vives emphasizes the consequences of market interaction and social learning for informational and economic efficiency. He looks closely at information aggregation mechanisms, progressing from simple to complex environments: from static to dynamic models; from competitive to strategic agents; and from simple market strategies such as noncontingent orders or quantities to complex ones like price contingent orders or demand schedules. Vives finds that contending theories like informational efficiency and herding build on the same principles of Bayesian decision making and that "irrational" agents are not needed to explain herding behavior, booms, and crashes. As this book shows, the microstructure of a market is the crucial factor in the informational efficiency of prices. Provides the most complete analysis of the ways markets aggregate information Bridges the gap between the rational expectations and herding literatures Includes exercises with solutions Serves both as a graduate textbook and a resource for researchers, including financial analysts

Book Synopsis Information and Learning in Markets by : Xavier Vives

Download or read book Information and Learning in Markets written by Xavier Vives and published by Princeton University Press. This book was released on 2010-01-25 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ways financial analysts, traders, and other specialists use information and learn from each other are of fundamental importance to understanding how markets work and prices are set. This graduate-level textbook analyzes how markets aggregate information and examines the impacts of specific market arrangements--or microstructure--on the aggregation process and overall performance of financial markets. Xavier Vives bridges the gap between the two primary views of markets--informational efficiency and herding--and uses a coherent game-theoretic framework to bring together the latest results from the rational expectations and herding literatures. Vives emphasizes the consequences of market interaction and social learning for informational and economic efficiency. He looks closely at information aggregation mechanisms, progressing from simple to complex environments: from static to dynamic models; from competitive to strategic agents; and from simple market strategies such as noncontingent orders or quantities to complex ones like price contingent orders or demand schedules. Vives finds that contending theories like informational efficiency and herding build on the same principles of Bayesian decision making and that "irrational" agents are not needed to explain herding behavior, booms, and crashes. As this book shows, the microstructure of a market is the crucial factor in the informational efficiency of prices. Provides the most complete analysis of the ways markets aggregate information Bridges the gap between the rational expectations and herding literatures Includes exercises with solutions Serves both as a graduate textbook and a resource for researchers, including financial analysts

Mind Over Markets

Author: James F. Dalton

Publisher: Wiley

Published: 2013-07-01

Total Pages: 368

ISBN-13: 9781118531730

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A timely update to the book on using the Market Profile method to trade Emerging over twenty years ago, Market Profile analysis continues to realize a strong following among active traders. The approach explains the underlying dynamics and structure of markets, identifies value areas, price rejection points, and measures the strength of buyers and sellers. Unlike more conventional forms of technical analysis, Market Profile is an all-encompassing approach, and Mind Over Markets, Updated Edition provides traders with a solid understanding of it. Since the first edition of Mind Over Markets—considered the best book on applying Market Profile analysis to trading—was published over a decade ago, much has changed in the worlds of finance and investing. That's why James Dalton, a pioneer in the popularization of Market Profile, has returned with a new edition of this essential guide. Written to reflect today's dynamic market conditions, Mind Over Markets, Updated Edition clearly puts this unique method of interpreting market behavior and identifying trading/investment opportunities in perspective. Includes new chapters on Market Profile-based trading strategies, using Market Profile in connection with other market indicators, and much more Explains how the Market Profile approach has evolved over the past twenty-five years and how it is used by contemporary traders Written by a leading educator and authority on the Market Profile One of the key elements that has long separated successful traders from the rest is their intuitive understanding that time regulates all financial opportunities. The ability to record price information according to time has unleashed huge amounts of useful market information. Mind Over Markets, Updated Edition will show you how to profitably put this information to work for you.

Book Synopsis Mind Over Markets by : James F. Dalton

Download or read book Mind Over Markets written by James F. Dalton and published by Wiley. This book was released on 2013-07-01 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: A timely update to the book on using the Market Profile method to trade Emerging over twenty years ago, Market Profile analysis continues to realize a strong following among active traders. The approach explains the underlying dynamics and structure of markets, identifies value areas, price rejection points, and measures the strength of buyers and sellers. Unlike more conventional forms of technical analysis, Market Profile is an all-encompassing approach, and Mind Over Markets, Updated Edition provides traders with a solid understanding of it. Since the first edition of Mind Over Markets—considered the best book on applying Market Profile analysis to trading—was published over a decade ago, much has changed in the worlds of finance and investing. That's why James Dalton, a pioneer in the popularization of Market Profile, has returned with a new edition of this essential guide. Written to reflect today's dynamic market conditions, Mind Over Markets, Updated Edition clearly puts this unique method of interpreting market behavior and identifying trading/investment opportunities in perspective. Includes new chapters on Market Profile-based trading strategies, using Market Profile in connection with other market indicators, and much more Explains how the Market Profile approach has evolved over the past twenty-five years and how it is used by contemporary traders Written by a leading educator and authority on the Market Profile One of the key elements that has long separated successful traders from the rest is their intuitive understanding that time regulates all financial opportunities. The ability to record price information according to time has unleashed huge amounts of useful market information. Mind Over Markets, Updated Edition will show you how to profitably put this information to work for you.

Learning by Doing in Markets, Firms, and Countries

Author: Naomi R. Lamoreaux

Publisher: University of Chicago Press

Published: 2007-11-01

Total Pages: 356

ISBN-13: 0226468437

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Learning by Doing in Markets, Firms, and Countries draws out the underlying economics in business history by focusing on learning processes and the development of competitively valuable asymmetries. The essays show that organizations, like people, learn that this process can be organized more or less effectively, which can have major implications for how competition works. The first three essays in this volume explore techniques firms have used to both manage information to create valuable asymmetries and to otherwise suppress unwelcome competition. The next three focus on the ways in which firms have built special capabilities over time, capabilities that have been both sources of competitive advantage and resistance to new opportunities. The last two extend the notion of learning from the level of firms to that of nations. The collection as a whole builds on the previous two volumes to make the connection between information structure and product market outcomes in business history.

Book Synopsis Learning by Doing in Markets, Firms, and Countries by : Naomi R. Lamoreaux

Download or read book Learning by Doing in Markets, Firms, and Countries written by Naomi R. Lamoreaux and published by University of Chicago Press. This book was released on 2007-11-01 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learning by Doing in Markets, Firms, and Countries draws out the underlying economics in business history by focusing on learning processes and the development of competitively valuable asymmetries. The essays show that organizations, like people, learn that this process can be organized more or less effectively, which can have major implications for how competition works. The first three essays in this volume explore techniques firms have used to both manage information to create valuable asymmetries and to otherwise suppress unwelcome competition. The next three focus on the ways in which firms have built special capabilities over time, capabilities that have been both sources of competitive advantage and resistance to new opportunities. The last two extend the notion of learning from the level of firms to that of nations. The collection as a whole builds on the previous two volumes to make the connection between information structure and product market outcomes in business history.

Liquidity, Markets and Trading in Action

Author: Deniz Ozenbas

Publisher: Springer Nature

Published: 2022

Total Pages: 111

ISBN-13: 3030748170

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This open access book addresses four standard business school subjects: microeconomics, macroeconomics, finance and information systems as they relate to trading, liquidity, and market structure. It provides a detailed examination of the impact of trading costs and other impediments of trading that the authors call rictions It also presents an interactive simulation model of equity market trading, TraderEx, that enables students to implement trading decisions in different market scenarios and structures. Addressing these topics shines a bright light on how a real-world financial market operates, and the simulation provides students with an experiential learning opportunity that is informative and fun. Each of the chapters is designed so that it can be used as a stand-alone module in an existing economics, finance, or information science course. Instructor resources such as discussion questions, Powerpoint slides and TraderEx exercises are available online.

Book Synopsis Liquidity, Markets and Trading in Action by : Deniz Ozenbas

Download or read book Liquidity, Markets and Trading in Action written by Deniz Ozenbas and published by Springer Nature. This book was released on 2022 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book addresses four standard business school subjects: microeconomics, macroeconomics, finance and information systems as they relate to trading, liquidity, and market structure. It provides a detailed examination of the impact of trading costs and other impediments of trading that the authors call rictions It also presents an interactive simulation model of equity market trading, TraderEx, that enables students to implement trading decisions in different market scenarios and structures. Addressing these topics shines a bright light on how a real-world financial market operates, and the simulation provides students with an experiential learning opportunity that is informative and fun. Each of the chapters is designed so that it can be used as a stand-alone module in an existing economics, finance, or information science course. Instructor resources such as discussion questions, Powerpoint slides and TraderEx exercises are available online.

Artificial Intelligence in Financial Markets

Author: Christian L. Dunis

Publisher: Springer

Published: 2016-11-21

Total Pages: 349

ISBN-13: 1137488808

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As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.

Book Synopsis Artificial Intelligence in Financial Markets by : Christian L. Dunis

Download or read book Artificial Intelligence in Financial Markets written by Christian L. Dunis and published by Springer. This book was released on 2016-11-21 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.

Guide to Financial Markets

Author: Marc Levinson

Publisher: The Economist

Published: 2018-07-24

Total Pages: 304

ISBN-13: 1541742516

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The revised and updated 7th edition of this highly regarded book brings the reader right up to speed with the latest financial market developments, and provides a clear and incisive guide to a complex world that even those who work in it often find hard to understand. In chapters on the markets that deal with money, foreign exchange, equities, bonds, commodities, financial futures, options and other derivatives, the book examines why these markets exist, how they work, and who trades in them, and gives a run-down of the factors that affect prices and rates. Business history is littered with disasters that occurred because people involved their firms with financial instruments they didn't properly understand. If they had had this book they might have avoided their mistakes. For anyone wishing to understand financial markets, there is no better guide.

Book Synopsis Guide to Financial Markets by : Marc Levinson

Download or read book Guide to Financial Markets written by Marc Levinson and published by The Economist. This book was released on 2018-07-24 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: The revised and updated 7th edition of this highly regarded book brings the reader right up to speed with the latest financial market developments, and provides a clear and incisive guide to a complex world that even those who work in it often find hard to understand. In chapters on the markets that deal with money, foreign exchange, equities, bonds, commodities, financial futures, options and other derivatives, the book examines why these markets exist, how they work, and who trades in them, and gives a run-down of the factors that affect prices and rates. Business history is littered with disasters that occurred because people involved their firms with financial instruments they didn't properly understand. If they had had this book they might have avoided their mistakes. For anyone wishing to understand financial markets, there is no better guide.

The Econometrics of Financial Markets

Author: John Y. Campbell

Publisher: Princeton University Press

Published: 2012-06-28

Total Pages: 630

ISBN-13: 1400830214

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The past twenty years have seen an extraordinary growth in the use of quantitative methods in financial markets. Finance professionals now routinely use sophisticated statistical techniques in portfolio management, proprietary trading, risk management, financial consulting, and securities regulation. This graduate-level textbook is intended for PhD students, advanced MBA students, and industry professionals interested in the econometrics of financial modeling. The book covers the entire spectrum of empirical finance, including: the predictability of asset returns, tests of the Random Walk Hypothesis, the microstructure of securities markets, event analysis, the Capital Asset Pricing Model and the Arbitrage Pricing Theory, the term structure of interest rates, dynamic models of economic equilibrium, and nonlinear financial models such as ARCH, neural networks, statistical fractals, and chaos theory. Each chapter develops statistical techniques within the context of a particular financial application. This exciting new text contains a unique and accessible combination of theory and practice, bringing state-of-the-art statistical techniques to the forefront of financial applications. Each chapter also includes a discussion of recent empirical evidence, for example, the rejection of the Random Walk Hypothesis, as well as problems designed to help readers incorporate what they have read into their own applications.

Book Synopsis The Econometrics of Financial Markets by : John Y. Campbell

Download or read book The Econometrics of Financial Markets written by John Y. Campbell and published by Princeton University Press. This book was released on 2012-06-28 with total page 630 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past twenty years have seen an extraordinary growth in the use of quantitative methods in financial markets. Finance professionals now routinely use sophisticated statistical techniques in portfolio management, proprietary trading, risk management, financial consulting, and securities regulation. This graduate-level textbook is intended for PhD students, advanced MBA students, and industry professionals interested in the econometrics of financial modeling. The book covers the entire spectrum of empirical finance, including: the predictability of asset returns, tests of the Random Walk Hypothesis, the microstructure of securities markets, event analysis, the Capital Asset Pricing Model and the Arbitrage Pricing Theory, the term structure of interest rates, dynamic models of economic equilibrium, and nonlinear financial models such as ARCH, neural networks, statistical fractals, and chaos theory. Each chapter develops statistical techniques within the context of a particular financial application. This exciting new text contains a unique and accessible combination of theory and practice, bringing state-of-the-art statistical techniques to the forefront of financial applications. Each chapter also includes a discussion of recent empirical evidence, for example, the rejection of the Random Walk Hypothesis, as well as problems designed to help readers incorporate what they have read into their own applications.

Financial Markets and Trading

Author: Anatoly B. Schmidt

Publisher: John Wiley & Sons

Published: 2011-07-05

Total Pages: 195

ISBN-13: 1118093658

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An informative guide to market microstructure and trading strategies Over the last decade, the financial landscape has undergone a significant transformation, shaped by the forces of technology, globalization, and market innovations to name a few. In order to operate effectively in today's markets, you need more than just the motivation to succeed, you need a firm understanding of how modern financial markets work and what professional trading is really about. Dr. Anatoly Schmidt, who has worked in the financial industry since 1997, and teaches in the Financial Engineering program of Stevens Institute of Technology, puts these topics in perspective with his new book. Divided into three comprehensive parts, this reliable resource offers a balance between the theoretical aspects of market microstructure and trading strategies that may be more relevant for practitioners. Along the way, it skillfully provides an informative overview of modern financial markets as well as an engaging assessment of the methods used in deriving and back-testing trading strategies. Details the modern financial markets for equities, foreign exchange, and fixed income Addresses the basics of market dynamics, including statistical distributions and volatility of returns Offers a summary of approaches used in technical analysis and statistical arbitrage as well as a more detailed description of trading performance criteria and back-testing strategies Includes two appendices that support the main material in the book If you're unprepared to enter today's markets you will underperform. But with Financial Markets and Trading as your guide, you'll quickly discover what it takes to make it in this competitive field.

Book Synopsis Financial Markets and Trading by : Anatoly B. Schmidt

Download or read book Financial Markets and Trading written by Anatoly B. Schmidt and published by John Wiley & Sons. This book was released on 2011-07-05 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: An informative guide to market microstructure and trading strategies Over the last decade, the financial landscape has undergone a significant transformation, shaped by the forces of technology, globalization, and market innovations to name a few. In order to operate effectively in today's markets, you need more than just the motivation to succeed, you need a firm understanding of how modern financial markets work and what professional trading is really about. Dr. Anatoly Schmidt, who has worked in the financial industry since 1997, and teaches in the Financial Engineering program of Stevens Institute of Technology, puts these topics in perspective with his new book. Divided into three comprehensive parts, this reliable resource offers a balance between the theoretical aspects of market microstructure and trading strategies that may be more relevant for practitioners. Along the way, it skillfully provides an informative overview of modern financial markets as well as an engaging assessment of the methods used in deriving and back-testing trading strategies. Details the modern financial markets for equities, foreign exchange, and fixed income Addresses the basics of market dynamics, including statistical distributions and volatility of returns Offers a summary of approaches used in technical analysis and statistical arbitrage as well as a more detailed description of trading performance criteria and back-testing strategies Includes two appendices that support the main material in the book If you're unprepared to enter today's markets you will underperform. But with Financial Markets and Trading as your guide, you'll quickly discover what it takes to make it in this competitive field.

Markets in Higher Education

Author: Pedro Teixeira

Publisher: Springer Science & Business Media

Published: 2006-08-01

Total Pages: 361

ISBN-13: 1402028350

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This volume presents the most comprehensive international discussion yet on the role of markets in higher education. It considers both the political and economic implications of the rising trend towards introducing market elements in higher education. The book draws together leading international scholars in higher education to explore different theoretical perspectives and present new empirical evidence on market mechanisms in higher education in several Western countries.

Book Synopsis Markets in Higher Education by : Pedro Teixeira

Download or read book Markets in Higher Education written by Pedro Teixeira and published by Springer Science & Business Media. This book was released on 2006-08-01 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents the most comprehensive international discussion yet on the role of markets in higher education. It considers both the political and economic implications of the rising trend towards introducing market elements in higher education. The book draws together leading international scholars in higher education to explore different theoretical perspectives and present new empirical evidence on market mechanisms in higher education in several Western countries.

Machine Learning for Algorithmic Trading

Author: Stefan Jansen

Publisher: Packt Publishing Ltd

Published: 2020-07-31

Total Pages: 822

ISBN-13: 1839216786

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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 : 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.