{"product_id":"quantitative-trading-strategies-using-python-technical-analysis-statistical-testing-and-machine-learning-paperback","title":"Quantitative Trading Strategies Using Python: Technical Analysis, Statistical Testing, and Machine Learning - Paperback","description":"\u003cp\u003eby \u003cb\u003ePeng Liu\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eBuild and implement trading strategies using Python. This book will introduce you to the fundamental concepts of quantitative trading and shows how to use Python and popular libraries to build trading models and strategies from scratch. It covers practical trading strategies coupled with step-by-step implementations that touch upon a wide range of topics, including data analysis and visualization, algorithmic trading, backtesting, risk management, optimization, and machine learning, all coupled with practical examples in Python.\u003c\/p\u003e\u003cp\u003ePart one of \u003ci\u003eQuantitative Trading Strategies with Python\u003c\/i\u003e covers the fundamentals of trading strategies, including an introduction to quantitative trading, the electronic market, risk and return, and forward and futures contracts. Part two introduces common trading strategies, including trend-following, momentum trading, and evaluation process via backtesting. Part three covers more advanced topics, including statistical arbitrage using hypothesis testing, optimizing trading parameters using Bayesian optimization, and generating trading signals using a machine learning approach. \u003c\/p\u003e\u003cp\u003eWhether you're an experienced trader looking to automate your trading strategies or a beginner interested in learning quantitative trading, this book will be a valuable resource. Written in a clear and concise style that makes complex topics easy to understand, and chock full of examples and exercises to help reinforce the key concepts, you'll come away from it with a firm understanding of core trading strategies and how to use Python to implement them.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eWhat You Will Learn\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eMaster the fundamental concepts of quantitative trading\u003c\/li\u003e\n\u003cli\u003eUse Python and its popular libraries to build trading models and strategies from scratch\u003c\/li\u003e\n\u003cli\u003ePerform data analysis and visualization, algorithmic trading, backtesting, risk management, optimization, and machine learning for trading strategies using Python\u003c\/li\u003e\n\u003cli\u003eUtilize common trading strategies such as trend-following, momentum trading, and pairs trading\u003c\/li\u003e\n\u003cli\u003eEvaluate different quantitative trading strategies by applying the relevant performance measures and statistics in a scientific manner during backtesting\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eWho This Book Is For\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003eAspiring quantitative traders and analysts, data scientists interested in finance, and researchers or students studying quantitative finance, financial engineering, or related fields.\u003c\/p\u003e\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003eBuild and implement trading strategies using Python. This book will introduce you to the fundamental concepts of quantitative trading and shows how to use Python and popular libraries to build trading models and strategies from scratch. It covers practical trading strategies coupled with step-by-step implementations that touch upon a wide range of topics, including data analysis and visualization, algorithmic trading, backtesting, risk management, optimization, and machine learning, all coupled with practical examples in Python.\u003c\/p\u003e\u003cp\u003ePart one of \u003ci\u003eQuantitative Trading Strategies with Python\u003c\/i\u003e covers the fundamentals of trading strategies, including an introduction to quantitative trading, the electronic market, risk and return, and forward and futures contracts. Part II introduces common trading strategies, including trend-following, momentum trading, and evaluation process via backtesting. Part III covers more advanced topics, including statistical arbitrage using hypothesis testing, optimizing trading parameters using Bayesian optimization, and generating trading signals using a machine learning approach.\u003c\/p\u003e\u003cp\u003eWhether you're an experienced trader looking to automate your trading strategies or a beginner interested in learning quantitative trading, this book will be a valuable resource. Written in a clear and concise style that makes complex topics easy to understand, and chock full of examples and exercises to help reinforce the key concepts, you'll come away from it with a firm understanding of core trading strategies and how to use Python to implement them.\u003c\/p\u003e\u003cp\u003eYou will: \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eMaster the fundamental concepts of quantitative trading\u003c\/li\u003e\n\u003cli\u003eUse Python and its popular libraries to build trading models and strategies from scratch\u003c\/li\u003e\n\u003cli\u003ePerform data analysis and visualization, algorithmic trading, backtesting, risk management, optimization, and machine learning for trading strategies using Python\u003c\/li\u003e\n\u003cli\u003eUtilize common trading strategies such as trend-following, momentum trading, and pairs trading\u003c\/li\u003e\n\u003cli\u003eEvaluate different quantitative trading strategies by applying the relevant performance measures and statistics in a scientific manner during backtesting\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003ePeng Liu\u003c\/b\u003e is an assistant professor of quantitative finance (practice) at Singapore Management University and an adjunct researcher at the National University of Singapore. He holds a Ph.D. in statistics from the National University of Singapore and has ten years of working experience as a data scientist across the banking, technology, and hospitality industries. Peng is the author of \u003ci\u003eBayesian Optimization\u003c\/i\u003e (Apress, 2023).\u003cbr\u003e\u003c\/p\u003e\u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 337\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.73 x 10 x 7 IN\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e September 10, 2023\u003c\/div\u003e","brand":"Books by splitShops","offers":[{"title":"Default Title","offer_id":42704482074687,"sku":"9781484296745","price":71.26,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0105\/8226\/1823\/files\/0e1f4e080311f3f79b5d863649e6010c.webp?v=1765033407","url":"https:\/\/dhlswag.com\/products\/quantitative-trading-strategies-using-python-technical-analysis-statistical-testing-and-machine-learning-paperback","provider":"BBB","version":"1.0","type":"link"}