LEADER 04471nam 22006015 450 001 9910746096203321 005 20251008165002.0 010 $a9781484296752 010 $a1484296753 024 7 $a10.1007/978-1-4842-9675-2 035 $a(MiAaPQ)EBC30736797 035 $a(Au-PeEL)EBL30736797 035 $a(DE-He213)978-1-4842-9675-2 035 $a(OCoLC)1397574030 035 $a(OCoLC-P)1397574030 035 $a(PPN)272740950 035 $a(CaSebORM)9781484296752 035 $a(CKB)28172720800041 035 $a(Perlego)4515823 035 $a(EXLCZ)9928172720800041 100 $a20230909d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aQuantitative Trading Strategies Using Python $eTechnical Analysis, Statistical Testing, and Machine Learning /$fby Peng Liu 205 $a1st ed. 2023. 210 1$aBerkeley, CA :$cApress :$cImprint: Apress,$d2023. 215 $a1 online resource (341 pages) 300 $aDescription based upon print version of record. 300 $aImplementing the Momentum Trading Strategy 311 08$a9781484296745 311 08$a1484296745 327 $aChapter 1: Introduction to Quantitative Trading -- Chapter 2: Understanding the Electronic Market -- Chapter 3: Understanding Risk and Return -- Chapter 4: Forward and Futures Contracts -- Chapter 5: Trend Following Strategy -- Chapter 6: Momentum Trading Strategy -- Chapter 7: Backtesting A Trading Strategy -- Chapter 8: Statistical Arbitrage with Hypothesis Testing -- Chapter 9: Optimizing Trading Strategies with Bayesian Optimization -- Chapter 10: Optimizing Trading Strategies with Machine Learning. 330 $aBuild 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. Part one of Quantitative Trading Strategies with Python 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 hypothesistesting, optimizing trading parameters using Bayesian optimization, and generating trading signals using a machine learning approach. Whether 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. You will: Master the fundamental concepts of quantitative trading Use Python and its popular libraries to build trading models and strategies from scratch Perform data analysis and visualization, algorithmic trading, backtesting, risk management, optimization, and machine learning for trading strategies using Python Utilize common trading strategies such as trend-following, momentum trading, and pairs trading Evaluate different quantitative trading strategies by applying the relevant performance measures and statistics in a scientific manner during backtesting. 606 $aPython (Computer program language) 606 $aFinancial services industry 606 $aPython 606 $aFinancial Services 615 0$aPython (Computer program language) 615 0$aFinancial services industry. 615 14$aPython. 615 24$aFinancial Services. 676 $a005.133 700 $aLiu$b Peng$01271805 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910746096203321 996 $aQuantitative Trading Strategies Using Python$93562740 997 $aUNINA