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Quantitative trading strategies using Python : technical analysis, statistical testing, and machine learning /
"Build 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-...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
[Berkeley, CA] :
Apress,
[2023]
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Liu, Peng, |e author. | |
| 245 | 1 | 0 | |a Quantitative trading strategies using Python : |b technical analysis, statistical testing, and machine learning / |c Peng Liu. |
| 264 | 1 | |a [Berkeley, CA] : |b Apress, |c [2023] | |
| 300 | |a 1 online resource (xi, 337 pages) : |b illustrations (chiefly color) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 500 | |a Place of publication from publisher's website. | ||
| 504 | |a Includes index. | ||
| 505 | 0 | |a Intro -- Table of Contents -- About the Author -- About the Technical Reviewer -- Chapter 1: Quantitative Trading: An Introduction -- Overview of Quantitative Trading -- Model Development Workflow -- Institutional Algorithmic Trading -- Being a Quant Trader -- Major Asset Classes and Derivatives -- Grouping Tradable Assets -- Common Trading Avenues and Steps -- Market Structures -- Major Types of Buy-Side Stock Investors -- Market Making -- Scalping -- Portfolio Rebalancing -- Getting Started with Financial Data Analysis -- Summarizing Stock Prices -- Downloading Stock Price Data | |
| 505 | 8 | |a Visualizing Stock Price Data -- Summary -- Exercises -- Chapter 2: Electronic Market -- Introducing Electronic Market -- Electronic Order -- Proprietary and Agency Trading -- Order Matching Systems -- Market Order -- Limit Order -- Limit Order Book -- Display vs. Non-display Orders -- Stop Order -- Stop-Limit Order -- Pegged Order -- Trailing Stop Order -- Market If Touched Order -- Summarizing Major Types of Orders -- More Order Types: Limit and Cancelation -- Price Impact -- Order Flow -- Working with LOB Data -- Understanding Label Distribution -- Understanding Price-Volume Data | |
| 505 | 8 | |a Visualizing Price Movement -- Summary -- Exercises -- Chapter 3: Forward and Futures Contracts -- Introducing Forward and Futures Contracts -- Parameters of a Futures Contract -- Hedging and Speculation -- Obligations at Maturity -- Leverage in a Futures Contract -- Clearing House -- Mark-to-Market -- Pricing Forward Contract -- Pricing Futures Contract -- Contango and Backwardation -- Working with Futures Data -- Adding Technical Indicators -- Summary -- Exercises -- Chapter 4: Understanding Risk and Return -- Risk and Return Trade-Off -- Analyzing Returns -- Working with Dummy Returns | |
| 505 | 8 | |a The 1+R Format -- The Terminal Return -- Stock Return with Dividends -- Multiperiod Return -- Annualizing Returns -- Calculating Single-Period Returns from Price Data -- Calculating Two-Period Terminal Return -- Calculating Annualized Returns -- Analyzing Risk -- Introducing Variance and Standard Deviation -- Annualizing Volatility -- Combining Risk and Return via the Sharpe Ratio -- Working with Stock Price Data -- Calculating the Mean, Variance, and Standard Deviation -- Calculating the Annualized Volatility -- Calculating the Annualized Returns -- Calculating the Sharpe Ratio -- Summary | |
| 505 | 8 | |a Exercises -- Chapter 5: Trend-Following Strategy -- Working with Log Returns -- Analyzing Stock Prices Using Log Returns -- Introducing Trend Trading -- Understanding Technical Indicators -- Introducing Moving Averages -- Delving into Simple Moving Averages -- Delving into Exponential Moving Averages -- Implementing the Trend-Following Strategy -- Summary -- Exercises -- Chapter 6: Momentum Trading Strategy -- Introducing Momentum Trading -- Diving Deeper into Momentum Trading -- Contrasting with the Trend-Following Strategy -- Observing the Role of Lookback Windows -- More on Trend Following | |
| 505 | 8 | |a Implementing the Momentum Trading Strategy | |
| 520 | |a "Build 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 two introduces common trading | ||
| 520 | |a 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. 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. What You Will Learn Master the fundamental concepts of quantitative | ||
| 520 | |a 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 Who This Book Is For Aspiring quantitative traders and analysts, data scientists interested in finance, and researchers or students studying quantitative finance, financial engineering, or related fields." -- |c Provided by publisher. | ||
| 588 | |a Description based on online resource; title from digital title page (viewed on October 16, 2023). | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Electronic trading of securities. | |
| 650 | 0 | |a Python (Computer program language) | |
| 776 | 0 | 8 | |i Print version: |a Liu, Peng |t Quantitative Trading Strategies Using Python |d Berkeley, CA : Apress L. P.,c2023 |z 9781484296745 |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781484296752/?ar |z Texto completo (Requiere registro previo con correo institucional) |
| 938 | |a ProQuest Ebook Central |b EBLB |n EBL30736797 | ||
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| 938 | |a EBSCOhost |b EBSC |n 3676754 | ||
| 994 | |a 92 |b IZTAP | ||