Quantitative Trading Strategies Using Python : Technical Analysis, Statistical Testing, and Machine Learning

✍ Scribed by Peng Liu

Publisher: Apress
Year: 2023
Tongue: English
Leaves: 341
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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 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 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.

✦ Table of Contents

Pages i-xi

Quantitative Trading: An Introduction
    Peng Liu 
Pages 1-33
Electronic Market
    Peng Liu 
Pages 35-75
Forward and Futures Contracts
    Peng Liu 
Pages 77-105
Understanding Risk and Return
    Peng Liu 
Pages 107-140
Trend-Following Strategy
    Peng Liu 
Pages 141-174
Momentum Trading Strategy
    Peng Liu 
Pages 175-196
Backtesting a Trading Strategy
    Peng Liu 
Pages 197-223
Statistical Arbitrage with Hypothesis Testing
    Peng Liu 
Pages 225-255
Optimizing Trading Strategies with Bayesian Optimization
    Peng Liu 
Pages 257-301
Pairs Trading Using Machine Learning
    Peng Liu 
Pages 303-325
Back Matter
Pages 327-337

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