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.
General
Imprint: |
Apress
|
Country of origin: |
United States |
Release date: |
September 2023 |
First published: |
2023 |
Authors: |
Peng Liu
|
Dimensions: |
254 x 178mm (L x W) |
Pages: |
270 |
ISBN-13: |
978-1-4842-9674-5 |
Categories: |
Books
|
LSN: |
1-4842-9674-5 |
Barcode: |
9781484296745 |
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