- eBook:Hands-On Algorithmic Trading with Python: A practical guide to using NumPy, pandas, Matplotlib, and Quantopian for automated trading
- Author:Sourav Ghosh
- Data:May 11, 2021
- Pages:489 pages
- Format:PDF, ePUB
- Get to grips with financial statistics and stock analysis and visualize data to gain quality insights
- Find out how to systematically approach quantitative research and strategy generation in automated trading
- Learn how to navigate significant number of features in Python data manipulation libraries
Book DescriptionAlgorithmic trading, also known as automated trading, helps you stay ahead of the market by devising strategies in quantitative analysis to gain profits and cut losses. This book will help you to understand financial theories and execute a range of algorithmic trading strategies confidently.
The book starts by introducing you to algorithmic trading, the pyfinance ecosystem, and Quantopian. You'll then cover algorithmic trading and quantitative analysis using Python, and learn how to build algorithmic trading strategies on Quantopian. As you advance, you'll gain an in-depth understanding of Python libraries such as NumPy and pandas for analyzing financial datasets, and also explore Matplotlib, statsmodels, and scikit-learn libraries for advanced analytics. Moving on, you'll explore useful financial concepts and theories such as financial statistics, leveraging and hedging, and short selling that will help you understand how financial markets operate. Finally, you will discover mathematical models and approaches for analyzing and understanding financial time series data.
By the end of this trading book, you will be able to build predictive trading signals, adopt basic and advanced algorithmic trading strategies, and perform portfolio optimization on the Quantopian platform.
What you will learn
- Understand key financial theories such as the market hypothesis, the capital asset pricing model, and portfolio optimization
- Discover how quantitative analysis works, covering key techniques like financial statistics and ARIMA models
- Use core Python libraries to perform quantitative research and strategy development using real datasets
- Perform quantitative research on Quantopian financial datasets
- Build and deploy algo trading strategies
- Assemble Python libraries with backtesting frameworks and explore financial concepts to master quantitative trading
Who This Book Is ForThis book is for data analysts and financial traders who want to explore algo trading using Python core libraries. If you are looking for a practical guide to execute various algorithmic trading strategies, then this book is for you. Basic working knowledge of Python programming and statistics will be helpful.
1. Introduction to Algorithmic Trading
Section 2: In-Depth Look at Python Libraries for the Analysis of Financial Datasets
2. Exploratory Data Analysis in Python
3. High-Speed Scientific Computing Using NumPy
4. Data Manipulation and Analysis with pandas
5. Data Visualization Using Matplotlib
6. Statistical Estimation, Inference, and Prediction
Section 3: Algorithmic Trading in Python
7. Financial Market Data Access in Python
8. Introduction to Zipline and PyFolio
9. Fundamental Algorithmic Trading Strategies