This course will teach participants how to work with financial data, and learn to import real-time data from various sources, to design and backtest various algorithmic trading strategies. We will begin with a brief review of Python’s fundamental concepts. Using finance related exercises, we will review working with variables, logic, and looping. Then we will learn how to pull in live data via Pandas Data Reader and how to use API keys to pull in various types of data including stock prices, commodity prices, real estate prices, economic data, cryptocurrencies, ESG data, and more.
Next, we will develop trading strategies to backtest. We will focus on six types of trading strategies in this course: simple moving averages, momentum, mean reversion, linear regression, machine learning, and deep learning: neural networks.
Throughout the course, we will use NumPy and Pandas to perform complex mathematical functions on the large datasets, taking advantage of Python’s ability to apply vectorization, making the code run quickly and efficiently. We will use MatPlotLib and Plotly to visualize our datasets and the trading strategy results. Sci-kit learn, Keras, and TensorFlow will be used for the machine learning and deep learning trading strategies.
Course Objectives
By the end of the course, participants will be able to:
- Work with variables, logic, and looping in Python
- Use popular commands and tools in many important libraries
- NumPy, Pandas, Pandas-datareader, MatPlotLib, Plotly, Quandl, Scikit-learn, Keras, and TensorFlow
- Import public financial data, and use API keys to get data from the web
- Explain a variety of trading strategies and related concepts
- Perform calculations to create trade signals and calculate returns
- Build trading strategies and backtest them
- Calculate the gross performance of each strategy
- Run linear regression and use it on any number of lagged values
- Use machine learning and neural networks to predict market direction
- Evaluate and visualize strategy performance
Suggested Prerequisites: Introduction to Python
Program Level: Intermediate
Advance Preparation: Participants must have Python and Spyder which come with the Anaconda distribution: https://www.anaconda.com/download/. If Python was installed via Anaconda Distribution, you will already have many of the packages that we need for this course.
Computers and Financial Calculators: Computers and Microsoft Excel
Recommended CPE Credits: 12