In this tutorial, you’ll learn how to get started with Python for finance. The tutorial will cover the following:
- The basics that you need to get started: for those who are new to finance, you’ll first learn more about trading strategies, what time series data is and what you need to set up your workspace.
- An introduction to time series data and some of the most common financial analyses, such as moving windows, volatility calculation, … with the Python package Pandas.
- The development of a simple momentum strategy: you’ll first go through the development process step-by-step and start by formulating and coding up a simple algorithmic trading strategy.
- Next, you’ll backtest the formulated trading strategy with Pandas, zipline and Quantopian.
- Afterward, you’ll see how you can do optimizations to your strategy to make it perform better, and you’ll eventually evaluate your strategy’s performance and robustness.
Note: In every DataCamp exercise, you are writing and running real R, Python, or SQL code. You won’t just learn the theory, you’ll get hands-on experience exploring real data sets in courses covering the entire data science workflow.
https://www.datacamp.com/community/tutorials?posts_selected_tab=must_read
