Python for Finance: Financial Analysis for Investing

Python for Finance: Financial Analysis for Investing

Use Python to Find Good Investments and when to Buy and Sell. Learn Pandas, NumPy, Matplotlib for Financial Analysis

What you’ll learn

  • How to automate financial analysis with Python using Pandas and Numpy
  • Learn to find attractive companies to invest in using fundamental analysis with Pandas
  • Identify when to buy and sell stocks based on technical analysis using Pandas and Numpy
  • Export your financial analysis to Excel in formatted multi sheets
  • How to calculate a fair price (intrinsic value) of a stock with Python using Pandas
  • Introduction to Pandas, Numpy and Visualization of financial data
  • Use Monte Carlo simulation to optimize your portfolio allocation
  • Understand risk when buying stock shares
  • Learn how to evaluate an investment to lower the risk
  • Learn about Intrinsic value, Market value, Book value, and Shares
  • Master the concepts Dividend, Earnings per share (EPS), Price/Earnings (PE) ratio, and Volume Yield
  • Cover a Python Crash Course with all the basic Python
  • How to use DataFrames for financial analysis
  • Use Matplotlib to visualize DataFrames with time series data
  • How to join, merge and concatenate DataFrame
  • Export data from Python to Excel in nice colorful sheets with charts
  • Calculate concrete intrinsic values (a fair price to buy a stock for) for 50 companies
  • Read and interpret Dept/Equity (DE) ratio, Current ratio, Return of Investment (ROI) and more
  • Use revenue, Earnings-per-share (EPS), and Book value to determine if a company is predictable and worth investing in.
  • How to use Price/Earnings (PE) ratio to make calculations
  • How to use Pandas Datareader to read data directly form API of financial pages
  • To read financial statements from API’s
  • Web scraping of pages and how to convert data to correct format and types
  • How to calculate rate of return (RoR), percentage change, and to normalize stock price data
  • Understand and learn to calculate the CAGR (Compound Annual Growth Rate)
  • A deep dive case study of DOW theory
  • How to calculate technical indicators, like, Moving Average (MA), MACD, Stochastic Oscillator, and more
  • Make financial calculations with NumPy
  • Calculate with vectors and matrices using NumPy
  • How to calculate the Volatility of a stock
  • Correlation and Linear Regression between securities between investments
  • How the Beta is used and how to calculate it
  • Deep dive into using CAPM
  • Optimize your portfolio of investments
  • Learn what Sharpe Ratio is and how to use it
  • How to use Monte Carlo Simulation to simulate random variables
  • Use Sharpe Ratio and Monte Carlo Simulation to calculate the Efficient Frontier
  • Advice on next books to read about investing


  • Some knowledge of programming is recommended
  • All software and data used in course is free
  • Ability to install Anaconda (guide in course)

Who this course is for:

  • Someone that wants to learn about financial analysis with Python
  • Anyone that wants to start data science on financial data
  • Programmers that want to learn about finance and investing
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