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