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financial_analytics_python's Introduction

Financial Analytics with Python

Part 1

  1. Notebook and Python Introduction
  2. NumPy

Part 2

  1. Pandas - Introduction to Data Structure

  2. Pandas - Basic Functions

  3. Pandas - Computational Tools

  4. Pandas - IO Tools

  5. Pandas - Working with Text, Merge, Join and Concatenate and Pivot Table

  6. Pandas - Split, Apply and Combine

  7. Pandas - Categorical Data

  8. Pandas - Time Series

  9. Pandas - Visualisation

Part 3

  1. Matplotlib

  2. Seaborn

Part 4

  1. Financial Applications
  • Python as a Financial Calculator
    • Time Value of Money
    • Call Option (Scipy and Numpy)
  • Intro to Numpy and Scipy - Linear Regression, CAPM (Numpy, matplotlib, scipy, statsmodel)
  • Risk and Returns (Pandas, Matplotlib, Bokeh)
    • Return Distribution
    • Comparing return versus volatility for several stocks
  • Time Series Analysis (Pandas, Scipy)
    • Bartlett’s test for equal variances
    • Levene test for equal variances
    • Jan Month Effect
    • Fama-French
    • Rolling Beta
    • Efficient Frontier
    • Optimization
    • Portfolio Optimisation

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Contributors

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