ShiveshM / python_for_finance

Mastering Python for Finance

Mastering Python for Finance

This module wraps into standalone functions the contents of James Ma Weiming's "Mastering Python for Finance", published by Packt.

Chapters

1. Overview of Financial Analysis with Python
   • Introduction to Quandl
   • Plotting a time series chart
   • Performing financial analysis on time series data
2. Importance of Linearity in Finance
   • The Captial Asset Pricing Model and the security market line
   • The Arbitrage Pricing Theory Model
   • Multivariate linear regression of factors
   • Linear optimization
   • Solving linear equations using matrices
   • The LU decomposition
   • The Cholesky decomposition
   • The QR decomposition
   • Solving with other matrix algebra methods
3. Nonlinearity in Finance
   • Nonlinearity modeling
   • Root-finding algorithms
   • SciPy implementations in root-finding
4. Numerical Methods for Pricing Options
   • Binomial trees in option pricing
   • Pricing European and American options
   • The Greeks for free
   • Trinomial trees in option pricing
   • Lattices in option pricing
   • Finite differences in option pricing

Dependencies

• Python >= 3.7
• NumPy
• SciPy
• Pandas
• Quandl
• PuLP
• statsmodels

Usage

Overview of chapters is given above. To run all code for a particular chapter, e.g. chapter 1, simply run

python chap1.py

To specify a particular method(s), then enter the name of the method after the filename, e.g. to run the methods plot_time_series and correlation inside chap1.py, do

python chap1.py plot_time_series correlation