Python Programming for Finance
This course will teach you the essential elements of Python to build practically useful applications and conduct data analysis for finance.
This course is a component of the Data Analysis and Programming for Finance Professional Certificate.
Prerequisite knowledge:
- Basic probability and statistics
- Some familiarity with financial securities and derivatives
- Elementary differential and integral calculus
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To make it even easier to learn, you can finance your program through Affirm.
Loans offered through Affirm are available in the U.S. and Canada.
Module 1: Introduction to Python
- The Anaconda Python distribution
- Interactive programming: IPython and Jupyter notebooks
- Programming: control structures, data types, functions, data structures
- Modules and Packages
Module 2: Essential Python Toolkit
- Date and time management : format, measuring time lapse, etc.
- How to build and run a standalone application
- Parsing command line arguments
- Importing/Exporting files
- Reading and writing in CSV format
- Accessing SQL databases
- Multiprocessing
- Using a dictionary for explicit indexing
Module 3: Arrays, Vectorization and Random NUmbers
- NumPy: array processing
- Vectorized functions
- Random number generation
Module 1: Scientific Computing with Python
- Matplotlib: 2D and 3D plotting
- Using pyplot
- SciPy: scientific computing
- Root finding, interpolation, integration and optimization
Module 2: Data Analysis with Python
- Data analysis with scipy.stats and pandas
- Pandas data structures: series and data frames
- Importing and exporting data from/to MS Excel
- Importing data from websites
Module 1: Python Applications
- Monte Carlo simulation basics
- Simulating asset price trajectories
- Smoothing using Kalman Filter
- Exercise: Stock Correlation Prediction
Module 2: Python Applications
- Time Series Analysis using Advanced Python Libraries
- Value-At-Risk (VAR) Calculation using Var/Cov Model