Python Programming for Finance Training Course

Introduction

Setting up the Development Environment

• Programming locally vs online: Anaconda and Jupyter

Python Programming Fundamentals

• Control structures, data types, functions, data structures and operators

Extending Python's Capabilities

• Modules and Packages

Your first Python Application

• Estimating beginning and ending dates and times

Accessing External Data with Python

• Importing and exporting, reading and writing CSV data
• Accessing data in an SQL database

Organizing Data Using Arrays and Vectors in Python

• NumPy and vectorized functions

Visualizing Data with Python

• Matplotlib for 2D and 3D plotting, pyplot, and SciPy

Analyzing Data with Python

• Data analysis with scipy.stats and pandas
• Importing and exporting financial data (Excel, website data, etc.)

Simulating Asset Price Trajectories

• Monte Carlo simulation

Asset Allocation and Portfolio Optimization

• Performing capital allocation, asset allocation, and risk assessment

Risk Analysis and Investment Performance

• Defining and solving portfolio optimization problems

Fixed-Income Analysis and Option Pricing

• Performing fixed-income analysis and option pricing

Financial Time Series Analysis

• Analyzing time series data in financial markets

Taking Your Python Application into Production

• Integrating your application with Excel and other web applications

Application Performance

• Optimizing your application
• Parallel Computing and Multiprocessing

Troubleshooting

Closing Remarks