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 Duration 35 hours

Course Outline

Introduction

Configuring the Development Environment

  • Local versus online programming: Anaconda and Jupyter

Python Programming Essentials

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

Expanding Python Functionality

  • Modules and Packages

Creating Your First Python Application

  • Calculating initial and final dates and times

Retrieving External Data via Python

  • Importing/exporting and reading/writing CSV data
  • Querying data within an SQL database

Structuring Data with Arrays and Vectors in Python

  • NumPy and vectorized operations

Data Visualization in Python

  • Using Matplotlib for 2D and 3D plots, pyplot, and SciPy

Data Analysis in Python

  • Performing analysis with scipy.stats and pandas
  • Importing/exporting financial data (Excel, web data, etc.)

Simulating Asset Price Movements

  • Monte Carlo simulation

Asset Allocation and Portfolio Optimization

  • Executing capital allocation, asset allocation, and risk assessment

Risk Assessment and Investment Performance

  • Formulating and resolving portfolio optimization problems

Fixed-Income Analysis and Option Valuation

  • Conducting fixed-income analysis and option pricing

Financial Time Series Analysis

  • Examining time series data in financial markets

Deploying Python Applications to Production

  • Integrating applications with Excel and other web-based systems

Application Performance

  • Enhancing application efficiency
  • Parallel computing and multiprocessing

Troubleshooting

Conclusion

Requirements

  • A foundational knowledge of finance (including securities, derivatives, etc.)
  • A general grasp of probability and statistics
  • Basic understanding of differential and integral calculus

Testimonials (3)

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