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Course Outline

Introduction

Configuring the Development Environment

  • Local versus online programming: Anaconda and Jupyter

Python Programming Basics

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

Expanding Python's Functionality

  • Modules and Packages

Creating Your First Python Application

  • Calculating start and end dates and times

Retrieving External Data with Python

  • Importing and exporting, as well as reading and writing CSV data
  • Interacting with data in SQL databases

Structuring Data with Arrays and Vectors in Python

  • NumPy and vectorized functions

Data Visualization with Python

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

Data Analysis with Python

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

Simulating Asset Price Movements

  • Monte Carlo simulation

Asset Allocation and Portfolio Optimization

  • Executing capital allocation, asset allocation, and risk assessment

Risk Analysis and Investment Performance

  • Formulating and resolving portfolio optimization problems

Fixed-Income Analysis and Option Pricing

  • Carrying out fixed-income analysis and option pricing

Financial Time Series Analysis

  • Analyzing time series data within financial markets

Deploying Your Python Application to Production

  • Integrating your application with Excel and other web applications

Application Performance

  • Optimizing your application
  • Parallel Computing and Multiprocessing

Troubleshooting

Conclusion

Requirements

  • Knowledge of financial concepts (securities, derivatives, etc.)
  • A solid grasp of probability and statistics
  • Basic skills in differential and integral calculus
 35 Hours

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