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Course Outline

Introduction

Establishing the Development Environment

  • Local programming versus online platforms: Anaconda and Jupyter

Python Programming Essentials

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

Expanding Python's Capabilities

  • Utilizing Modules and Packages

Building Your First Python Application

  • Calculating start and end dates and times

Retrieving External Data with Python

  • Importing and exporting data; reading and writing CSV files
  • Accessing data stored in SQL databases

Structuring Data Using Arrays and Vectors in Python

  • NumPy and vectorized operations

Data Visualization with Python

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

Data Analysis with Python

  • Statistical analysis using scipy.stats and pandas
  • Importing and exporting financial data (from Excel, websites, etc.)

Simulating Asset Price Movements

  • Monte Carlo simulation

Asset Allocation and Portfolio Optimization

  • Executing capital allocation, asset allocation, and risk evaluation

Risk Analysis 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

  • Analyzing time series data within financial markets

Deploying Your Python Application to Production

  • Integrating your application with Excel and other web-based tools

Optimizing Application Performance

  • Refining application efficiency
  • Parallel Computing and Multiprocessing

Troubleshooting

Conclusion

Requirements

  • Familiarity with finance concepts (such as securities and derivatives)
  • A solid grasp of probability and statistics
  • Basic knowledge of differential and integral calculus
 35 Hours

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