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Course Outline

Introduction

Configuring the Development Environment

  • Local programming versus online environments: Anaconda and Jupyter

Python Programming Essentials

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

Enhancing Python's Functionality

  • Modules and Packages

Developing Your First Python Application

  • Calculating initial and final dates and times

Retrieving External Data via Python

  • Importing and exporting, as well as reading and writing CSV data
  • Connecting to and retrieving data from SQL databases

Structuring Data with Arrays and Vectors in Python

  • NumPy and vectorized operations

Data Visualization with Python

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

Data Analysis using Python

  • Analyzing data with 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 assessment

Risk Assessment and Investment Performance

  • Formulating and resolving portfolio optimization problems

Fixed-Income Analysis and Option Pricing

  • Carrying out fixed-income analysis and pricing options

Financial Time Series Analysis

  • Evaluating time series data within financial markets

Deploying Your Python Application for Production

  • Connecting your application to Excel and other web-based tools

Application Performance

  • Optimizing your application
  • Parallel Computing and Multiprocessing

Troubleshooting

Conclusion

Requirements

  • Familiarity with financial concepts (such as securities and derivatives)
  • A basic grasp of probability and statistics
  • Foundational knowledge of differential and integral calculus
 35 Hours

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