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Course Outline

Introduction

Setting up the Development Environment

  • Local programming versus online environments: Anaconda and Jupyter

Python Programming Fundamentals

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

Extending Python's Capabilities

  • Utilizing modules and packages

Building Your First Python Application

  • Calculating start and end dates and times

Accessing External Data with Python

  • Importing, exporting, reading, and writing CSV data
  • Retrieving data from SQL databases

Organizing Data Using Arrays and Vectors in Python

  • NumPy and vectorized operations

Visualizing Data with Python

  • Creating 2D and 3D plots with Matplotlib, pyplot, and SciPy

Analyzing Data with Python

  • Performing data analysis using scipy.stats and pandas
  • Importing and exporting financial data from Excel, websites, and other sources

Simulating Asset Price Trajectories

  • Implementing Monte Carlo simulations

Asset Allocation and Portfolio Optimization

  • Executing capital allocation, asset allocation, and risk assessment

Risk Analysis and Investment Performance

  • Formulating and solving portfolio optimization problems

Fixed-Income Analysis and Option Pricing

  • Conducting fixed-income analysis and pricing options

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 platforms

Application Performance

  • Optimizing application efficiency
  • Parallel computing and multiprocessing

Troubleshooting

Closing Remarks

Requirements

  • Familiarity with financial concepts, including securities and derivatives
  • A foundational understanding of probability and statistics
  • Basic knowledge of differential and integral calculus
 35 Hours

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