Use of Excel in Financial Risk Modeling: Scenario Analysis, Monte Carlo Simulation, and Stress Testing with Python in Excel

About the Course:

Financial models rarely behave as neatly as their spreadsheets suggest. In this 90-minute session, you will learn how to use Excel together with Python to measure, simulate, and visualize financial risk.

We will start with Excel’s built-in scenario and sensitivity tools, then bring in Python in Excel to create scalable Monte Carlo simulations that run thousands of trials in seconds. You will learn how to generate random variables, calculate expected outcomes, and visualize probability distributions directly within Excel.

The session concludes with practical stress testing examples that demonstrate how portfolios or projects respond to extreme market conditions. Every example is built inside Excel 365 using Python, making the techniques immediately usable in real-world finance workflows.

Course Objectives:

By the end of this session, participants will be able to:

• Understand the role of uncertainty and risk in financial modeling
• Create structured scenarios and sensitivity analyses in Excel
• Use Python in Excel to build Monte Carlo simulations for financial forecasts
• Generate and visualize random data using NumPy and Matplotlib inside Excel
• Design and interpret stress tests for extreme financial conditions
• Integrate simulation results into dashboards and reports

Who is the Target Audience?

• Finance, accounting, and investment professionals who model uncertainty in Excel
• Analysts and managers are ready to explore Python within Excel for deeper analytics
• Educators and trainers teaching modern Excel modeling techniques

Basic Knowledge:

• Intermediate Excel skills, including formulas and charts
• Familiarity with basic financial modeling concepts
• No prior programming experience required. All Python code runs directly inside Excel cells