Advanced Financial Modeling Using Excel and Python

COURSE OBJECTIVES

• Equip participants with advanced financial modeling skills using Excel and Python.
• Enhance ability to build, analyze, and automate complex financial models.
• Strengthen forecasting, valuation, optimization, and scenario-analysis capabilities.
• Apply Python for data automation, analytics, and model enhancement.
• Improve decision-making through data-driven financial insights.

COURSE OUTLINE

Introduction to Advanced Financial Modeling

• Principles of robust financial models
• Model structure, logic flow, and best practices
• Integrating Excel and Python for modeling

Advanced Excel for Financial Modeling

• Complex formulas, nested functions, arrays
• Advanced lookups, dynamic tables, Power Query
• Scenario and sensitivity analysis
• Financial statements modeling (3-statement models)

Python for Financial Modeling

• Python basics for finance: NumPy, Pandas
• Data importing, cleaning, and transformation
• Building automated financial calculations
• Python visualization for financial insights

Forecasting & Valuation Models

• Revenue, expense, and cash-flow forecasting
• DCF valuation model (Excel + Python)
• Sensitivity, Monte Carlo simulation
• KPI modeling and performance dashboards

Risk Analysis & Optimization

• Risk modeling techniques
• Portfolio optimization using Python
• Scenario planning and stress testing
• Decision models and advanced analytics

Automation & Model Integration

• Automating Excel tasks with Python
• Creating reusable model templates
• Linking Python scripts with Excel
• Documenting, validating, and presenting models