(PARTICIPANTS MUST BE WITH THEIR COMPUTERS)
Programme Description
This program will make participants with little or no knowledge in modeling understand how to build a working data analysis model in excel. They will be equipped with advanced excel functions vital in modeling financial and business data. The will also be equipped with Excel Macro in visual basic to handle repetitive tasks.
This programme will enable participants:
• be able to Model and Forecast Financial Reports
• be able to Reference and Linking Business data in models
• build cash and flexible budget models
• able to use various breakeven techniques
• know how to value businesses
• make optimal decision regarding investment.
Course Contents
DAY ONE
• Business Performance Analysis
• Cash flow Forecast Models
• Excel Referencing and application
• Linking and worksheet Consolidation
• Forecasting Models:
- Historical Forecast (Point Forecast)
- Trend Lines (Interval Forecast)
- Cyclicality and Seasonality
• Forecasting Financial Reports:
- Key Drivers
- Driving Financial Statements
- Alternative Approaches
• Variance Analysis
• Breakeven Analysis:
- Breakeven
- Operating Leverage
- Financial Leverage.
DAY TWO
• Personal Budget
• Company Budget
• Flexible budget model
• Fixed budget model
• Budget variance
• Budgeting and Control Models.
DAY THREE
• Portfolio Analysis
• Risk and Return Analysis
• Cost of Capital:
- Capital Asset Pricing Model
- How to determine your company’s Beta.
- Cost of Preference Share
- Cost of Debt
- Weighted Average Cost of Capital (WACC)
- Marginal WACC
• Investment Analysis:
- Payback Period
- Accounting Rate of Returns
- Internal Rate of Return
- Net Present Value
- Loan Management and Loan Determination Schedule
- Benefit/Cost Ratio
- Capital Rationing
- Scenarios and Sensitivity Analysis and Charts.
DAY FOUR
• Company Valuation:
- Adjusted Accounting Valuation
- Dividends Valuation
- Market Valuation
- Free Cash flow Valuation
DAY FIVE
• Optimization:
- Elements of Optimization Models
- Linear Programming
- Margin Maximization
- Bayes’ Theorem
- Decision Tree Model
- Building Sensitivity analysis and Scenarios into Models
- Introduction and Application of Macro to enhance your Model.
