MODELING
COURSE OBJECTIVES
MBA Financial Modeling and Analysis teaches students how to conceive and build a financial model from beginning-to-end, followed by due diligence. This course demonstrates how financial models guide commercial discussions. Participants will learn how to negotiate off the model.
This course will utilize a Discounted Cash Flow (“DCF”) pro forma approach derived from a full suite
of financial statements: 1) Income Statement, 2) Statement of Retained Earnings, 3) Balance Sheet
and, 4) Statement of Cash Flow. Participants use “hot keys” and page-setup techniques to build a fully integrated pro forma DCF model from a list of assumptions. The “mouseless” Excel techniques employed dramatically reduce model coding time. Next, delegates learn how to integrate all financial statements to produce a correctly-balanced Balance Sheet, without circularities. The class will use this model as a guide to review commercial issues, negotiate strategies and analyze financial ratios. Finally, the course demonstrates the power of Monte Carlo simulation analysis to create a dynamic decision-making tool and that elevates beyond simple static input and output spreadsheets.
This course is indispensable to the effective use of financial spreadsheets for any industry or sector. (NB: A working knowledge of financial accounting is helpful but not essential.)
Each graduating student will receive a Vair Training Certificate of Completion.
COURSE OUTLINE
Part 1 – Introduction to Excel
Part 2 – Introduction to Financial Statements
Part 3 – Introduction of a Pro Forma Model
Part 4 – Assets: Purchasing versus Leasing
Part 5 – Operational Worksheets
Part 6 – Debt
Part 7 – Coding Full Financial Statements
Part 8 – Discussion on Valuation
Part 9 – Discounted Cash-Flow Modeling
Part 10 – Using the Model to Price the Asset
Part 11 – Monte Carlo Simulation Analysis
Click Here for Class Syllabus
STRUCTURE
This course takes a practical "learn by doing" modular approach. The course structure for each module follows a four-step pattern: 1) teaching of the material, 2) spreadsheet exercise, 3) review of the exercise; then, 4) follow-up with a question-and-answer session. Each successive module builds upon the previous exercise. Each participant will be given problem and answer files to insure course fluidity for every student's level.
This course uses methodologies to:
• Identify the model-type for analysis
• Create models that are easy to navigate without forfeiting robustness
• Use that model to assist your decision-making process
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