Course Code: 25BP03MJB1

Financial Modeling

Master the art of building professional financial models using Excel, Python, and AI-enhanced tools. Prepare for careers in investment banking, private equity, and corporate finance.

📅 MBA Term 3
⏱️ 45 Contact Hours
🎓 3 Credits
📊 30 Sessions
30
Sessions
3
CILOs
5
Assessments
100
Total Marks

Course Modules

30 sessions covering everything from Excel basics to advanced AI-enhanced modeling

Session 1 Introduction to Financial Modeling
  • What is financial modeling?
  • Applications in finance
  • Core principles & best practices
  • Excel basics review
📚 Pignataro, Ch. 1–2 🎯 CILO 1
Start Learning →
Session 2 Excel Functions for Financial Modeling
  • VLOOKUP, XLOOKUP, INDEX-MATCH
  • Logical functions (IF, AND, OR, IFERROR)
  • Date and text functions
  • Excel Lab: Hands-on practice
📚 Excel Bible, Ch. 5–7 🎯 CILO 1
Start Learning →
Session 3 Financial Statement Mechanics
  • Income statement
  • Balance sheet
  • Cash flow statement
  • Common-size analysis
📚 Rosenbaum, Ch. 2 🎯 CILO 1
Start Learning →
Session 4 Building a Historical Model
  • Inputting historical financials
  • Calculating key ratios
  • Trend analysis
  • Quality checks
📚 Pignataro, Ch. 3–5 🎯 CILO 1
Start Learning →
Supplementary · Session 4a Converting Annual to Quarterly Statements
  • Stock vs. flow variables — why BS can't be divided by 4
  • Working Capital Ratio Method (DSO, DIO, DPO)
  • Linear interpolation for PP&E, debt, intangibles
  • RE roll-forward & quarterly cash flow build-up
  • Industry examples: Retail, IT Services, Manufacturing
📚 Pignataro, Ch. 3–4 🎯 CILO 1
Start Learning →
⭐ Supplementary Resource Three-Statement Model Workflow
  • Visual SVG master flow chart (6 phases)
  • Step-by-step instructions with formulas
  • Statement linkage diagrams (IS ↔ BS ↔ CF)
  • Industry drivers: IT, Manufacturing, Retail, Pharma, Banking
  • Printable build checklist with localStorage save
📋 Reference Guide 🔗 Covers Sessions 4–8
Open Resource →
Session 5 Revenue & Expense Forecasting
  • Top-down vs. bottom-up
  • Driver-based assumptions
  • Seasonality
  • Growth rate estimation
📚 Damodaran, Ch. 4 🎯 CILO 1, 2
Start Learning →
Session 6 Working Capital & Capex Modeling
  • Net working capital cycles (DSO, DIO, DPO)
  • CAPEX & depreciation schedules
  • PP&E roll-forward
  • Three-statement integration
📚 Rosenbaum, Ch. 3 🎯 CILO 1
Start Learning →
Session 7 Debt & Interest Schedules
  • Debt tranches & instruments
  • Interest calculations (beginning/average/ending balance)
  • Repayment schedules (mandatory amort, cash sweep)
  • Circular references handling
📚 Pignataro, Ch. 5 🎯 CILO 1
Start Learning →
Session 8 Three-Statement Integration
  • Linking IS, BS, and CF
  • Income statement & balance sheet links
  • Cash flow statement construction
  • Balancing the model & error-checking
📚 Rosenbaum, Ch. 4 🎯 CILO 1
Start Learning →
Session 9 Scenario & Sensitivity Analysis
  • Data tables
  • Scenario manager
  • Goal seek
  • Sensitivity tables for key drivers
📚 Excel Bible, Ch. 12 🎯 CILO 2
Start Learning →
Session 10 DCF Valuation – I
  • Free cash flow to firm (FCFF)
  • Terminal value methods
  • Gordon growth model
  • Exit multiple approach
📚 McKinsey, Ch. 8 🎯 CILO 1, 3
Start Learning →
Session 11 DCF Valuation – II
  • Weighted average cost of capital (WACC)
  • Cost of equity (CAPM)
  • Cost of debt
  • Present value calculation
📚 Damodaran, Ch. 7 🎯 CILO 1, 3
Start Learning →
Session 12 Relative Valuation (Comps)
  • Trading comparables
  • Transaction comparables
  • Selecting multiples
  • Normalizing adjustments
📚 Rosenbaum, Ch. 5 🎯 CILO 1, 3
Start Learning →
Session 13 Precedent Transactions Analysis
  • M&A transaction multiples (EV/EBITDA, EV/Revenue, P/E)
  • Control premiums & unaffected share prices
  • Synergy assumptions & synergy-to-premium ratios
  • Football field valuation range
📚 McKinsey, Ch. 9; Rosenbaum, Ch. 5 🎯 CILO 1, 3
Start Learning →
Session 14 M&A Modeling – I
  • Deal structure (cash, stock, mixed consideration)
  • Sources & Uses of Funds
  • Purchase Price Allocation & Goodwill
  • Pro forma balance sheet construction
📚 Rosenbaum, Ch. 6; Pignataro, Ch. 8 🎯 CILO 1, 3
Start Learning →
Session 15 M&A Modeling – II
  • Synergy modeling (cost & revenue with probability weighting)
  • Pro forma income statement (6 M&A adjustments)
  • Accretion/dilution analysis (3 scenarios)
  • Deal optimization & sensitivity analysis
📚 Rosenbaum, Ch. 6; Pignataro, Ch. 8 🎯 CILO 1, 3
Start Learning →
Session 16 LBO Modeling – I
  • LBO mechanics
  • Sources & uses of funds
  • Debt capacity analysis
  • IRR hurdles
📚 Rosenbaum, Ch. 7 🎯 CILO 1
Start Learning →
Session 17 LBO Modeling – II
  • Debt repayment schedules (mandatory amort + cash sweep)
  • Cash flow waterfall construction
  • Sponsor returns & scenario analysis (IRR/MOIC)
  • Value creation bridge & multiple expansion/compression
📚 Pignataro, Ch. 9 🎯 CILO 1, 3
Start Learning →
Session 18 IPO Modeling
  • IPO process & book-building mechanism
  • Offering structure — fresh issue vs. offer for sale
  • Underwriting costs — gross spread + expenses
  • Post-IPO capitalization & shareholding pattern
  • Pro forma financials — EPS dilution analysis
📚 McKinsey, Ch. 10 🎯 CILO 1, 3
Start Learning →
Session 19 Python for Financial Modeling – I
  • Excel vs Python — when to use what
  • Setting up Python, Pandas, and yfinance
  • Fetching live stock data from Yahoo Finance
  • DataFrames, data cleaning, and financial calculations
📚 Hilpisch, Ch. 3–4; McKinney Ch. 4–5 🎯 CILO 2
Start Learning →
Session 20 Python for Financial Modeling – II
  • Full DCF model class with automated beta & WACC
  • Two-way sensitivity tables replacing Excel Data Tables
  • Professional visualizations (waterfall, heatmap, bar charts)
  • Jupyter notebooks & Excel report export
📚 Hilpisch, Ch. 7–8; McKinney, Ch. 9–10 🎯 CILO 2
Start Learning →
Session 21 AI-Enhanced Forecasting
  • Multiple linear regression for revenue prediction
  • Time-series decomposition (trend, seasonal, residual)
  • Feature engineering: lags, rolling means, cyclical encoding
  • OLS vs Ridge vs Lasso with walk-forward validation
📚 López de Prado, Ch. 3 🎯 CILO 2
Start Learning →
Session 22 Monte Carlo Simulation
  • Probability distributions for finance (Normal, Triangular, Lognormal)
  • Monte Carlo DCF valuation with 10,000 simulations
  • Project NPV simulation & risk analysis
  • Reusable MonteCarloSimulator Python template
  • Portfolio Value at Risk (VaR) with Cholesky decomposition
📚 Damodaran (Risk & Return) 🎯 CILO 2, 3
Start Learning →
Session 23 Real Options Valuation
  • Five types of real options: delay, expand, abandon, switch, stage
  • Binomial tree method with backward induction (Python)
  • Black-Scholes adapted for real options (patents, licenses)
  • Reusable RealOptionsValuer Python template
  • Expanded NPV = NPV + Option Value
📚 McKinsey, Ch. 11; Damodaran (Real Options) 🎯 CILO 1, 3
Start Learning →
Session 24 Model Auditing & Error-Proofing
  • The 7 Deadly Sins of financial modeling
  • Excel audit tools: Trace Precedents, Go To Special, Evaluate Formula
  • 8 automated validation checks (BS balance, roll-forwards)
  • FAST Standard, color coding, changelogs, named ranges
  • 30-point master audit checklist
📚 Pignataro, Ch. 10; FAST Standard 🎯 CILO 1
Start Learning →
Session 25 Industry Modeling – Banking
  • Bank financial statements
  • Net interest margin
  • Provision for loan losses
  • Regulatory capital
📚 CFA Level II 🎯 CILO 1, 3
Session 26 Industry Modeling – Real Estate
  • Real estate pro forma
  • NOI calculation
  • Cap rates
  • Debt service coverage ratio
📚 RE Finance refs 🎯 CILO 1, 3
Session 27 Bloomberg for Financial Modeling
  • Data retrieval (FA, DRS)
  • Template models (MODL)
  • Company comparables
  • Market data analysis
📚 Bloomberg guides 🎯 CILO 2
Session 28 Integrated Case Study – I
  • Three-statement model
  • DCF valuation
  • Comparable company analysis
  • Real company analysis
📚 SEC Filing 🎯 CILO 1, 2, 3
Session 29 Integrated Case Study – II
  • M&A/LBO scenario
  • Accretion/dilution
  • Returns analysis
  • Strategic transaction modeling
📚 Rosenbaum, Ch. 6–7 🎯 CILO 1, 2, 3
Session 30 Model Presentation & Communication
  • Effective presentation of outputs
  • Executive summary creation
  • Key drivers communication
  • Sensitivity charts presentation
📚 McKinsey, Ch. 12 🎯 CILO 3

Course Resources

Textbooks, tools, and platforms you'll need for this course

📖

Core Textbooks

Pignataro's Financial Modeling, Rosenbaum & Pearl's Investment Banking, Damodaran on Valuation

📊

Microsoft Excel

Advanced functions, Power Query, Power Pivot for building professional models

🐍

Python

Pandas, NumPy, Scikit-learn for automated modeling and ML forecasting

💹

Bloomberg Terminal

Real-time data, company analysis, and professional modeling templates

🎓

Online Platforms

Corporate Finance Institute, Wall Street Prep, Investopedia for supplementary learning

🤖

AI Tools

Modern AI-assisted modeling approaches and automation techniques

Course Intended Learning Outcomes

What you'll achieve by the end of this course

1

Build Financial Models

Understand, design, and build integrated financial models (three-statement, DCF, M&A, LBO) following industry best practices.

2

Use Tools & Technology

Use Excel, Python, and AI/ML tools to automate data collection, perform analysis, and generate forecasts.

3

Interpret & Recommend

Interpret model outputs and formulate actionable financial recommendations considering ethical and risk dimensions.