Md Fozley Elahi

Investment Evaluation Using Monte Carlo Simulation

1. Project Title

Investment Decision Analysis Using Financial Modeling and Monte Carlo Simulation

2. Project Purpose

The purpose of this project is to evaluate a capital investment opportunity by analyzing expected cash flows, profitability, and risk. The model incorporates uncertainty in sales and demand (Triangular Distribution) using simulation techniques to support a more realistic investment decision.

3. Project Objectives

  • Build a 5-year financial model based on projected sales and margins
  • Calculate NPV using 10% cost of capital
  • Model uncertainty using triangular distribution (sales & decay rate)
  • Estimate Mean NPV and Confidence Intervals
  • Measure risk using:
    • Probability of loss (NPV < 0)
    • Value at Risk (VaR at 5%)
  • Provide a clear Go / No-Go investment recommendation

4. Project Scope

In Scope:

  • Cash flow projection (5 years)
  • Depreciation and tax impact (40% tax rate)
  • Simulation of uncertain inputs (sales, decay rate)
  • Risk analysis (CI, probability of loss, VaR)

Out of Scope:

  • Real-time market validation
  • Strategic/operational implementation

5. Key Assumptions

  • Initial fixed development cost = $700M
  • Year 1 margin = $4,000 per unit, declining at 4% annually
  • Sales follow a triangular distribution (50K – 75K – 85K)
  • Annual demand decay between 5%–10%
  • Cost of capital = 10%
  • Depreciation is constant over 5 years

6. Key Deliverables

  • Excel financial model
  • Monte Carlo simulation results
  • Risk analysis summary
  • Final investment recommendation

7. Key Results (From Your Model)

  • Base Case NPV: $126.9M
  • Mean NPV: ~$33.5M
  • 95% Confidence Interval: $30M – $36M
  • Probability of Negative NPV: 27%
  • VaR (5%): ~$69.3M loss

Interpretation:

  • The project is profitable on average
  • But has a moderate risk (27% chance of loss)
  • The downside risk is significant

8. Risks

  • High uncertainty in demand and sales decay
  • Profit margin decreases over time
  • Large upfront investment increases downside exposure

9. Success Criteria

  • Model accurately captures uncertainty
  • Clear understanding of risk vs return
  • Decision supported by data (not assumptions only)

10. Final Recommendation

The project shows positive expected value (NPV > 0), but also meaningful downside risk (27% loss probability and high VaR).

Recommendation:
Proceed with caution (Conditional Go)- invest only if the company can tolerate short-term losses and has strong risk management in place.

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