Linear Programming Excel Case Study – Portfolio Optimization
Real-World Linear Programming Excel Case Study: Investment Portfolio Strategy
Are you unsure how to allocate your investments across multiple asset classes while balancing risk and maximizing returns? This linear programming Excel case study shows how to build a smart financial portfolio using Excel Solver—an ideal tool for both beginners and data-savvy users. In fact, using transition points such as budgeting, goal-setting, and constraint handling will help guide your decision-making process.
Key Data for the Linear Programming Excel Investment Model
Investment Opportunities
| Asset Class | Expected Return (%) | Risk Index | Min Investment | Max Investment |
|---|---|---|---|---|
| Bonds | 4 | 2 | $10,000 | $50,000 |
| Stocks | 10 | 7 | $10,000 | $80,000 |
| Real Estate | 7 | 5 | $20,000 | $70,000 |
| Crypto | 15 | 9 | $5,000 | $30,000 |
Portfolio Constraints
To stay within realistic financial bounds, consider the following constraints:
- Total Investment Budget: $150,000
- Average Risk Index must not exceed 6
- Must invest in at least 3 asset classes
Building the Excel Linear Programming Model for Finance
Decision Variables
Let x_i be the dollar amount invested in each asset class.
Objective Function: Maximize Expected Return
Total Return = Σ(Expected_Return_i * x_i)In Excel: =SUMPRODUCT(ReturnRange, InvestmentRange)
Constraints
Next, define these constraints to guide Solver’s decisions:
- Total Investment = $150,000
- Weighted Average Risk ≤ 6:
=SUMPRODUCT(RiskIndexRange, InvestmentRange)/Total Investment - Each investment must fall within its min/max range
- At least three investments must be non-zero (advanced models use binary flags)
Configuring Excel Solver for Financial Portfolio Optimization
Now that we’ve set up our data, let’s move into Solver setup:
- Set Objective: Maximize total return (output cell)
- Variable Cells: x_i investment cells
- Constraints:
- SUM(x_i) = 150,000
- SUMPRODUCT(RiskIndex, x_i) / 150,000 ≤ 6
- x_i ≥ Min and ≤ Max for each asset
- Binary enforcement (if needed) for inclusion of at least 3 asset classes
- Solver Method: Simplex LP
Once everything is ready, click Solve to generate the optimal portfolio using this linear programming Excel case study model.
Results: Optimized Investment Portfolio Example
Let’s see how the portfolio turns out when optimized:
| Asset Class | Investment | Return (%) | Expected Return |
| Bonds | $30,000 | 4% | $1,200 |
| Stocks | $60,000 | 10% | $6,000 |
| Real Estate | $40,000 | 7% | $2,800 |
| Crypto | $20,000 | 15% | $3,000 |
Total Return: $13,000 | Average Risk Index: 5.93 (within allowed limit)
👉 Download the Free Excel Case Study Template (Financial Portfolio)
Strategic Insights from the Linear Programming Excel Case Study
- Balanced Risk and Return: Portfolio hits a risk score of 5.93, safely below the 6.0 cap
- Diversification Achieved: Funds distributed across all four classes
- Solver Power: Excel Solver enforces boundaries and finds optimal return
This financial linear programming Excel case study offers a solid foundation for making real-world investment decisions using data-driven logic.
