Explanation

We need to calculate the predicted P/E using the cross-sectional regression model and compare it to the actual P/E of 12.

Given:

• Beta = 1.2
• Dividend payout ratio = 0.30
• Earnings growth rate = 0.10

Using the regression equation: $\text{Predicted P/E} = 12 + (5.75 \times \text{dividend payout}) + (14.35 \times \text{earnings growth rate}) - (0.60 \times \text{beta})$

Substitute the values: $\text{Predicted P/E} = 12 + (5.75 \times 0.30) + (14.35 \times 0.10) - (0.60 \times 1.2)$ $\text{Predicted P/E} = 12 + 1.725 + 1.435 - 0.72$ $\text{Predicted P/E} = 12 + 3.16 - 0.72$ $\text{Predicted P/E} = 14.44$

Now compare:

• Predicted P/E = 14.44
• Actual P/E = 12

Since the actual P/E (12) is lower than the predicted P/E (14.44), the stock appears undervalued.

This means that based on the company's characteristics (dividend payout, earnings growth, and beta), the regression model suggests it should have a higher P/E ratio than what the market is currently pricing.