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LOS h: Calculate a predicted P/E, given a cross-sectional regression on fundamentals, and explain limitations to the cross-sectional regression methodology.
Q1. An analyst is valuing a company with a dividend payout ratio of 0.35, a beta of 1.45, and an expected earnings growth rate of 0.08. A regression on comparable companies produces the following equation:
Predicted price to earnings (P/E) = 7.65 + (3.75 × dividend payout) + (15.35 × growth) ? (0.70 × beta)
What is the predicted P/E using the above regression?
A) 9.18.
B) 7.65.
C) 11.21.
Q2. An analyst is valuing a company with a dividend payout ratio of 0.55, a beta of 0.92, and an expected earnings growth rate of 0.07. A regression on comparable companies produces the following equation:
Predicted price to earnings (P/E) = 7.65 + (3.75 × dividend payout) + (15.35 × growth) ? (0.70 × beta)
What is the predicted P/E using the above regression?
A) 11.43.
B) 7.65.
C) 10.14.
Q3. An analyst is valuing a company with a dividend payout ratio of 0.65, a beta of 0.72, and an expected earnings growth rate of 0.05. A regression on comparable companies produces the following equation:
Predicted price to earnings (P/E) = 7.65 + (3.75 × dividend payout) + (15.35 × growth) ? (0.70 × beta)
What is the predicted P/E using the above regression?
A) 10.35.
B) 7.65.
C) 11.39. | 
发表于 2009-3-9 17:10
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