Practice questions for Exam 2 This practice exam is not intended to duplicate the actual exam. It is intended to provide practice as part of your exam preparation. 1. The value of a parameter will only change if A. the population changes. B. a different sample is obtained from the population.
- Beta alone is not a good predictor of returns. High beta stocks did not outperform low beta stocks. Beta is dead. - High BE/ME is a good predictor of returns. Book to market ratio was the most powerful scaled price variable for predicting stock returns (more than PE and A/ME).
The reason for this is because in tests like these observed differences are usually due to chance differences in sampling. Meaning that, let’s say the p value is more than the significant level of what is being tested or if it’s less than what is being tested. If it is more the null hypothesis is rejected, and if it is less the null hypothesis is rejected in favor of an additional hypothesis. Which is more in the line of saying that it is accepted. The null hypothesis for this experiment was that there would be no changes in allele or genotype frequencies.
If Sharon were risk-indifferent, she would select Investments X and Y because they have a higher return than 12% and risk would not be pertinent. b) If she were risk-averse, which investments would she select? Why? If Sharon were risk-adverse, she would select Investment X because it provides the highest return and has the lowest expected risk index. c) If she were risk-seeking, which investments would she select?
Test is lower for half-test than they are for whole test applications when the Spearman-Bowman formula which means shorter test does not work with this instrument. | Split-half | The split-half method involves dividing the number of individual questions or items of a
The calculated value of F statistic is greater than the critical value of F, therefore the null hypothesis should be rejected. 2. A teacher is interested in comparing the
(c) What sample size would be needed to obtain an error of ±10 square millimeters with 99 percent confidence? n = [t*s/E] n = [2.093*170.378/10]^2 = 1271.64 n = 1272 (when rounded up) (d) If this is not a reasonable requirement, suggest one that is. A 99% confidence level is not logical for a distribution that is probably not normal. dropping it (confidence level) to a 90%, would reduce the required sample size to a more sensible and realistic answer. B.
Since the hurdle rate is usually the cost of capital, WACC for the company is calculated as below: Cost of debt 5.88% After tax 3.53% D/E 28.21% Company Beta 1.15 Cost of equity 10.95% WACC 9.3% It means that any project that will not return 9.3% will be rejected and anything above 9.3% has a good chance of being accepted. Actually the required rate of return and the systematic risk of cash flows for each project were not equal. Actually the projects with low return has a lower beta and would have a lower hurdle rate and projects with higher return have a higher beta and higher hurdle rate. The application of single hurdle rate will result in rejection of projects which return is higher than the actual hurdle rate and accept projects which return is lower than the actual hurdle rate. In other words, it would lead to false rejects for Telecom services while signaling false accepts for the Product and Systems group.
* Risk premium: Arithmetic mean is often used for one-year period valuation, while geometric mean is better for long-term period estimated expected returns. * Beta: Cohen took the average value of historical betas to measure the risk. From my perspective, however, the most recent beta is more representative than the average beta in terms of reflecting future risk. Question 2: What is your estimate of the equity cost of capital? Based on the analysis in question 1, I estimate the cost of equity as following: 9.81% =5.74% + 0.69 * (5.9%) Question 3: How, if at all, would you change Cohen’s debt cost of capital calculation?
* Cost of Equity: * Beta: she used the average beta of the last 5 years, which is also acceptable. However, we decide to use the Bayesian beta calculated with the firm’s present beta as a measure of the future beta assessing for future risk. * Risk-free rate: from the investor’s perspective, we conclude that a 10-year holding period would be more realistic estimate than 20-year. Therefore, we decide to use 10-year U.S. Treasury yield as our risk-free rate in this case. * Risk premium: using the geometric mean from 1926 to 1999 might be problematic, since the risk premium of recent decades is obviously lower than earlier (stated in the lecture).