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1、What is the most appropriate interpretation of a slope coefficient estimate equal to 10.0?

　　A. The predicted value of the dependent variable when the independent variable is zero is 10.0.

　　B. The predicted value of the independent variable when the dependent variable is zero is 0.1.

　　C. For every one unit change in the independent variable the model predicts that the dependent variable will change by 0.1 units.

　　D. For every one unit change in the independent variable the model predicts that the dependent variable will change by 10 units.

　　Answer: D

　　Explanation: The slope coefficient is best interpreted as the predicted change in the dependent variable for a 1-unit change in the independent variable. If the slope coefficient estimate is 10.0 and the independent variable changes by one unit, the dependent variable will change by 10 units. The intercept term is best interpreted as the value of the dependent variable when the independent variable is equal to zero.

2、Which of the following statements are wrong?

　　I Type I error occurs when the null hypothesis is not rejected when it is actually false.

　　II Type II error occurs when the null hypothesis is rejected when it is actually true.

　　III Type I error occurs when the alternate hypothesis is wrongly accepted.

　　IV Minimizing the probability of Type I error maximizes the power of the test.

　　A. I and II

　　B. I and III

　　C. II and IV

　　D. I, II and IV

　　Answer: D

　　In hypothesis testing we accept the alternate hypothesis if the null hypothesis has been rejected. Type I error happens if the null hypothesis is rejected when it is actually true. Type II error happens if the null hypothesis is accepted when it is actually false. The power of the test is the probability of correctly rejecting the null hypothesis (when it is false), so minimizing Type II (not Type I) errors would maximize the power of the test.

3、According to linear regression function assumptions, the equation must be linear in:

　 A. Both the variables and the coefficients.

　　B. The variables but not necessarily the coefficients.

　　C. The coefficients but not necessarily the variables.

　　D. Neither the variables nor the coefficients.

　　Answer：C.

　　Linear regression refers to a regression that is linear in the coefficients/parameters; it may or may not be linear in the variables.

4、Which of the following statements regarding assumption of the CAPM is correct?

　　I. Each investor seeks to maximize the expected utility of wealth at the end of that investor’s horizon.

　　II. Investors can borrow and lend at the same risk-free rate.

　　III. Investors have the same expectations concerning returns.

　　IV. The time horizons of investors are normally distributed.

　　A. I、 III

　　B. II、 III

　　C. I、 II、 III

　　D. I、 II、 IV

　　Answer: C

　　Explanation: The CAPM assumes that investors all have the same horizon (as well as expectations). This means that the distribution of the horizons is not normal because normality implies a bell-shaped curve distribution, which would have a positive variance and hence, dispersion.

　　FRM相關(guān)知識點：CAPM Assumptions

　　1. Investors seek to maximize the expected utility of their wealth at the end of the period, and all investors have the same investment horizon.

　　2. Investors are risk averse.

　　3. Investors only consider the mean and standard deviation of return (which implicitly assumes the asset returns are normally distributed).

　　4. Investors can borrow and lend at the same risk-free rate.

　　5. Investors have the same expectations concerning returns.

　　6. There are neither taxes nor transactions costs, and assets are infinitely divisible. This is often referred to as “perfect markets”

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