## Concept Checkers

A portfolio manager produced an alpha of 2.3% based on monthly returns over a 5-year period. Under the assumption of a normal distribution, the portfolio manager claims that the probability of observing such a large alpha by chance is only 1%. To test her claim, we will use a f-test, constructing a confidence level of:

Based on 60 monthly returns, you estimate an actively managed portfolio alpha =

I.24% and standard error of alpha = 0.1278%. The portfolio manager wants to get due credit for producing positive alpha and believes that the probability of observing such a large alpha by chance is only 1%. Calculate the i-statistic, and based on the estimated i-value would you accept (or reject) the claim made by the portfolio manager.

The main effect of hetroskedasticity and serial correlation refinements to a regression model is to achieve:

I. unbiased standard error of estimate (SEE).

II. unbiased standard errors of the estimated coefficients.

III. unbiased and valid t-tests for drawing inferences about the values of the parameters.

IV. none of the above.

Refer to Figure 3, assume that the beta, |3pA(t), and benchmark return, Rfi(t), are as given in the table for each of the 12 periods, but the long-term expected excess benchmark return, Mfi is 5% instead of 6%. Which of the following are TRUE?

I. Total Active Systematic Returns decrease.

II. Expected Active Beta Returns decreases.

III. Active Beta Surprise increases.

IV. Active Benchmark Timing Returns increase.

5. When conducting a cross-sectional analysis of performance data which of the following is NOT a shortcoming of the data? There is: