Concept: These on-line quiz questions are not specifically linked to AIMs, but are instead based on recent sample questions. The difficulty level is a notch, or two notches, easier than bionicturtle.com's typical AIM-by-AIM question such that the intended difficulty level is nearer to an actual exam question. As these represent "easier than our usual" practice questions, they are well-suited to online simulation.
Questions:
406.1. A fund advertises that its maximum volatility is 10.0%. However, over the last 15 trading days (n = 15), the observed volatility is 14.0%. With 95.0% confidence, can we reject the null hypothesis that the true (population) volatility is equal to 10.0% or less? Please use this chi-square lookup table:
https://learn.bionicturtle.com/images/2014/dailypq/406_1_chi_square.png.
a. No, fail to reject this one-tailed null due to an observed chi-square value of 19.60 which is less than the one-tailed 5.0% critical chi-square
b. No, fail to reject this one-tailed null due to an observed chi-square value of 38.57 which is less than the one-tailed 5.0% critical chi-square
c. Yes, reject this one-tailed null due to an observed chi-square value of 19.60 which is greater than the one-tailed 5.0% critical chi-square
d. Yes, reject this one-tailed null due to an observed chi-square value of 27.44 which is greater than the one-tailed 5.0% critical chi-square
406.2. Your analysis of an asset price series determines the price follows a lognormal distribution with parameters values of mu (μ) = 3.4 and sigma (σ) = 1.0. For example, the expected mean price = exp(μ + σ^2/2) = exp(3.4^2 + 1^2/2) = $49.40. We want to specify the price level that will be exceeded with 50.0% probability; i.e., at approximately which price quantile (level) will the price exceed with 50% probability, and therefore also be lower than 50% of the time?
a. 30.0
b. 37.9
c. 49.4
d. 51.0
406.3. Over the last ten (n = 10) trading days, the daily volatility of two series are 5.0% and 3.0%. If the null hypothesis is that the series (samples) are drawn from the normal population, can we reject the null hypothesis and conclude these volatilities are statistically different with a confidence level of 95.0%? Please use this F distribution lookup table:
https://learn.bionicturtle.com/images/2014/dailypq/406_3_f_lookup.png.
a. No, fail to reject null given observed F ratio of 1.67 and a higher critical F
b. No, fail to reject null given observed F ratio of 2.78 and a higher critical F
c. Yes, reject null given observed F ratio of 1.67 and a lower critical F
d. Yes, reject null given observed F ratio of 2.50 and a lower critical F
Answers here:
Questions:
406.1. A fund advertises that its maximum volatility is 10.0%. However, over the last 15 trading days (n = 15), the observed volatility is 14.0%. With 95.0% confidence, can we reject the null hypothesis that the true (population) volatility is equal to 10.0% or less? Please use this chi-square lookup table:
https://learn.bionicturtle.com/images/2014/dailypq/406_1_chi_square.png.
a. No, fail to reject this one-tailed null due to an observed chi-square value of 19.60 which is less than the one-tailed 5.0% critical chi-square
b. No, fail to reject this one-tailed null due to an observed chi-square value of 38.57 which is less than the one-tailed 5.0% critical chi-square
c. Yes, reject this one-tailed null due to an observed chi-square value of 19.60 which is greater than the one-tailed 5.0% critical chi-square
d. Yes, reject this one-tailed null due to an observed chi-square value of 27.44 which is greater than the one-tailed 5.0% critical chi-square
406.2. Your analysis of an asset price series determines the price follows a lognormal distribution with parameters values of mu (μ) = 3.4 and sigma (σ) = 1.0. For example, the expected mean price = exp(μ + σ^2/2) = exp(3.4^2 + 1^2/2) = $49.40. We want to specify the price level that will be exceeded with 50.0% probability; i.e., at approximately which price quantile (level) will the price exceed with 50% probability, and therefore also be lower than 50% of the time?
a. 30.0
b. 37.9
c. 49.4
d. 51.0
406.3. Over the last ten (n = 10) trading days, the daily volatility of two series are 5.0% and 3.0%. If the null hypothesis is that the series (samples) are drawn from the normal population, can we reject the null hypothesis and conclude these volatilities are statistically different with a confidence level of 95.0%? Please use this F distribution lookup table:
https://learn.bionicturtle.com/images/2014/dailypq/406_3_f_lookup.png.
a. No, fail to reject null given observed F ratio of 1.67 and a higher critical F
b. No, fail to reject null given observed F ratio of 2.78 and a higher critical F
c. Yes, reject null given observed F ratio of 1.67 and a lower critical F
d. Yes, reject null given observed F ratio of 2.50 and a lower critical F
Answers here:
