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L15.2082 - Statistics for Business and Economics (2024/2025)
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The covariance between the returns on stock A and the returns on stock B is 0. Therefore we can conclude that the returns on A are independent from the returns on B.
Consider the joint probability distribution:
| x = 1 | x = 2 | |
|---|---|---|
| y = 0 | 0.2 | 0.25 |
| y = 1 | 0.3 | 0.25 |
What is E[X | Y = 0]?
Consider the joint probability distribution:
| x = 0 | x = 1 | |
|---|---|---|
| y = 0 | 0.15 | 0.35 |
| y = 1 | 0.25 | 0.25 |
Where:
- E[X] = 0.6
- E[Y] = 0.5
A portfolio is invested in stocks Alpha and Beta with 30% of the portfolio invested in Alpha. The exhibit below illustrates the covariance matrix and expected returns with respect to the portfolio.
The correlation coefficient (r) between alpha and beta is closest to:
Given a portfolio of five stocks, how many unique covariance terms, excluding variances, are required to calculate the portfolio return variance?
The Bernoulli distribution is always symmetric.