Explanation : When a dice is rolled, since there are a finite number of outcomes, it is an
example of a discrete probability distribution. The continuous uniform
distribution is defined over a range from a lower limit ‘a’ to an upper limit ‘b’. A
normal distribution is symmetrical and bell-shaped.
Explanation : The cumulative distribution function gives the probability that a random
variable X is less than or equal to a particular value x, P (X < x). Probability
function specifies probability that random variable takes on a specific value.
Probability density function is used for continuous random variables.
Explanation : Consider the tree diagram below: The probability of a price decrease is equal to the probability of a price change times the probability of a decrease given a change = 0.6 * 0.6 = 0.36.
The probability of a price decrease is equal to the probability of a price change times the probability of a decrease given a change = 0.6 * 0.6 = 0.36.
Explanation : The portfolio standard deviation of the returns is calculated through
And covariance is calculated through following formula:
Cov(RARB)=ρ (RARB) σ (RA)σ(RB)
First calculate the covariance, Cov= 0.7 ∗ .14 ∗ .06 = 0.00588, then
enter values in the formula 1 for calculating portfolio standard
deviation, you should get portfolio standard deviation = 8.90%.