Quantitative Methods III Flashcards
Empirical probability, a priori and subjective
Empirical: past observations
A priori: using formal reasoning and inspection
Subjective: personal judgment
Odds
Probability / (1 - probability)
Multiplication rule P(AB)
P(AB) = P(A | B) * P(B)
Prob of A&B = prob of A given B * prob of B
Addition rule P(A or B)
P(A or B) = P(A) + P(B) - P(AB)
Probability that at least one of the two events occur
If A & B are mutually exclusive P(AB) = 0
Joint probability of independent events P(A and B)
P(A and B) = P(A) * P(B)
Think dice
Expected value
Weighted average of the possible outcomes, where weights are probabilities of occurrence.
Expected standard deviation and variance
Probability weighted standard deviation where Xbar = expected return.
Sum[Wi * (Xi - Xbar)^2…] / n
Covariance
Sum[probability(Rx,Ry) * ((Rx - E(Rx)) * (Ry - E(Ry))]
How two assets move together
Correlation
Cov(X,Y) / [stdev(x) * stdev(y)]
Measures strength of linear correlation
Has no units
Portfolio expected return
E(Rp) = Sum[WiE(Ri) + … WnE(Rn)]
Portfolio expected variance
Var(Rp) = Sum[Sum[WiWjCov(Ri,Rj)]]
Bayes formula
P(A | B) = [P(B | A) * P(A)] / P(B)
Used to update prob given prior probs
Check out page 219 example
Combination formula (factorial)
N! / [(n-r)! * r!]
R = number of items in group
N = number of total items
Permutation formula (factorial)
N! / (n-r)!
How many different groups of size r in specific order can be chosen from n objects
Order matters
How many combinations of 5 kids from a group of 15?
5! / [(15 - 5)! * 5!]