Probability Concepts Flashcards
Uncertain value determined by chance
Random variable
The realization of a random variable
Outcome
A set of one or more outcomes
Event
Two events that cannot both occur
Mutually exclusive
A set of events that includes all possible outcomes
Exhaustive
Two properties of probability
- The sum of the probabilities of all possible mutually exclusive events is 1.
- The probability of any event cannot be greater than 1 or less than 0.
Measures predetermined probabilities based on well-defined inputs
A priori probability
Measures probability from observations or experiments
Empirical probability
Measures probability using informed guess
Subjective probability
Odds for v. odds against
Odds for = A / B - A, odds against = B / A + B
The probability of an event occuring
Unconditional probability
The probability of an event A occurring given that event B has occurred
Conditional probability
Used to determine to the joint probability of two events
The multiplication rule of probability
P(AB) = P (A|B) x P (B)
or
P(A|B) = P(AB) / P(B)
Used to determine the probability that at least one of two events occur
The addition rule of probability
P(A or B) = P(A) + P(B) - P(AB)
Used to determine the unconditional probability of an event given condition probabilities
The total probability rule
P(A) = P (A|B1)P(B1) + P(A|B2)P(B2)
B1, B2, etc are mutually exclusive and exhaustive
The measure of extent to which two random variables tend to be above and below their respective means for each joint realization.
Covariance
Covariance formula
CovA,B = ∑ (Ai - A-bar)(Bi - B-bar) / n - 1
The standardized measure of association between two random values
Correlation
Correlation formula
Corr (X,Y) = Cov(X,Y) / σA * σB
Expected Value of Random Variable
= ∑ Pi(Xi) * Xi
Variance of a Random Variable
= ∑ P(Xi)[(Xi-E(X)]^2
Expected Return of a 2-asset Portfolio
E(Rp) = w1E(R1) + w2E(R2)
Expected Variance of a 2-asset Portfolio
Var(Rp) = (w1^2 * σ1^2) + (w2^2 * σ2^2) + 2(w1w2Cov1,2)
Covariance (given joint probability)
=∑ P(Xi, Yi) * (Xi-E(X) * (Yi - E(Y)
Bayes’ Formula
= P(I|O) = P(O|I) / P (O) x P (I)
Formula to chose a subset of size r from a set of size n when order doesn’t matter
= nCk (combination)
Formula to chose a subset of size r from a set of size n when order matters
= nPk (permutation)