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Unformatted text preview: P(B|A) = P(A|B) * P(B) / P(A) P(A|B) = P(B|A) * P(A) / (B) E(x) = xP(x) 2= (x-E(x))2P(x) Standard Dev = 1/2 E(x) = Return = risk Co-variance xy = (x-E(x))(y-E(y))P(xy) negative Co-variance is ok 2x+y = x2 + y2 +2xy Portfolio Expected Return = E(p) = wE(x) + (1-w)(E(y)) w = proportion invested p = [w2x 2 + (1-w)2 y2 + 2(w)(1-w) xy]1/2 P(x) = [n! / x!(n-x)!] * pxqn-xq n = # of trials x = # of successes p = prob. of s. q = prob of f. The four assumptions that must be met for a prob distribution to qualify as a binomial distribution. 1. series of `n' identical trials 2. 2 only possible outcomes 3. Prob s(p) + Prob f(q) must remain constant 4. Independent Trials Poisson Distribution to determine the prob of `x' # of occurrences of an event over a specified period of time on distance discrete function b/c we count. 2 reqs 1. Prob of an occurrence of an event is the same for any two intervals of time or distance 2. the occurrences must be independent. f(x) = P(x) = e-u ux / x! x = # of occurrences e = const. u = expected # of occurrences over a specified interval. Hypogeometric = P(x) = (rx)(N-r n-x) / (Nn) N = # of items in the population r = # of successes in the pop N-r = # of failures in the pop n = # of items in sample x = # of successes in sample n-x = # of failures in sample ...
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This note was uploaded on 04/29/2008 for the course MGT 2250 taught by Professor Milne during the Spring '08 term at Georgia Institute of Technology.
- Spring '08