Empirical Implications of Arbitrage-Free Asset Markets
... Here we characterize the result more intuitively. which probabilities ...
... Here we characterize the result more intuitively. which probabilities ...
GENERAL ASSIGNMENT PROBLEM via Branch and Price
... tasks to n machines such that each task (i=1,2,…,n) is assigned to exactly one machine (j=1,2,…n). ...
... tasks to n machines such that each task (i=1,2,…,n) is assigned to exactly one machine (j=1,2,…n). ...
Probability metrics with applications in finance
... where τ (t; X, Y ) = P (X ≤ t < Y ) + P (Y ≤ t < X). The function τ (t; X, Y ), which is the building block of the BirnbaumOrlicz compound metric, can be interpreted in the following way. Suppose that X and Y describe the return distributions of two common stocks. The function argument, t, can be r ...
... where τ (t; X, Y ) = P (X ≤ t < Y ) + P (Y ≤ t < X). The function τ (t; X, Y ), which is the building block of the BirnbaumOrlicz compound metric, can be interpreted in the following way. Suppose that X and Y describe the return distributions of two common stocks. The function argument, t, can be r ...
CONDITIONAL EXPECTATION Definition 1. Let (Ω,F,P) be a
... Corollary 1. For any cumulative distribution function F on R (that is, any right-continuous, nondecreasing function satisfying F → 0 at −∞ and F → 1 at +∞) there is a Borel probability measure µF on R such that for every x ∈ R, ...
... Corollary 1. For any cumulative distribution function F on R (that is, any right-continuous, nondecreasing function satisfying F → 0 at −∞ and F → 1 at +∞) there is a Borel probability measure µF on R such that for every x ∈ R, ...
