For all random variables X, Y, and Z, let Cov(X, Y z) denote the covariance ofX and Y in their conditional joint distribution given Z z Prove that Cov(X, Y) E Cov(X, Y Z) Cov E(X Z), E(Y Z) ...

Cov X Y EX X Y Y EX EX Z EX Z X Y EY Z EY Z Y EX EX ZY EY Z EX EX ZEY Z Y EEX Z X Y EY Z EEX Z ...

For all random variables X, Y, and Z, let Cov(X, Y |z) denote the covariance ofX and

Question:

For all random variables X, Y, and Z, let Cov(X, Y |z) denote the covariance ofX and Y in their conditional joint given Z = z. Prove that
Cov(X, Y) = E[Cov(X, Y |Z)]
+ Cov[E(X|Z), E(Y|Z)].
Distribution
The word "distribution" has several meanings in the financial world, most of them pertaining to the payment of assets from a fund, account, or individual security to an investor or beneficiary. Retirement account distributions are among the most...