Let X1 and X2 have a bivariate Gaussian PDF with correlation coefficient ρ12 such that each Xi is a Gaussian (µi, σi) random variable. Show that Y = X1X2 has variance 
You may also need to look ahead to Problem 6.3.4.
Problem 6.3.4
Let X be a Gaussian (0,σ) random variable. Use the moment generating function to show that

Let Y be a Gaussian (µ, σ ) random variable. Use the moments of X to show that
