Past exam of the mathematics course of the University of Cambridge / 2018 / ii / Paper 4 / 29K (Stochastic Financial Models)

Write $X=\mu +\sigma Z$, where $Z$ has the standard normal distribution. Apply Gaussian integration by parts to $g(z)=U^{\prime }(\mu +\sigma z)$:Since $X-\mu =\sigma Z$,The polynomial growth assumption and decay of the normal distribution density justify the integration by parts.

Using the representation $X=\mu +\sigma Z$ and differentiation under the integral sign,because $U$ is strictly increasing. Similarly, part (a) givesbecause a twice differentiable concave function has $U^{\prime \prime }\le 0$. ThereforeIn mean-variance optimization, an expected-utility investor consequently prefers a larger mean at fixed standard deviation and a smaller variance at fixed mean. This is the usual risk-averse ordering of Gaussian payoffs.

Differentiating $f(\mu ,\sigma )=\mathbb{E}[U(\mu +\sigma Z)]$ twice gives the Hessian matrixFor every vector $(a,b)$,Thus the Hessian is a negative semidefinite matrix, andEquivalently, with $W=-U^{\prime \prime }(X)\ge 0$, its determinant isby the Cauchy-Schwarz inequality, while both diagonal entries are nonpositive.