  We investigate the computation of the gradient of the value function in
parametric convex optimization problems. We derive general expression for the
gradient of the value function in terms of the cost function, constraints and
Lagrange multipliers. In particular, we show that for the strictly convex
parametric quadratic program the value function is continuously differentiable
at every point in the interior of feasible space for which the Linear
Independent Constraint Qualification holds.
