The authors apply the minimum-risk approach to the stochastic continuous time linear-fractional problem. They assume that the coefficients of the objective functions are simply randomized, and show, under some positivity conditions, that the stochastic continuous time linear-fractional problem is equivalent to certain deterministic continuous time linear-fractional problem, while the stochastic continuous time linear-fractional problem with an objective function having a linear-fractional kernel is equivalent to a deterministic continuous time nonlinear-fractional problem. Some parametric procedures are proposed for solving these deterministic equivalent problems. These procedures involve approximations by discrete optimization problems.