Bibliography

(eng): The article is devoted to Markov reward chains, in particular, attention is primarily focused on the reward variance arising by summation of generated rewards. Explicit formulae for calculating the variances for transient and average models are reported along with sketches of algorithmic procedures for finding policies guaranteeing minimal variance in the class of policies with a given transient or average reward. Application of the obtained results to financial models is indicated.