This paper studies multi-period risk management problems by presenting a dynamic risk measure. This risk measure is the sum of conditional value-at-risk of each period. The authors model it by Markov decision processe...This paper studies multi-period risk management problems by presenting a dynamic risk measure. This risk measure is the sum of conditional value-at-risk of each period. The authors model it by Markov decision processes and derive its optimality equation. This equation is further transformed equivalently to an analytically tractable one. The authors then use the model and its results to a multi-period portfolio optimization when the return rate vectors at each period form a Markov chain.展开更多
基金This research was supported in part by the National Natural Science Foundation of China under Grant Nos. 70971023 and 71001089 and in part by the Natural Science Foundation of Zhejiang Province under Grant No. Y60860040.
文摘This paper studies multi-period risk management problems by presenting a dynamic risk measure. This risk measure is the sum of conditional value-at-risk of each period. The authors model it by Markov decision processes and derive its optimality equation. This equation is further transformed equivalently to an analytically tractable one. The authors then use the model and its results to a multi-period portfolio optimization when the return rate vectors at each period form a Markov chain.
