Partial hedging and cash requirements in discrete time
将连续时间模型离散化，提出基于动态规划的数值算法，用于求解标准期权、奇异期权的分位数对冲问题，并扩展到效用无差别定价、好交易边界和预期亏损问题。
This paper develops a discrete time version of the continuous time model of Bouchard et al. [J. Control Optim., 2009, 48, 3123–3150], for the problem of finding the minimal initial data for a controlled process to guarantee reaching a controlled target with probability one. An efficient numerical algorithm, based on dynamic programming, is proposed for the quantile hedging of standard call and put options, exotic options and quantile hedging with portfolio constraints. The method is then extended to solve utility indifference pricing, good-deal bounds and expected shortfall problems.