HEDGING BY SEQUENTIAL REGRESSIONS REVISITED
回顾了Föllmer和Schweizer提出的序贯回归对冲策略，结合全局风险最小化理论的最新进展，给出了数值示例，对金融衍生品定价与风险管理研究者有参考价值。
Almost 20 years ago Föllmer and Schweizer (1989) suggested a simple and influential scheme for the computation of hedging strategies in an incomplete market. Their approach of local risk minimization results in a sequence of one‐period least squares regressions running recursively backward in time. In the meantime, there have been significant developments in the global risk minimization theory for semimartingale price processes. In this paper we revisit hedging by sequential regression in the context of global risk minimization, in the light of recent results obtained by Černý and Kallsen (2007) . A number of illustrative numerical examples are given.