Robust Hedging in Incomplete Markets

We develop a robust optimal dynamic hedging strategy that takes both downside risks and market incompleteness into account for an agent who fears model misspecification. The robust agent is assumed to minimize the shortfall between the assets and liabilities under an endogenous worst case scenario by means of solving a min-max robust optimization problem. When the funding ratio is low, robustness reduces the demand for risky assets. However, cherishing the hope of covering the liabilities, a substantial risk exposure is still optimal. A longer investment horizon or a higher funding ratio weakens the investor's fear of model misspecification. If the expected equity return is overestimated, the initial capital requirement for hedging can be decreased by following the robust strategy