We consider a financial model where stocks are available for dynamic trading, and European and American options are available for static trading (semi-static trading strategies). We assume that the American options are infinitely divisible, and can only be bought but not sold.  We first get the fundamental theorem of asset pricing (FTAP) using semi-static trading strategies . Using the FTAP result, we further get the dualities for the hedging prices of European and American options. Based on the hedging dualities, we also get the duality for the utility maximization involving semi-static trading strategies .
We consider a financial market where stocks are available for dynamic trading, and European and American options are available for static trading (semi-static trading strategies). We assume that the American options are infinitely divisible, and can only be bought but not sold. In the first part of the paper, we work within the framework without model ambiguity. We first get the fundamental theorem of asset pricing (FTAP) . Using the FTAP , we get the dualities for the hedging prices of European and American options. Based on the hedging dualities, we also get the duality for the utility maximization . In the second part of the paper, we consider the market which admits non-dominated model uncertainty. We first establish the hedging result, and then using the hedging duality we further get the FTAP. Due to the technical difficulty stemming from the non-dominancy of the probability measure set, we use a discretization technique and apply the minimax theorem .
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model
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In the first part of the paper, we work within the framework without model ambiguity.
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using semi-static trading strategies
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result, we further
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involving semi-static trading strategies
. In the second part of the paper, we consider the market which admits non-dominated model uncertainty. We first establish the hedging result, and then using the hedging duality we further get the FTAP. Due to the technical difficulty stemming from the non-dominancy of the probability measure set, we use a discretization technique and apply the minimax theorem