在内生定价下的效用最大化
Utility maximization under endogenous pricing
AI总结:
本文研究了在内生定价机制下,大型投资者如何通过解决非线性后向随机偏微分方程来实现预期效用最大化,并探讨了不同条件下的解存在性和光滑性。
摘要:
我们研究了一个大型投资者在不完全金融市场中进行交易时的预期效用最大化问题,该市场具有内生的永久市场影响。资产价格假设遵循一个非线性价格曲线,该曲线以市场中代表性流动性提供者的效用无差异曲线报价。利用广义次微分,我们证明可以通过一组耦合的前向后向随机微分方程(FBSDEs)来完全表征最优性,这对应于一个非线性后向随机偏微分方程(BSPDE)。我们展示了在代表性市场做市商的驱动函数至少二次增长或大型投资者的效用函数比二次衰减或指数性时,最优投资问题和FBSDEs解的存在性。此外,我们还推导了BSPDEs解存在性的光滑性结果。当市场是完整的、驱动函数是正齐次的或效用函数是指数型时,提供了示例。
英文摘要:
We study the expected utility maximization problem of a large investor who is allowed to make transactions on tradable assets in an incomplete financial market with endogenous permanent market impacts. The asset prices are assumed to follow a nonlinear price curve quoted in the market as the utility indifference curve of a representative liquidity supplier. Using generalized subgradients, we show that optimality can be fully characterized via a system of coupled forward-backward stochastic differential equations (FBSDEs) which corresponds to a non-linear backward stochastic partial differential equation (BSPDE). We show existence of solutions to the optimal investment problem and the FBSDEs in the case where the driver function of the representative market maker grows at least quadratically or the utility function of the large investor falls faster than quadratically or is exponential. Furthermore, we derive smoothness results for the existence of solutions of BSPDEs. Examples are provided when the market is complete, the driver is positively homogeneous or the utility function is exponential.
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