当前位置: X-MOL 学术Math. Financ. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Convex duality and Orlicz spaces in expected utility maximization
Mathematical Finance ( IF 1.6 ) Pub Date : 2019-03-12 , DOI: 10.1111/mafi.12209
Sara Biagini 1 , Aleš Černý 2
Affiliation  

In this paper, we report further progress toward a complete theory of state‐independent expected utility maximization with semimartingale price processes for arbitrary utility function. Without any technical assumptions, we establish a surprising Fenchel duality result on conjugate Orlicz spaces, offering a new economic insight into the nature of primal optima and providing a fresh perspective on the classical papers of Kramkov and Schachermayer. The analysis points to an intriguing interplay between no‐arbitrage conditions and standard convex optimization and motivates the study of the fundamental theorem of asset pricing for Orlicz tame strategies.

中文翻译:

期望效用最大化中的凸对偶性和Orlicz空间

在本文中,我们报告了针对具有完全独立状态的期望效用最大化和半效价过程的任意效用函数的完整理论的进一步进展。在没有任何技术假设的情况下,我们在共轭Orlicz空间上建立了令人惊讶的Fenchel对偶结果,从而为原始最优值的性质提供了新的经济学见识,并为Kramkov和Schachermayer的经典论文提供了新的视角。分析指出了无套利条件与标准凸优化之间有趣的相互作用,并激发了对Orlicz驯服策略的资产定价基本定理的研究。
更新日期:2019-03-12
down
wechat
bug