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arXiv 2305.18136q-fin.MFq-fin.PM
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离散时间高斯框架下的指数效用最大化

Exponential Utility Maximization in a Discrete Time Gaussian Framework

Yan Dolinsky, Or Zuk

AI总结:

本文研究了离散时间高斯框架下的指数效用最大化问题,考虑了投资者获知价格变化存在延迟的情况,并基于已有理论和最优投资组合猜测提出求解方法。

摘要:

本短文旨在求解离散时间指数效用最大化问题,其中标的资产服从多元正态分布。除数理金融中的常规设定外,我们还考虑了知情投资者在获知风险资产价格变化时存在延迟的情况。求解方法基于文献[4]的理论及对最优投资组合的猜测。

英文摘要:

The aim of this short note is to present a solution to the discrete time exponential utility maximization problem in a case where the underlying asset has a multivariate normal distribution. In addition to the usual setting considered in Mathematical Finance, we also consider an investor who is informed about the risky asset's price changes with a delay. Our method of solution is based on the theory developed in [4] and guessing the optimal portfolio.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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