英文标题：
《On Utility Maximisation Under Model Uncertainty in Discrete-Time Markets》
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作者：
Mikl\\\'os R\\\'asonyi and Andrea Meireles-Rodrigues
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最新提交年份：
2020
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英文摘要：
We study the problem of maximising terminal utility for an agent facing model uncertainty, in a frictionless discrete-time market with one safe asset and finitely many risky assets. We show that an optimal investment strategy exists if the utility function, defined either over the positive real line or over the whole real line, is bounded from above. We further find that the boundedness assumption can be dropped provided that we impose suitable integrability conditions, related to some strengthened form of no-arbitrage. These results are obtained in an alternative framework for model uncertainty, where all possible dynamics of the stock prices are represented by a collection of stochastic processes on the same filtered probability space, rather than by a family of probability measures.
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中文摘要：
我们研究了在一个具有一个安全资产和有限多个风险资产的无摩擦离散时间市场中，面对模型不确定性的代理的终端效用最大化问题。我们证明，如果效用函数（定义在正实线或整个实线上）从上方有界，则存在最优投资策略。我们进一步发现，如果我们施加适当的可积条件，与无套利的某种强化形式相关，则可以放弃有界性假设。这些结果是在模型不确定性的另一个框架中获得的，其中所有可能的股票价格动态都由同一过滤概率空间上的随机过程集合表示，而不是由一系列概率测度表示。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Mathematical Finance 数学金融学
分类描述：Mathematical and analytical methods of finance, including stochastic, probabilistic and functional analysis, algebraic, geometric and other methods
金融的数学和分析方法，包括随机、概率和泛函分析、代数、几何和其他方法
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