英文标题：
《Discrete time portfolio optimisation managing value at risk under heavy
tail return distribution》
---
作者：
Subhojit Biswas and Diganta Mukherjee
---
最新提交年份：
2020
---
英文摘要：
We consider an investor, whose portfolio consists of a single risky asset and a risk free asset, who wants to maximize his expected utility of the portfolio subject to the Value at Risk assuming a heavy tail distribution of the stock prices return. We use Markov Decision Process and dynamic programming principle to get the optimal strategies and the value function which maximize the expected utility for parametric as well as non parametric distributions. Due to lack of explicit solution in the non parametric case, we use numerical integration for optimization
---
中文摘要：
我们考虑一个投资者，其投资组合由一个风险资产和一个无风险资产组成，他希望根据风险价值最大化其投资组合的预期效用，假设股票价格回报率服从厚尾分布。利用马尔可夫决策过程和动态规划原理，得到了参数分布和非参数分布的最优策略和最大化期望效用的值函数。由于在非参数情况下缺乏显式解，我们使用数值积分进行优化
---
分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Portfolio Management 项目组合管理
分类描述：Security selection and optimization, capital allocation, investment strategies and performance measurement
证券选择与优化、资本配置、投资策略与绩效评价
--
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
--

---
PDF下载：
-->