英文标题：
《Portfolio Optimization Managing Value at Risk under Heavy Tail Return,
using Stochastic Maximum Principle》
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作者：
Subhojit Biswas, Mrinal K.Ghosh and Diganta Mukherjee
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最新提交年份：
2020
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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 managing the Value at Risk (VaR) assuming a heavy tailed distribution of the stock prices return. We use a stochastic maximum principle to formulate the dynamic optimisation problem. The equations which we obtain does not have any explicit analytical solution, so we look for accurate approximations to estimate the value function and optimal strategy. As our calibration strategy is non-parametric in nature, no prior knowledge on the form of the distribution function is needed. We also provide detailed empirical illustration using real life data. Our results show close concordance with financial intuition.We expect that our results will add to the arsenal of the high frequency traders.
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中文摘要：
我们考虑一个投资者，其投资组合由单一风险资产和无风险资产组成，他希望在管理风险价值（VaR）的前提下，最大化其投资组合的预期效用，假设股票价格回报率服从重尾分布。我们使用随机极大值原理来描述动态优化问题。我们得到的方程没有任何显式的解析解，因此我们寻求精确的近似值来估计值函数和最优策略。由于我们的校准策略本质上是非参数的，因此不需要关于分布函数形式的先验知识。我们还使用实际数据提供了详细的实证说明。我们的结果与财务直觉非常一致。我们预计，我们的结果将为高频交易者的军火库增添一份力量。
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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
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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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