英文标题：
《Portfolio Benchmarking under Drawdown Constraint and Stochastic Sharpe
Ratio》
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作者：
Ankush Agarwal, Ronnie Sircar
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最新提交年份：
2016
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英文摘要：
We consider an investor who seeks to maximize her expected utility derived from her terminal wealth relative to the maximum performance achieved over a fixed time horizon, and under a portfolio drawdown constraint, in a market with local stochastic volatility (LSV). In the absence of closed-form formulas for the value function and optimal portfolio strategy, we obtain approximations for these quantities through the use of a coefficient expansion technique and nonlinear transformations. We utilize regularity properties of the risk tolerance function to numerically compute the estimates for our approximations. In order to achieve similar value functions, we illustrate that, compared to a constant volatility model, the investor must deploy a quite different portfolio strategy which depends on the current level of volatility in the stochastic volatility model.
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中文摘要：
我们考虑一个投资者，在具有局部随机波动性（LSV）的市场中，在固定的时间范围内，在投资组合缩减约束下，寻求最大化从其终端财富中获得的预期效用。在没有价值函数和最优投资组合策略的封闭式公式的情况下，我们通过使用系数展开技术和非线性变换来获得这些数量的近似值。我们利用风险容限函数的正则性来数值计算近似值的估计。为了实现类似的价值函数，我们说明，与恒定波动率模型相比，投资者必须部署完全不同的投资组合策略，这取决于随机波动率模型中当前的波动水平。
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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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