英文标题：
《Skewed target range strategy for multiperiod portfolio optimization
using a two-stage least squares Monte Carlo method》
---
作者：
Rongju Zhang, Nicolas Langren\\\'e, Yu Tian, Zili Zhu, Fima Klebaner,
Kais Hamza
---
最新提交年份：
2019
---
英文摘要：
In this paper, we propose a novel investment strategy for portfolio optimization problems. The proposed strategy maximizes the expected portfolio value bounded within a targeted range, composed of a conservative lower target representing a need for capital protection and a desired upper target representing an investment goal. This strategy favorably shapes the entire probability distribution of returns, as it simultaneously seeks a desired expected return, cuts off downside risk and implicitly caps volatility and higher moments. To illustrate the effectiveness of this investment strategy, we study a multiperiod portfolio optimization problem with transaction costs and develop a two-stage regression approach that improves the classical least squares Monte Carlo (LSMC) algorithm when dealing with difficult payoffs, such as highly concave, abruptly changing or discontinuous functions. Our numerical results show substantial improvements over the classical LSMC algorithm for both the constant relative risk-aversion (CRRA) utility approach and the proposed skewed target range strategy (STRS). Our numerical results illustrate the ability of the STRS to contain the portfolio value within the targeted range. When compared with the CRRA utility approach, the STRS achieves a similar mean-variance efficient frontier while delivering a better downside risk-return trade-off.
---
中文摘要：
本文针对投资组合优化问题提出了一种新的投资策略。该策略将目标范围内的预期投资组合价值最大化，该范围由代表资本保护需求的保守下目标和代表投资目标的期望上目标组成。这种策略有利于塑造整个回报概率分布，因为它同时寻求期望的预期回报，切断下行风险，并隐含地限制波动率和更高时刻。为了说明这种投资策略的有效性，我们研究了一个具有交易成本的多周期投资组合优化问题，并开发了一种两阶段回归方法，该方法在处理高凹、突变或不连续函数等困难收益时改进了经典的最小二乘蒙特卡罗（LSMC）算法。我们的数值结果表明，对于常数相对风险规避（CRRA）效用方法和所提出的倾斜目标距离策略（STRS），相对于经典的LSMC算法都有很大的改进。我们的数值结果说明了STR将投资组合价值控制在目标范围内的能力。与CRRA效用法相比，STRS实现了类似的均值-方差有效边界，同时提供了更好的下行风险-回报权衡。
---
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：Computational Finance 计算金融学
分类描述：Computational methods, including Monte Carlo, PDE, lattice and other numerical methods with applications to financial modeling
计算方法，包括蒙特卡罗，偏微分方程，格子和其他数值方法，并应用于金融建模
--
一级分类：Quantitative Finance 数量金融学
二级分类：General Finance 一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
--
一级分类：Quantitative Finance 数量金融学
二级分类：Risk Management 风险管理
分类描述：Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
衡量和管理贸易、银行、保险、企业和其他应用中的金融风险
--

---
PDF下载：
-->