英文标题：
《Two-Stage Stochastic International Portfolio Optimisation under
  Regular-Vine-Copula-Based Scenarios》
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作者：
Nonthachote Chatsanga and Andrew J. Parkes
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最新提交年份：
2017
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英文摘要：
  In this paper, we present a two-stage stochastic international portfolio optimisation model to find an optimal allocation for the combination of both assets and currency hedging positions. Our optimisation model allows a \"currency overlay\", or a deviation of currency exposure from asset exposure, to provide flexibility in hedging against, or in speculation using, currency exposure. The transaction costs associated with both trading and hedging are also included.   To model the realistic dependence structure of the multivariate return distributions, a new scenario generation method, employing a regular-vine copula is developed. The use of vine copulas allows a better representation of the characteristics of returns, specifically, their non-normality and asymmetric dependencies. It hence improves the representation of the uncertainty underlying decisions needed for international portfolio optimisation problems. Efficient portfolios optimised with scenarios generated from the new vine-copula method are compared with the portfolios from a standard scenario generation method. Experimental results show that the proposed method, using realistic non-normal uncertainty, produces portfolios that give better risk-return reward than those from a standard scenario generation approach, using normal distributions. The difference in risk-return compensation is largest when the portfolios are constrained to require higher returns. The paper shows that it can be important to model the non-normality in uncertainty, and not just assume normal distributions.
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中文摘要：
在本文中，我们提出了一个两阶段随机国际投资组合优化模型，以寻求资产和货币对冲头寸组合的最优配置。我们的优化模型允许“货币叠加”，或货币敞口与资产敞口的偏差，以提供对冲或投机使用货币敞口的灵活性。还包括与交易和对冲相关的交易成本。为了模拟多元收益分布的现实依赖结构，提出了一种新的情景生成方法，该方法采用正则vine copula。vine连接函数的使用可以更好地表示收益的特征，特别是它们的非正态性和非对称依赖性。因此，它改进了国际投资组合优化问题所需的不确定性基础决策的表示。将使用新的vine copula方法生成的情景优化的有效投资组合与标准情景生成方法生成的投资组合进行比较。实验结果表明，该方法利用真实的非正态不确定性，生成的投资组合比使用正态分布的标准情景生成方法生成的投资组合具有更好的风险收益回报。当投资组合被限制要求更高的回报时，风险回报补偿的差异最大。本文表明，对不确定性中的非正态性进行建模是很重要的，而不仅仅是假设正态分布。
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Computational Engineering, Finance, and Science        计算工程、金融和科学
分类描述：Covers applications of computer science to the mathematical modeling of complex systems in the fields of science, engineering, and finance. Papers here are interdisciplinary and applications-oriented, focusing on techniques and tools that enable challenging computational simulations to be performed, for which the use of supercomputers or distributed computing platforms is often required. Includes material in ACM Subject Classes J.2, J.3, and J.4 (economics).
涵盖了计算机科学在科学、工程和金融领域复杂系统的数学建模中的应用。这里的论文是跨学科和面向应用的，集中在技术和工具，使挑战性的计算模拟能够执行，其中往往需要使用超级计算机或分布式计算平台。包括ACM学科课程J.2、J.3和J.4（经济学）中的材料。
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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
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