投资组合条件风险价值优化中的次优性

IF 0.3 4区经济学 Q4 BUSINESS, FINANCE

Journal of Risk Pub Date : 2016-04-07 DOI:10.21314/J0R.2016.330

E. Jakobsons

{"title":"投资组合条件风险价值优化中的次优性","authors":"E. Jakobsons","doi":"10.21314/J0R.2016.330","DOIUrl":null,"url":null,"abstract":"In this paper, we consider the portfolio optimization problem, with conditional value-at-risk as the objective. We summarize commonly used methods of solution and note that the linear programming (LP) approximation is the most generally applicable and easiest to use (the LP uses a Monte Carlo sample from the true asset returns distribution). The suboptimality of the obtained approximate portfolios is then analyzed using a numerical example, with up to 101 assets and Student t - distributed returns, ranging from light to heavy tails. The results can be used as an estimate of the portfolio suboptimality for more general asset returns distributions, based on the number of assets, tail heaviness and fineness of the discretization. Computation times using the different techniques available in the literature are also analyzed.","PeriodicalId":46697,"journal":{"name":"Journal of Risk","volume":"1 1","pages":""},"PeriodicalIF":0.3000,"publicationDate":"2016-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Suboptimality in Portfolio Conditional Value-at-Risk Optimization\",\"authors\":\"E. Jakobsons\",\"doi\":\"10.21314/J0R.2016.330\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we consider the portfolio optimization problem, with conditional value-at-risk as the objective. We summarize commonly used methods of solution and note that the linear programming (LP) approximation is the most generally applicable and easiest to use (the LP uses a Monte Carlo sample from the true asset returns distribution). The suboptimality of the obtained approximate portfolios is then analyzed using a numerical example, with up to 101 assets and Student t - distributed returns, ranging from light to heavy tails. The results can be used as an estimate of the portfolio suboptimality for more general asset returns distributions, based on the number of assets, tail heaviness and fineness of the discretization. Computation times using the different techniques available in the literature are also analyzed.\",\"PeriodicalId\":46697,\"journal\":{\"name\":\"Journal of Risk\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2016-04-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Risk\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.21314/J0R.2016.330\",\"RegionNum\":4,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Risk","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.21314/J0R.2016.330","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}

引用次数: 3

摘要

本文研究了以条件风险价值为目标的投资组合优化问题。我们总结了常用的解决方法，并注意到线性规划(LP)近似是最普遍适用和最容易使用的(LP使用来自真实资产回报分布的蒙特卡罗样本)。然后使用一个数值示例分析所获得的近似投资组合的次优性，该示例包含多达101个资产和学生t分布收益，从轻尾到重尾不等。根据资产数量、尾重和离散化的精细程度，结果可以用来估计更一般的资产收益分布的投资组合次优性。还分析了使用文献中可用的不同技术的计算时间。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Suboptimality in Portfolio Conditional Value-at-Risk Optimization

In this paper, we consider the portfolio optimization problem, with conditional value-at-risk as the objective. We summarize commonly used methods of solution and note that the linear programming (LP) approximation is the most generally applicable and easiest to use (the LP uses a Monte Carlo sample from the true asset returns distribution). The suboptimality of the obtained approximate portfolios is then analyzed using a numerical example, with up to 101 assets and Student t - distributed returns, ranging from light to heavy tails. The results can be used as an estimate of the portfolio suboptimality for more general asset returns distributions, based on the number of assets, tail heaviness and fineness of the discretization. Computation times using the different techniques available in the literature are also analyzed.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Journal of Risk BUSINESS, FINANCE-

CiteScore

1.00

自引率

14.30%

发文量

期刊介绍： This international peer-reviewed journal publishes a broad range of original research papers which aim to further develop understanding of financial risk management. As the only publication devoted exclusively to theoretical and empirical studies in financial risk management, The Journal of Risk promotes far-reaching research on the latest innovations in this field, with particular focus on the measurement, management and analysis of financial risk. The Journal of Risk is particularly interested in papers on the following topics: Risk management regulations and their implications, Risk capital allocation and risk budgeting, Efficient evaluation of risk measures under increasingly complex and realistic model assumptions, Impact of risk measurement on portfolio allocation, Theoretical development of alternative risk measures, Hedging (linear and non-linear) under alternative risk measures, Financial market model risk, Estimation of volatility and unanticipated jumps, Capital allocation.