{"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}
引用次数: 3
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.
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.
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