On the Assessment of Coherent Economic-Capital Structures

Mutual Funds Pub Date : 2021-04-26 DOI:10.2139/ssrn.1735187

Mazin A. M. Al Janabi

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Moreover, in this paper, the authors develop a dynamic nonlinear portfolio selection model and an optimization algorithm which allocates both economic capital and trading assets by minimizing L-VaR subject to the constraints that the expected return, trading volume and liquidation horizon should meet the budget limits set by the fund manager. The empirical results strongly confirm the importance of enforcing financially and operationally meaningful nonlinear and dynamic constraints, when they are available, on the L-VaR optimization procedure. References and Further Reading: Al Janabi, M.A.M., Ferrer, R., and Shahzad, S. J. H., (2019). “Liquidity-adjusted value-at-risk optimization of a multi-asset portfolio using a vine copula approach”. Physica A: Statistical Mechanics and its Applications, Volume 536, Article 122579. Al Janabi, M.A.M., Arreola-Hernández, Jose, Berger, Theo, Khuong Nguyen, Duc, (2017), “Multivariate Dependence and Portfolio Optimization Algorithms under Illiquid Market Conditions”, European Journal of Operational Research, Vol. 259, No. 3, pp. 1121-1131. Al Janabi, M.A.M. (2021a), “Is Optimum Always Optimal? A Revisit of the Mean-Variance Method under Nonlinear Measures of Dependence and Non-Normal Liquidity Constraints”. Journal of Forecasting, Vol. 40, No. 3, pp. 387-415. Al Janabi, M.A.M. (2021b), “Multivariate Portfolio Optimization under Illiquid Market Prospects: A Review of Theoretical Algorithms and Practical Techniques for Liquidity Risk Management”. Journal of Modelling in Management, Vol. 16, No. 1, pp. 288-309. Al Janabi, M.A.M. (2014), “Optimal and Investable Portfolios: An Empirical Analysis with Scenario Optimization Algorithms under Crisis Market Prospects”, Economic Modelling, Vol. 40, pp. 369-381. Al Janabi, M.A.M. (2015), “Scenario Optimization Technique for the Assessment of Downside-Risk and Investable Portfolios in Post-Financial Crisis”, Int. J. of Financial Engineering, Vol. 2, No. 3, pp. 1550028-1 to 1550028-28. Al Janabi, M.A.M. (2013), “Optimal and Coherent Economic-Capital Structures: Evidence from Long and Short-Sales Trading Positions under Illiquid Market Perspectives”, Annals of Operations Research, Vol. 205, No. 1, pp. 109-139. Al Janabi, M.A.M. (2012), “Optimal Commodity Asset Allocation with a Coherent Market Risk Modeling”, Review of Financial Economics, Vol. 21, No. 3, pp. 131-140. Al Janabi, M.A.M. (2011), “A Generalized Theoretical Modeling Approach for the Assessment of Economic Capital under Asset Market Liquidity Risk Constraints”, Service Industries Journal, Vol. 31, No. 13 & 14, pp. 2193-2221. Al Janabi, M. A.M. (2008), “Integrating liquidity risk factor into a parametric value at risk Method”, Journal of Trading, Vol. 3, No. 3, pp. 76–87. Arreola-Hernandez, J. and Al Janabi, M.A.M. (2020), “Forecasting of dependence, market and investment risks of a global index portfolio”. Journal of Forecasting, Vol. 39, No. 3, pp. 512-532. Arreola-Hernandez, J., Hammoudeh, S., Khuong, N.D., Al Janabi, M.A.M., and Reboredo, J.C., (2017), “Global financial crisis and dependence risk analysis of sector portfolios: a vine copula approach,” Applied Economics, Vol. 49, No. 25, pp. 2409–2427. Arreola-Hernandez, J., Al Janabi, M.A.M., Hammoudeh, S. and Nguyen, D.K. (2015), “Time lag dependence, cross-correlation and risk analysis of U.S. energy and non-energy stock portfolios,” Journal of Asset Management, Vol. 16, No. 7, pp. 467-483. Asadi, S., and Al Janabi, M.A.M. (2020), “Measuring market and credit risk under Solvency II: Evaluation of the standard technique versus internal models for stock and bond markets”, European Actuarial Journal, Vol. 10, No. 2, pp. 425–456. Grillini, S., Sharma, A., Ozkan, A., & Al Janabi, M.A.M. (2019), “Pricing of time-varying illiquidity within the Eurozone: Evidence using a Markov switching liquidity-adjusted capital asset pricing model”. International Review of Financial Analysis, Vol. 64, pp. 145-158. Uddin, M.S., Chi, G., Al Janabi, M.A.M., and Habib, T., (2020), “Leveraging random forest in micro-enterprises credit risk modeling for accuracy and interpretability”. 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引用次数: 0

Abstract

This research study analyses, from a fund manager’s perspective, the performance of liquidity adjusted risk modeling in obtaining optimal and coherent economic capital structures, subject to meaningful operational and financial constraints as specified by the fund manager. Specifically, the paper proposes a re-engineered and robust approach to optimal economic capital allocation, in a Liquidity-Adjusted Value at Risk (L-VaR) framework, and particularly from the perspective of trading portfolios that have both long and short trading. This paper expands previous approaches by explicitly modeling the liquidation of trading portfolios, over the holding period, with the aid of an appropriate scaling of the multiple-assets’ L-VaR matrix along with GARCH-M technique to forecast conditional volatility and expected return. Moreover, in this paper, the authors develop a dynamic nonlinear portfolio selection model and an optimization algorithm which allocates both economic capital and trading assets by minimizing L-VaR subject to the constraints that the expected return, trading volume and liquidation horizon should meet the budget limits set by the fund manager. The empirical results strongly confirm the importance of enforcing financially and operationally meaningful nonlinear and dynamic constraints, when they are available, on the L-VaR optimization procedure.

References and Further Reading:

Al Janabi, M.A.M., Ferrer, R., and Shahzad, S. J. H., (2019). “Liquidity-adjusted value-at-risk optimization of a multi-asset portfolio using a vine copula approach”. Physica A: Statistical Mechanics and its Applications, Volume 536, Article 122579.

Al Janabi, M.A.M., Arreola-Hernández, Jose, Berger, Theo, Khuong Nguyen, Duc, (2017), “Multivariate Dependence and Portfolio Optimization Algorithms under Illiquid Market Conditions”, European Journal of Operational Research, Vol. 259, No. 3, pp. 1121-1131.

Al Janabi, M.A.M. (2021a), “Is Optimum Always Optimal? A Revisit of the Mean-Variance Method under Nonlinear Measures of Dependence and Non-Normal Liquidity Constraints”. Journal of Forecasting, Vol. 40, No. 3, pp. 387-415.

Al Janabi, M.A.M. (2021b), “Multivariate Portfolio Optimization under Illiquid Market Prospects: A Review of Theoretical Algorithms and Practical Techniques for Liquidity Risk Management”. Journal of Modelling in Management, Vol. 16, No. 1, pp. 288-309.

Al Janabi, M.A.M. (2014), “Optimal and Investable Portfolios: An Empirical Analysis with Scenario Optimization Algorithms under Crisis Market Prospects”, Economic Modelling, Vol. 40, pp. 369-381.

Al Janabi, M.A.M. (2015), “Scenario Optimization Technique for the Assessment of Downside-Risk and Investable Portfolios in Post-Financial Crisis”, Int. J. of Financial Engineering, Vol. 2, No. 3, pp. 1550028-1 to 1550028-28.

Al Janabi, M.A.M. (2013), “Optimal and Coherent Economic-Capital Structures: Evidence from Long and Short-Sales Trading Positions under Illiquid Market Perspectives”, Annals of Operations Research, Vol. 205, No. 1, pp. 109-139.

Al Janabi, M.A.M. (2012), “Optimal Commodity Asset Allocation with a Coherent Market Risk Modeling”, Review of Financial Economics, Vol. 21, No. 3, pp. 131-140.

Al Janabi, M.A.M. (2011), “A Generalized Theoretical Modeling Approach for the Assessment of Economic Capital under Asset Market Liquidity Risk Constraints”, Service Industries Journal, Vol. 31, No. 13 & 14, pp. 2193-2221.

Al Janabi, M. A.M. (2008), “Integrating liquidity risk factor into a parametric value at risk Method”, Journal of Trading, Vol. 3, No. 3, pp. 76–87.

Arreola-Hernandez, J. and Al Janabi, M.A.M. (2020), “Forecasting of dependence, market and investment risks of a global index portfolio”. Journal of Forecasting, Vol. 39, No. 3, pp. 512-532.

Arreola-Hernandez, J., Hammoudeh, S., Khuong, N.D., Al Janabi, M.A.M., and Reboredo, J.C., (2017), “Global financial crisis and dependence risk analysis of sector portfolios: a vine copula approach,” Applied Economics, Vol. 49, No. 25, pp. 2409–2427.

Arreola-Hernandez, J., Al Janabi, M.A.M., Hammoudeh, S. and Nguyen, D.K. (2015), “Time lag dependence, cross-correlation and risk analysis of U.S. energy and non-energy stock portfolios,” Journal of Asset Management, Vol. 16, No. 7, pp. 467-483.

Asadi, S., and Al Janabi, M.A.M. (2020), “Measuring market and credit risk under Solvency II: Evaluation of the standard technique versus internal models for stock and bond markets”, European Actuarial Journal, Vol. 10, No. 2, pp. 425–456.

Grillini, S., Sharma, A., Ozkan, A., & Al Janabi, M.A.M. (2019), “Pricing of time-varying illiquidity within the Eurozone: Evidence using a Markov switching liquidity-adjusted capital asset pricing model”. International Review of Financial Analysis, Vol. 64, pp. 145-158.

Uddin, M.S., Chi, G., Al Janabi, M.A.M., and Habib, T., (2020), “Leveraging random forest in micro-enterprises credit risk modeling for accuracy and interpretability”. International Journal of Finance & Economics, Early View: https://doi.org/10.1002/ijfe.2346

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论经济资本结构一致性的评估

本研究从基金经理的角度分析了流动性调整风险模型在基金经理指定的有意义的运营和财务约束条件下，在获得最优和连贯的经济资本结构方面的表现。具体而言，本文提出了一种重新设计的稳健方法，在流动性调整后的风险价值(L-VaR)框架下，特别是从多头和空头交易的交易组合的角度来实现最优经济资本配置。本文扩展了以前的方法，通过明确地建模交易组合的清算，在持有期间，借助于多资产的L-VaR矩阵的适当缩放以及GARCH-M技术来预测条件波动率和预期收益。此外，本文还建立了一个动态非线性投资组合选择模型和优化算法，该模型在期望收益、交易量和清算期限满足基金经理设定的预算限制的约束下，以最小化L-VaR来配置经济资本和交易资产。实证结果有力地证实了在L-VaR优化过程中执行财务和运营上有意义的非线性和动态约束的重要性。参考文献和深入阅读:Al Janabi, m.a.m.， Ferrer, R.和Shahzad, s.j.h.，(2019)。“使用葡萄球菌方法的多资产组合的流动性调整风险价值优化”。物理学A:统计力学及其应用，第536卷，第122579条。Al Janabi, M.A.M Arreola-Hernández, Jose, Berger, Theo, Khuong Nguyen, Duc，(2017)，“非流动性市场条件下的多元依赖和投资组合优化算法”，欧洲运筹学杂志，Vol. 259, No. 3, pp. 1121-1131。Al Janabi, M.A.M. (2021a)，“最优总是最优吗?”非线性依赖测度和非正态流动性约束下均值-方差法的再探讨”。《预测学刊》，第40卷第3期，第387-415页。Al Janabi, M.A.M. (2021b)，“非流动性市场下的多元投资组合优化:流动性风险管理的理论算法和实践技术综述”。管理建模学报，第16卷，第1期，第288-309页。Al Janabi, M.A.M.(2014)，“最优和可投资投资组合:危机市场前景下情景优化算法的实证分析”，《经济建模》第40卷，第369-381页。Al Janabi, M.A.M.(2015)，“金融危机后下行风险与可投资组合评估的情景优化技术”，国际投资管理杂志。金融工程学报，第2卷第3期，第1550028-1 ~ 1550028-28页。Al Janabi, M.A.M.(2013)，“最优和连贯的经济资本结构:非流动性市场视角下的多头和空头交易头寸的证据”，运筹学年鉴，第205卷，第1期，第109-139页。Al Janabi, M.A.M.(2012)，“基于一致性市场风险模型的最优商品资产配置”，《金融经济学评论》，第21卷，第3期，第131-140页。Al Janabi, M.A.M.(2011)，“资产市场流动性风险约束下经济资本评估的广义理论建模方法”，《服务业研究》第31卷第13期;14，第2193-2221页。Al Janabi, M. A.M.(2008)，“将流动性风险因素纳入风险参数值方法”，《交易学报》，第3卷，第3期，第76-87页。Arreola-Hernandez, J.和Al Janabi, M.A.M.(2020)，“全球指数组合的依赖性、市场和投资风险预测”。预测学报，第39卷，第3期，第512-532页。张晓明、张晓明、张晓明(2017)，“全球金融危机与行业投资组合的依赖风险分析:一种藤组合方法”，《应用经济》第49卷，第25期，第2409-2427页。ararreola - hernandez, J.， Al Janabi, m.a.m.， Hammoudeh, S.和Nguyen, D.K.(2015)，“美国能源和非能源股票投资组合的时滞依赖、相互关联和风险分析”，《资产管理杂志》，第16卷，第7期，第467-483页。Asadi, S.和Al Janabi, M.A.M.(2020)，“偿付能力下的市场和信用风险度量:股票和债券市场的标准技术与内部模型的评估”，《欧洲精算杂志》，第10卷，第2期，第425-456页。格里里尼，S.，夏尔马，A.，奥兹坎，A.， &;Al Janabi, M.A.M.(2019)，“欧元区内时变非流动性的定价:使用马尔可夫切换流动性调整资本资产定价模型的证据”。国际金融分析评论，第64卷，第145-158页。Uddin, m.s.， Chi, G.， Al Janabi, m.a.m.和Habib, T.，(2020)，“利用随机森林在微型企业信用风险模型中的准确性和可解释性”。国际金融杂志;经济学，早期观点:https://doi.org/10.1002/ijfe.2346

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