Asset Market Liquidity Risk Management: A Generalized Theoretical Modeling Approach for Trading and Fund Management Portfolios

Mutual Funds Pub Date : 2021-04-26 DOI:10.2139/ssrn.1525787

Mazin A. M. Al Janabi

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This paper extends research literature related to the assessment of asset market/liquidity risk by providing a generalized theoretical modeling underpinning that handle, from the same perspective, market and liquidity risks jointly and integrate both risks into a portfolio setting without a commensurate increase of statistical postulations. As such, we argue that market and liquidity risk components are correlated in most cases and can be integrated into one single market/liquidity framework that consists of two interrelated sub-components. The first component is attributed to the impact of adverse price movements, while the second component focuses on the risk of variation in transactions costs due to bid-ask spreads and it attempts to measure the likelihood that it will cost more than expected to liquidate the asset position. We thereafter propose a concrete theoretical foundation and a new modeling framework that attempts to tackle the issue of market/liquidity risk at a portfolio level by combining two asset market/liquidity risk models. The first model is a re-engineered and robust liquidity horizon multiplier that can aid in producing realistic asset market liquidity losses during the unwinding period. The essence of the model is based on the concept of Liquidity-Adjusted Value-at-Risk (L-VaR) framework, and particularly from the perspective of trading portfolios that have both long and short trading positions. Conversely, the second model is related to the transactions cost of liquidation due to bid-ask spreads and includes an improved technique that tackles the issue of bid-ask spread volatility. As such, the model comprises a new approach to contemplating the impact of time-varying volatility of the bid-ask spread and its upshot on the overall asset market/liquidity risk. 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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Abstract

Asset market liquidity risk is a significant and perplexing subject and though the term market liquidity risk is used quite chronically in academic literature it lacks an unambiguous definition, let alone understanding of the proposed risk measures. To this end, this paper presents a review of contemporary thoughts and attempts vis-à-vis asset market/liquidity risk management. Furthermore, this research focuses on the theoretical aspects of asset liquidity risk and presents critically two reciprocal approaches to measuring market liquidity risk for individual trading securities, and discusses the problems that arise in attempting to quantify asset market liquidity risk at a portfolio level. This paper extends research literature related to the assessment of asset market/liquidity risk by providing a generalized theoretical modeling underpinning that handle, from the same perspective, market and liquidity risks jointly and integrate both risks into a portfolio setting without a commensurate increase of statistical postulations. As such, we argue that market and liquidity risk components are correlated in most cases and can be integrated into one single market/liquidity framework that consists of two interrelated sub-components. The first component is attributed to the impact of adverse price movements, while the second component focuses on the risk of variation in transactions costs due to bid-ask spreads and it attempts to measure the likelihood that it will cost more than expected to liquidate the asset position. We thereafter propose a concrete theoretical foundation and a new modeling framework that attempts to tackle the issue of market/liquidity risk at a portfolio level by combining two asset market/liquidity risk models. The first model is a re-engineered and robust liquidity horizon multiplier that can aid in producing realistic asset market liquidity losses during the unwinding period. The essence of the model is based on the concept of Liquidity-Adjusted Value-at-Risk (L-VaR) framework, and particularly from the perspective of trading portfolios that have both long and short trading positions. Conversely, the second model is related to the transactions cost of liquidation due to bid-ask spreads and includes an improved technique that tackles the issue of bid-ask spread volatility. As such, the model comprises a new approach to contemplating the impact of time-varying volatility of the bid-ask spread and its upshot on the overall asset market/liquidity risk.

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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资产市场流动性风险管理:交易与基金管理组合的广义理论建模方法

资产市场流动性风险是一个重要而令人困惑的主题，尽管市场流动性风险一词在学术文献中被长期使用，但它缺乏明确的定义，更不用说对所提出的风险措施的理解了。为此，本文对-à-vis资产市场/流动性风险管理的当代思想和尝试进行了回顾。此外，本研究侧重于资产流动性风险的理论方面，并提出了两种衡量个人交易证券市场流动性风险的关键互惠方法，并讨论了在投资组合层面量化资产市场流动性风险时出现的问题。本文扩展了与资产市场/流动性风险评估相关的研究文献，提供了一个广义的理论模型基础，从同一角度共同处理市场风险和流动性风险，并将这两种风险整合到一个投资组合设置中，而不需要相应增加统计假设。因此，我们认为市场和流动性风险成分在大多数情况下是相关的，可以整合到一个由两个相互关联的子成分组成的单一市场/流动性框架中。第一个组成部分归因于不利价格变动的影响，而第二个组成部分侧重于由于买卖价差而导致的交易成本变化的风险，并试图衡量清算资产头寸所需成本高于预期的可能性。随后，我们提出了一个具体的理论基础和一个新的建模框架，试图通过结合两个资产市场/流动性风险模型来解决投资组合层面的市场/流动性风险问题。第一个模型是一个重新设计的、强大的流动性视界乘数，可以帮助在平仓期间产生现实的资产市场流动性损失。该模型的本质是基于流动性调整风险价值(L-VaR)框架的概念，特别是从多头和空头交易组合的角度出发。相反，第二个模型与买卖价差引起的清算交易成本有关，并包括一种改进的技术，用于解决买卖价差波动问题。因此，该模型包含了一种新的方法来考虑买卖价差随时间变化的波动性及其对整体资产市场/流动性风险的影响。参考文献及深入阅读: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。Arreola-Hernandez, J.， Hammoudeh, S.， Khuong, N.D, Al Janabi, m.a.m.，和Reboredo, J.C.

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