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This paper aims to empirically test, from a regulatory portfolio management standpoint, the application of liquidity-adjusted risk techniques in the process of getting optimum and investable economic-capital structures in the Gulf Cooperation Council financial markets, subject to applying various operational and financial optimization restrictions under crisis outlooks.

The author implements a robust methodology to assess regulatory economic-capital allocation in a liquidity-adjusted value at risk (LVaR) context, mostly from the standpoint of investable portfolios analytics that have long- and short-sales asset allocation or for those portfolios that contain long-only asset allocation. The optimization route is accomplished by controlling the nonlinear quadratic objective risk function with certain regulatory constraints along with LVaR-GARCH-M (1,1) procedure to forecast conditional risk parameters and expected returns for multiple asset classes.

The author’s conclusions emphasize that the attained investable economic-capital portfolios lie-off the efficient frontier, yet those long-only portfolios seem to lie near the efficient frontier than portfolios with long- and short-sales assets allocation. In effect, the newly observed market microstructures forms and derived deductions were not apparent in prior research studies (Al Janabi, 2013).

The attained empirical results are quite interesting for practical portfolio optimization, within the environments of big data analytics, reinforcement machine learning, expert systems and smart financial applications. Furthermore, it is quite promising for multiple-asset portfolio management techniques, performance measurement and improvement analytics, reinforcement machine learning and operations research algorithms in financial institutions operations, above all after the consequences of the 2007–2009 financial crisis.

While this paper builds on Al Janabi’s (2013) optimization algorithms and modeling techniques, it varies in the sense that it covers the outcomes of a multi-asset portfolio optimization method under severe event market scenarios and by allowing for both long-only and combinations of long-/short-sales multiple asset. The achieved empirical results, optimization parameters and efficient and investable economic-capital figures were not apparent in Al Janabi’s (2013) paper because the prior evaluation were performed under normal market circumstances and without bearing in mind the impacts of the 2007–2009 global financial crunch.

This paper aims to examine from commodity portfolio managers’ perspective the performance of liquidity adjusted risk modeling in assessing the market risk parameters of a large commodity portfolio and in obtaining efficient and coherent portfolios under different market circumstances.

The implemented market risk modeling algorithm and investment portfolio analytics using reinforcement machine learning techniques can simultaneously handle risk-return characteristics of commodity investments under regular and crisis market settings besides considering the particular effects of the time-varying liquidity constraints of the multiple-asset commodity portfolios.

In particular, the paper implements a robust machine learning method to commodity optimal portfolio selection and within a liquidity-adjusted value-at-risk (LVaR) framework. In addition, the paper explains how the adapted LVaR modeling algorithms can be used by a commodity trading unit in a dynamic asset allocation framework for estimating risk exposure, assessing risk reduction alternates and creating efficient and coherent market portfolios.

The optimization parameters subject to meaningful operational and financial constraints, investment portfolio analytics and empirical results can have important practical uses and applications for commodity portfolio managers particularly in the wake of the 2007–2009 global financial crisis. In addition, the recommended reinforcement machine learning optimization algorithms can aid in solving some real-world dilemmas under stressed and adverse market conditions (e.g. illiquidity, switching in correlations factors signs, nonlinear and non-normal distribution of assets’ returns) and can have key applications in machine learning, expert systems, smart financial functions, internet of things (IoT) and financial technology (FinTech) in big data ecosystems.

This study aims to examine the theoretical foundations for multivariate portfolio optimization algorithms under illiquid market conditions. In this study, special emphasis is devoted to the application of a risk-engine, which is based on the contemporary concept of liquidity-adjusted value-at-risk (LVaR), to multivariate optimization of investment portfolios.

This paper examines the modeling parameters of LVaR technique under event market settings and discusses how to integrate asset liquidity risk into LVaR models. Finally, the authors discuss scenario optimization algorithms for the assessment of structured investment portfolios and present a detailed operational methodology for computer programming purposes and prospective research design with the backing of a graphical flowchart.

To that end, the portfolio/risk manager can specify different closeout horizons and dependence measures and calculate the necessary LVaR and resulting investable portfolios. In addition, portfolio managers can compare the return/risk ratio and asset allocation of obtained investable portfolios with different liquidation horizons in relation to the conventional Markowitz´s mean-variance approach.

The examined optimization algorithms and modeling techniques have important practical applications for portfolio management and risk assessment, and can have many uses within machine learning and artificial intelligence, expert systems and smart financial applications, financial technology (FinTech), and within big data environments. In addition, it provide key real-world implications for portfolio/risk managers, treasury directors, risk management executives, policymakers and financial regulators to comply with the requirements of Basel III best practices on liquidly risk.

The proposed optimization algorithms can aid in advancing portfolios selection and management in financial markets by assessing investable portfolios subject to meaningful operational and financial constraints. Furthermore, the robust risk-algorithms and portfolio optimization techniques can aid in solving some real-world dilemmas under stressed and adverse market conditions, such as the effect of liquidity when it dries up in financial and commodity markets, the impact of correlations factors when there is a switching in their signs and the integration of the influence of the nonlinear and non-normal distribution of assets’ returns in portfolio optimization and management.

Given the rising need for measuring and controlling of financial risk as proposed in Basel II and Basel III Capital Adequacy Accords, trading risk assessment under illiquid market conditions plays an increasing role in banking and financial sectors, particularly in emerging financial markets. The purpose of this chapter is to investigate asset liquidity risk and to obtain a Liquidity-Adjusted Value at Risk (L-VaR) estimation for various equity portfolios. The assessment of L-VaR is performed by implementing three different asset liquidity models within a multivariate context along with GARCH-M method (to estimate expected returns and conditional volatility) and by applying meaningful financial and operational constraints. Using more than six years of daily return dataset of emerging Gulf Cooperation Council (GCC) stock markets, we find that under certain trading strategies, such as short selling of stocks, the sensitivity of L-VaR statistics are rather critical to the selected internal liquidity model in addition to the degree of correlation factors among trading assets. As such, the effects of extreme correlations (plus or minus unity) are crucial aspects to consider in selecting the most adequate internal liquidity model for economic capital allocation, especially under crisis condition and/or when correlations tend to switch sings. This chapter bridges the gap in risk management literatures by providing real-world asset allocation tactics that can be used for trading portfolios under adverse markets’ conditions. The approach to computing L-VaR has been arrived at through the application of three distinct liquidity models and the obtained results are used to draw conclusions about the relative liquidity of the diverse equity portfolios.

It is the purpose of this article to empirically test the risk parameters for larger foreign‐exchange portfolios and to suggest real‐world policies and procedures for the management of market risk with the aid of value at risk (VaR) methodology. The aim of this article is to fill a void in the foreign‐exchange risk management literature and particularly for large portfolios that consist of long and short positions of multi‐currencies of numerous developed and emerging economies.

In this article, a constructive approach for the management of risk exposure of foreign‐exchange securities is demonstrated, which takes into account proper adjustments for the illiquidity of both long and short trading/investment positions. The approach is based on the renowned concept of VaR along with the innovation of a software tool utilizing matrix‐algebra and other optimization techniques. Real‐world examples and reports of foreign‐exchange risk management are presented for a sample of 40 distinctive countries.

A number of realistic case studies are achieved with the objective of setting‐up a practical framework for market risk measurement, management and control reports, in addition to the inception of a practical procedure for the calculation of optimum VaR limits structure. The attainment of the risk management techniques is assessed for both long and short proprietary trading and/or active investment positions.

The main contribution of this article is the introduction of a practical risk approach to managing foreign‐exchange exposure in large proprietary trading and active investment portfolios. Key foreign‐exchange risk management methods, rules and procedures that financial entities, regulators and policymakers should consider in setting‐up their foreign‐exchange risk management objectives are examined and adapted to the specific needs of a model of 40 distinctive economies.

Although a substantial literature has examined the statistical and economic meaning of VaR models, this article provides real‐world techniques and optimum asset allocation strategies for large foreign‐exchange portfolios in emerging and developed financial markets. This is with the objective of setting‐up the basis of a methodology/procedure for the measurement, management and control of foreign‐exchange exposures in the day‐to‐day trading and/or asset management operations.

The purpose of this paper is to provide proactive risk management techniques and strategies that can be applied to trading and investment portfolios in emerging and Islamic illiquid financial markets, such as the Moroccan foreign exchange and stock markets.

This paper demonstrates a practical approach for the measurements, management and control of market risk exposure for financial portfolios that contain illiquid foreign exchange and equity securities. This approach is based on the renowned concept of value‐at‐risk (VAR) along with the innovation of a software tool utilizing matrix‐algebra technique.

In order to illustrate the proper use of VAR and stress‐testing methods, real‐world examples and feasible reports of risk management are presented for the Moroccan financial markets. To this end, several case studies were achieved with the objective of creating a realistic framework of trading risk measurement and control reports in addition to the inception of procedures for the calculation of VAR limits.

The versatile risk management procedures that are discussed in this work will be of value to financial entities, regulators and policymakers operating within the context of emerging and Islamic markets. The risk management procedures that are outlined in this paper will aid in setting‐up of realistic policies for the management of trading/investment risk exposures in illiquid markets. The document includes comprehensive theory, analyses sections, conclusions and recommendations, and full viable risk management reports.

Even though considerable literatures have investigated the statistical and economic significance of VAR models, this article provides real‐world techniques and optimum asset allocation strategies that are useful for trading/investment portfolios in emerging and Islamic financial markets. This is with the objective of setting‐up the basis of a proactive methodology/procedure for the measurement, management and control of equity and foreign exchange exposures in the day‐to‐day trading/investment operations.

The aim of this paper is to fill a gap in the foreign‐exchange trading risk‐management literature and particularly from the perspective of emerging and illiquid markets, such as in the context of the Moroccan foreign‐exchange market.

This paper, demonstrates a constructive approach, for the management of trading risk exposure of foreign‐exchange securities, which takes into account proper adjustments for the illiquidity of both long and short trading positions. The approach is based on the renowned concept of value at risk (VaR) along with the innovation of a software tool utilizing matrix‐algebra and other optimization techniques.

Several case studies, on the Moroccan Dirham, were achieved with the objective of setting‐up a practical framework of trading risk measurement, management and control reports, in addition to the inception of a practical procedure for the calculation of optimum VaR limits structure.

In this work, the risk‐management procedures that are discussed will aid financial markets' participants, regulators and policymakers, operating within emerging economies, in founding sound and proactive policies to handle foreign‐exchange trading risk exposures. The document includes comprehensive theory, analyses sections, conclusions and recommendations, and full real‐world foreign‐exchange trading risk‐management reports.

Although a substantial literature has examined the statistical and economic meaning of VaR models, this article provides real‐world techniques and optimum asset allocation strategies that are useful for trading portfolios in emerging and illiquid financial markets. This is with the objective of setting‐up the basis of a proactive methodology/procedure for the measurement, management and control of foreign‐exchange exposures in the day‐to‐day trading operations.

This paper seeks to provide foreign exchange risk measurement/management techniques and strategies that can be applied to investment and trading portfolios in emerging financial markets, such as the Moroccan foreign exchange market, with the objective of setting up the basis of a methodology/procedure for the measurement, management and control of foreign exchange exposures in the day‐to‐day trading operations.

Demonstrates a proactive approach for the measurements, management and control of market risk exposure for financial trading portfolios that contain foreign exchange securities. This approach is based on the renowned concept of value‐at‐risk (VAR) along with the creation of a software tool utilizing matrix‐algebra technique. In order to illustrate the proper use of VAR and stress‐testing methods, real‐world examples and practical reports of foreign exchange trading risk management are presented for the Moroccan Dirham.

To this end, several case studies were achieved with the objective of setting up a practical framework of trading risk measurement and control reports in addition to the inception of procedures for the calculation of VAR's limits. Moreover, the effects of hedging of foreign exchange trading exposures with reciprocal equity trading positions were explored and quantified. Finally, initial empirical tests of the long‐term behavior of the Moroccan foreign exchange and debt markets were quantified and analyzed.

In this work, key foreign exchange trading risk management methods, rules and procedures that financial entities, regulators and policymakers should consider in setting up their daily foreign exchange trading risk management objectives are examined and adapted to the specific needs of emerging markets, such as in the context of the Moroccan foreign exchange market.

This paper fills a gap in the foreign exchange risk management literature especially in the emerging markets perspective. The risk management procedures that are discussed in this work will aid financial markets' participants, regulators and policymakers in founding sound and up‐to‐date policies to handle foreign exchange risk exposures.

The purpose of this paper is to originate a proactive approach for the quantification and analysis of liquidity risk for trading portfolios that consist of multiple equity assets.

The paper presents a coherent modeling method whereby the holding periods are adjusted according to the specific needs of each trading portfolio. This adjustment can be attained for the entire portfolio or for any specific asset within the equity trading portfolio. This paper extends 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' liquidity‐adjusted value‐at‐risk matrix. The key methodological contribution is a different and less conservative liquidity scaling factor than the conventional root‐t multiplier.

The proposed coherent liquidity multiplier is a function of a predetermined liquidity threshold, defined as the maximum position which can be unwound without disturbing market prices during one trading day, and is quite straightforward to put into practice even by very large financial institutions and institutional portfolio managers. Furthermore, it is designed to accommodate all types of trading assets held and its simplicity stems from the fact that it focuses on the time‐volatility dimension of liquidity risk instead of the cost spread (bid‐ask margin) as most researchers have done heretofore.

Using more than six years of daily return data, for the period 2004‐2009, of emerging Gulf Cooperation Council (GCC) stock markets, the paper analyzes different structured and optimum trading portfolios and determine coherent risk exposure and liquidity risk premium under different illiquid and adverse market conditions and under the notion of different correlation factors.

This paper fills a main gap in market and liquidity risk management literatures by putting forward a thorough modeling of liquidity risk under the supposition of illiquid and adverse market settings. The empirical results are interesting in terms of theory as well as practical applications to trading units, asset management service entities and other financial institutions. This coherent modeling technique and empirical tests can aid the GCC financial markets and other emerging economies in devising contemporary internal risk models, particularly in light of the aftermaths of the recent sub‐prime financial crisis.

Since, the early 1990s, emerging markets have started to play an important role in the trading of derivatives products. Despite the fact that these markets are characterized in general as illiquid, segmented, politically unstable, with lack of regulations and historical financial databases, they do have some advantages for markets' participants. This paper aims to discuss some of the main obstacles to the inception of successful derivative products in emerging economies and to provide a number of viable solutions.

The objective of this paper is to share with financial markets' participants, regulators and policymakers some of the author's real‐world experiences and observations as a derivatives trader and later as a trading risk manager in emerging economies. The endeavor here is to provide several robust guidelines that can assist emerging markets in the establishment of sound derivative markets within a prudential framework of rules and policies.

To this end, key risk management rules and procedures that should be considered before dealing with derivative products are examined and adapted to the specific needs of emerging markets. The suggested viable solutions can be implemented in almost all emerging economies, if they are adapted to correspond to each market's initial level of sophistication.

The real‐world guidelines and observations that are discussed in this work will be of value to financial entities, regulators and policymakers operating within the context of emerging markets.

This paper fills a gap in the risk management literature, especially from the emerging markets perspective, by providing a practitioner's views on how to set‐up sound and effective derivative products markets in emerging economies. The paper will be of value to those interested in founding a successful and sound trading environment of derivative products in emerging markets.