Mazin A.M. Al Janabi

Modeling Time-Varying Volatility and Expected Returns: Evidence from the GCC and MENA Regions

The aim of this study is to investigate empirically the underlying nexus of stock market returns and volatility in the Gulf Cooperation Council (GCC) countries and Middle East and North Africa (MENA) region by using the GARCH-M model. We find that volatility is time-varying in all countries, which indicates substantial variation in the degree of risk across time. However, we do not find empirical support that this time-varying volatility significantly explains expected returns, except in the case of Kuwait, United Arab Emirates, and the MENA region portfolio. Our findings show that stock return volatility is negatively correlated with stock returns in these three markets under the assumption of investor risk aversion. This lends some support to the hypothesis of a volatility-driven negative relationship in the literature. The policy implications of our results are discussed.

Commodity price risk management: Valuation of large trading portfolios under adverse and illiquid market settings

Given the rising need for measuring and controlling commodity price risk exposure, trading risk prediction under illiquid and adverse market conditions plays an increasing role in commodity and financial markets. The aim of this paper is to close the void in commodity trading risk management literature, particularly from the perspective of large trading portfolios, by illustrating how the modified Value-at-Risk (VaR) method can be used by a commodity trading unit in reporting risk exposure, assessing risk reduction alternatives and setting optimised risk limits. In this study we put forward a re-engineered VaR model relevant for commodity trading units that have long- and short-selling trading positions and suggest potential applications of VaR in the context of commodity risk management. To the best of our knowledge, this is the first research paper that addresses the issue of liquidity trading risk management in commodity markets with direct applications to a larger portfolio of distinctive assets. This paper provides real-world techniques and realistic asset allocation strategies that can be applied to commodity trading portfolios in illiquid markets and under adverse market conditions. The modelling technique is based on the renowned concept of liquidity-adjusted VaR (L-VaR), along with the creation of a software tool utilising matrix-algebra techniques. As such, our comprehensive risk model can simultaneously handle market risk analysis under normal and severe market settings as well as take into account the effects of illiquidity of traded commodities. In order to illustrate the proper use of L-VaR under stressed and illiquid market conditions, real-world examples and feasible reports of liquidity trading risk management are presented for a portfolio of 25 distinct commodities, within a multivariate context and under the notion of several correlation factors along with different liquidity horizons. The example and discussions are widely applicable to any commodity end-user, providing potential applications to practitioners and research ideas to academics.

On the use of value at risk for managing foreign‐exchange exposure in large portfolios

Purpose - 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. Design/methodology/approach - 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. Findings - 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. Practical implications - 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. Originality/value - 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.

Optimal and coherent economic-capital structures: evidence from long and short-sales trading positions under illiquid market perspectives

This paper broadens research literature associated with the assessment of modern portfolio risk management techniques by presenting a thorough modeling of nonlinear dynamic asset allocation and management under the supposition of illiquid and adverse market settings. 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-sales trading positions. 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 subject to some selected financial and operational rational constraints. The empirical results strongly confirm the importance of enforcing financially and operationally meaningful nonlinear and dynamic constraints, when they are available, on economic capital optimization procedure. The empirical results are interesting in terms of theory as well as practical applications and can aid in developing robust portfolio management algorithms that financial entities could consider in light of the aftermath of the latest financial crisis.This paper broadens research literature associated with the assessment of modern portfolio risk management techniques by presenting a thorough modeling of nonlinear dynamic asset allocation and management under the supposition of illiquid and adverse market settings. 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-sales trading positions. 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 subject to some selected financial and operational rational constraints. The empirical results strongly confirm the importance of enforcing financially and operationally meaningful nonlinear and dynamic constraints, when they are available, on economic capital optimization procedure. The empirical results are interesting in terms of theory as well as practical applications and can aid in developing robust portfolio management algorithms that financial entities could consider in light of the aftermath of the latest financial crisis.

A generalized theoretical modelling approach for the assessment of economic-capital under asset market liquidity risk constraints

This paper proposes a concrete theoretical foundation and a new modelling framework that attempts to tackle the issue of market/liquidity risk and economic-capital estimation at a portfolio level by combining two mutual asset market/liquidity risk models. In essence, this study extends research literature related to the assessment of the asset market/liquidity risk by providing a generalized theoretical modelling 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 and is modelled based on the concept of liquidity-adjusted value-at-risk framework, while the second component focuses on the risk of variation in transactions costs due to the bid-ask spreads and it attempts to measure the likelihood that it will cost more than expected to liquidate the asset position. 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. The modelling framework can be constructive for financial service industries in emerging-economies and particularly in reinforcing rational economic-capital allocation in light of the aftermaths of the sub-prime financial crisis.This paper proposes a concrete theoretical foundation and a new modelling framework that attempts to tackle the issue of market/liquidity risk and economic-capital estimation at a portfolio level by combining two mutual asset market/liquidity risk models. In essence, this study extends research literature related to the assessment of the asset market/liquidity risk by providing a generalized theoretical modelling 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 and is modelled based on the concept of liquidity-adjusted value-at-risk framework, while the second component focuses on the risk of variation in transactions costs due to the bid-ask spreads and it attempts to measure the likelihood that it will cost more than expected to liquidate the asset position. 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. The modelling framework can be constructive for financial service industries in emerging-economies and particularly in reinforcing rational economic-capital allocation in light of the aftermaths of the sub-prime financial crisis.

MARKET LIQUIDITY AND STRATEGIC ASSET ALLOCATION: APPLICATIONS TO GCC STOCK EXCHANGES

This paper aims at investigating issues of asset allocation and equity trading risk in the Gulf Cooperation Council (GCC) stock markets. The intent of this work is to bridge the gap in current asset market liquidity risk management methodologies and to assist GCC financial institutions in developing proactive asset market liquidity risk management techniques to assess potential market risks in light of the upshots of the current financial crisis. Using daily data of main market indicators for the period 2004–2009 and the Liquidity-Adjusted Value at Risk (L-VaR) model, the author finds that the distribution of the equity returns in the GCC stock markets is far from being normal and thus justifies using the L-VaR model, combined with other methods such as stress-testing, to incorporate the other remaining risks. Furthermore, the author shows that although there is a clear departure from normality, the asset market liquidity risk can be estimated without the need of complex mathematical and analytical procedures. To this end, several financial modeling strategies are achieved with the objective of creating a realistic framework of equity trading risk measurement in addition to the instigation of a practical iterative optimization technique for the calculation of maximum authorized L-VaR limits, subject to meaningful real-word operational constraints. Our modeling technique and empirical analysis have important implications for the GCC financial markets and can aid local financial institutions in developing advanced internal risk models and in complying with the requirements of the Basel II committee on capital adequacy.This paper aims at investigating issues of asset allocation and equity trading risk in the Gulf Cooperation Council (GCC) stock markets. The intent of this work is to bridge the gap in current asset market liquidity risk management methodologies and to assist GCC financial institutions in developing proactive asset market liquidity risk management techniques to assess potential market risks in light of the upshots of the current financial crisis. Using daily data of main market indicators for the period 2004–2009 and the Liquidity-Adjusted Value at Risk (L-VaR) model, the author finds that the distribution of the equity returns in the GCC stock markets is far from being normal and thus justifies using the L-VaR model, combined with other methods such as stress-testing, to incorporate the other remaining risks. Furthermore, the author shows that although there is a clear departure from normality, the asset market liquidity risk can be estimated without the need of complex mathematical and analytical procedures. To this end, several financial modeling strategies are achieved with the objective of creating a realistic framework of equity trading risk measurement in addition to the instigation of a practical iterative optimization technique for the calculation of maximum authorized L-VaR limits, subject to meaningful real-word operational constraints. Our modeling technique and empirical analysis have important implications for the GCC financial markets and can aid local financial institutions in developing advanced internal risk models and in complying with the requirements of the Basel II committee on capital adequacy.

Risk analysis, reporting and control of equity trading exposure: Viable applications to the Mexican financial markets

This paper provides real-world techniques and optimum asset allocation strategies that can be applied to equity trading portfolios in emerging and illiquid financial markets. Key market risk management methods and procedures that financial entities, regulators and policymakers should consider in formulating their daily market risk management objectives are examined and are adapted to the specific needs of emerging countries. The aim of this paper is to fill a gap in the trading risk management literature and particularly from the perspective of emerging and illiquid markets, such as in the context of the Mexican financial markets. In this paper, we demonstrate a comprehensive and proactive approach for the measurement, management and control of equity trading risk exposure, which takes into account proper adjustments for the illiquidity of both long and short trading/investment positions under normal and severe market conditions and within a multi-security setting. Our approach is based on the renowned concept of Value-at-Risk (VAR) along with the innovation of a software tool utilising matrix-algebra and other optimisation techniques. To illustrate the proper use of VAR and stress-testing (scenario analysis) methods, real-world examples and practical reports of market risk management are calculated and presented for a selected portfolio from the Mexican Stock Market (BMV). 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 the maximum authorised VAR limits.

Incorporating Asset Liquidity Effects in Risk-Capital Modeling

Recent turmoil in financial markets endorses the need for rigorous handling and integration of asset liquidity risk into Value-at-Risk (VaR) models. In this work we develop and test measures of certain kinds of asset liquidity risk that is useful for completing the definition of market risk and for predicting liquidity-adjusted VaR under adverse market conditions. This paper presents a practical simulation framework for the modeling of asset liquidity risk for portfolios that consist of multiple long and short trading assets. We put forward a method whereby the holding periods are adjusted according to the specific needs of each trading portfolio by explicitly modeling a linearlydistributed liquidation scheme by means of a pertinent scaling multiplier. The empirical testing is achieved using daily return data of emerging Gulf-Cooperation-Council (GCC) stock markets. We simulate and analyze different relevant portfolios (of both long and short-sales trading positions) and determine the risk-capital exposure under varied illiquid and adverse market conditions.Recent turmoil in financial markets endorses the need for rigorous handling and integration of asset liquidity risk into Value-at-Risk (VaR) models. In this work we develop and test measures of certain kinds of asset liquidity risk that is useful for completing the definition of market risk and for predicting liquidity-adjusted VaR under adverse market conditions. This paper presents a practical simulation framework for the modeling of asset liquidity risk for portfolios that consist of multiple long and short trading assets. We put forward a method whereby the holding periods are adjusted according to the specific needs of each trading portfolio by explicitly modeling a linearly-distributed liquidation scheme by means of a pertinent scaling multiplier. The empirical testing is achieved using daily return data of emerging Gulf-Cooperation-Council (GCC) stock markets. We simulate and analyze different relevant portfolios (of both long and short-sales trading positions) and determine the risk-capital exposure under varied illiquid and adverse market conditions.

Internal regulations and procedures for financial trading units

It is the purpose of this paper to suggest proactive policies and procedures for the adequate management of trading risk exposure within financial operating units. As such, this paper discusses the relevant risks that trading units should deal with and highlights the main obstacles to the launching of successful trading activities in emerging economies, and thereafter provides a number of viable solutions along with recommended internal regulations and procedures. The objective of this paper is to share with financial markets’ participants, regulators and policy makers some of the authors real-world experiences and observations as a derivatives trader and later as a trading risk manager in emerging markets. The endeavour here is to provide several robust guidelines that can assist both emerging and developed markets in the establishment of sound trading units within a prudential framework of rules and policies. The guidelines and internal regulations that are discussed in this work will be of value to financial entities, regulators and policy makers operating mainly within the context of emerging markets. A number of feasible key risk management rules and procedures that should be considered in strengthening trading units are examined and adapted to the specific needs of emerging markets. This is with the objective of setting up a practical framework for trading risk measurement, management and control reports. The suggested viable guidelines and procedures can be implemented in almost all emerging economies, if they are adapted to correspond to each markets initial level of sophistication. The main contribution of this paper is in the introduction of practical trading risk management internal regulations and procedures. The trading risk management internal rules that are discussed in this work will aid financial markets’ participants, regulators and policy makers in founding sound and up-to-date policies to handle trading risk exposures with special emphasis on foreign exchange trading activities. Although a substantial literature has examined the statistical and economic meaning of trading risk models, this paper provides pragmatic guidelines and internal regulations that can be applied for trading risk management in financial markets. This paper fills a gap in the risk management literature by providing a practitioners views on how to set-up sound and effective trading units, particularly from the perspective of emerging markets. This paper will be of value to those interested in founding a successful and sound trading environment of cash securities and derivative products in emerging and developed markets.

Dynamic equity asset allocation with liquidity-adjusted market risk criterion: Appraisal of efficient and coherent portfolios

This article extends research literature related to the evaluation of modern portfolio risk management techniques by providing a broad modeling of dynamic equity asset allocation under the supposition of illiquid and adverse market settings. This study analyzes, from a fund managers perspective, the performance of liquidity adjusted risk modeling in obtaining efficient and coherent equity trading portfolios subject to realistic operational constraints as specified by the fund manager. Specifically, the article proposes a re-engineered and robust approach to equity optimal portfolio selection, 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 positions or for trading portfolios that consists merely of long positions. Moreover, in this article, the authors develop a dynamic portfolio selection model and an optimization algorithm that allocates equity 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.