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The purpose of this paper is to study connections between interest rate risk and credit risk and investigate the inter-risk diversification benefit due to the joint consideration of these risks in the banking book containing sovereign debt.

The paper develops the historical derivative-based value at risk (VaR) for assessing the downside risk of a sovereign debt portfolio through the integrated treatment of interest rate and credit risks. The credit default swaps spreads and the fixed-leg rates of interest rate swap are used as proxies for credit risk and interest rate risk, respectively.

The proposed methodology is applied to the decade-long history of emerging markets sovereign debt. The empirical analysis demonstrates that the diversified VaR benefits from imperfect correlation between the risk factors. Sovereign risks of non-core emu states and oil producing countries are discussed through the prism of VaR metrics.

The proposed approach offers a clue for improving risk management in regards to banking books containing government bonds. It could be applied to access the riskiness of investment portfolios containing the wider spectrum of assets beyond the sovereign debt. The approach represents a useful tool for investigating interest rate and credit risk interrelation.

The proposed enhancement of the traditional historical VaR is twofold: usage of derivative instruments’ quotes and simultaneous consideration of the interest rate and credit risk factors to construct the hypothetical liquidity-free bond yield, which allows to distil liquidity premium.

This paper aims to illustrate, within the context of a well-known linear diversification model, that risk management as exerted by banks and regulators ultimately depends on how risk is assessed and conceptualized. The two risk metrics used are the probability of bank failure and value at risk (VaR). The paper also extends the results of the model by incorporating an explicit analysis of correlation of the bank's portfolios.

The paper is based on a well-known model of linear diversification of two banking institutions developed by Wagner (2010) in the Journal of Financial Intermediation. The authors added considerations that were unexplored by Wagner and derived the corresponding logical and practical implications.

The authors found that depending on which of the two risk metrics being used, the way diversification is perceived and risk is managed may differ. This situation may very well end-up generating different incentives for banks and regulators. The authors suggest a general rationale for considering how to think about the apparent dilemma and the challenges faced by regulators. The authors also offer an explicit analysis of correlation for the bank's portfolios.

The results are dependent on the particular aspects of the model, so the research results may lack generality in other contexts.

Despite the limitations already mentioned, the paper illustrates some relevant points within the open debate about risk measurement and diversification.

This paper contributes to the open discussion of diversification, risk perception and systemic crisis.

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.

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.

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.

Using a convenient tail-risk measure of performance, this paper aims to explore the extent to which incorporating higher statistical moments such as an assets skewness and kurtosis, provides further insight into the potential benefits of asset-class diversification within the realm of Islamic finance.

The authors use Engle’s (2002) DCC-GARCH model to study the dynamic conditional correlations between asset classes. Furthermore, the authors use the modified value-at-risk (Favre and Galeano, 2002), which incorporates higher statistical moments, to measure the performance of portfolios during both crisis and bullish regimes.

The most important finding relates to the estimation of portfolio tail-risk. In particular, the authors find that using a standard two-moment value-at-risk (VaR) measure, which assumes normally distributed returns, rather than a four-moment VaR, which incorporates an asset skewness and kurtosis, can lead to a substantial underestimation of portfolio risk during the most extreme market conditions.

This paper contributes to the extremely limited research considering higher-moments within the realm of Islamic portfolio-management. The results suggest that Islamic portfolio managers should remain cognisant of the skewness and kurtosis parameters of their assets. Ignoring higher-moments could induce misleading inferences and would, therefore, constitute imprudent risk-management.