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Risk capital is an important input for management functions. Capital structure decisions, capital budgeting, and ex post performance measurement require different measures of risk capital. While it has become common to estimate risk capital using VaR models, it is not clear that VaR‐based capital estimates are optimal for applications to management functions (e.g. risk management, capital budgeting, performance measurement, or regulation). This article considers three typical problems that require an estimate of credit risk capital: an optimal equity capital allocation; an optimal capital allocation for capital budgeting decisions; and an optimal capital allocation to remove moral hazard incentives from a compensation contract based on ex post performance. The optimal credit risk capital allocation is different for each problem and is never consistent with a credit VaR estimate of unexpected loss. The results demonstrate that the optimal risk capital allocation depends on the objective.

The pre‐commitment approach to bank capital regulation proposes that banks self‐select capital reserve requirements, facing penalties ex post for incurring losses in excess of reserves, hence providing incentives for high‐ risk banks to choose higher capital requirements. In order to assess the validity of the pre‐commitment approach, this article analyzes its comparative statics within the context of a standard European option written against the bank's capital base. The author finds that this approach works when it is not needed (when banks possess unlimited capital and hence cannot fail), but not when it is.

Spectacular bankruptcies of the Orange County Investment Pool in December 1994 and Barings Bank in February 1995 mounted a pressure on the U.S. Financial Accounting Standards Board (FASB) to issue Statement No. 133, Accounting for Derivatives Instruments and Hedging Activities (FAS 133). Although measuring derivatives at fair value is a major improvement in accounting for derivatives, such type of accounting falls short of quantifying and reporting the risk of losses associated with derivative instruments. The purpose of this paper is to suggest an alternative approach to market valuation by integrating quantitative market risk estimation into the valuation method. The paper will use the Barings Bank experience to demonstrate how FAS no. 133 disclosure falls short of disclosing the magnitude of the market risk held by the bank at the end of 1994. It will also demonstrate how using a risk‐impacted value would have improved the disclosure of how much the bank stood to lose from their open positions.

This paper provides a comprehensive overview of the gradual evolution of the supervisory policy adopted by the Basel Committee for the regulatory treatment of asset securitisation. The pathology of the new “securitisation framework” is carefully highlighted to facilitate a general understanding of what constitutes the current state of computing adequate capital requirements for securitised credit exposures. Although a simplified sensitivity analysis of the varying levels of capital charges depending on the security design of asset securitisation transactions is incorporated, the author does not engage in a profound analysis of the benefits and drawbacks implicated in the new securitisation framework.

Directors play a hard-to-quantify but critical role in the success of corporations. Outside directors supplement the firm-specific knowledge of inside directors by providing expertise and monitoring. Prior research finds that outside directors who are commercial bankers can be both beneficial and costly to large, non-financial corporations. Smaller, bank-dependent corporations should benefit more than large firms from the services banker directors provide, but may also be more prone to the costs they can impose. The purpose of this paper is to investigate the influence of bank dependency on appointments of banker directors.

The author estimates models relating the probability of a first-time banker-director appointment to proxies of bank dependency on data for a matched sample of firms with and without banker directors drawn from a size-representative sample of Compustat firms.

Bank-dependent firms are less likely to appoint bankers as directors than bank-independent firms. Bank-dependent firms are also less likely to appoint bankers whose employers are firms’ creditors (i.e. affiliated bankers). Bank-dependent and bank-independent firms are indistinguishable in their probabilities of appointing unaffiliated bankers as directors.

Bank-dependent firms with unexploited growth opportunities appear unable to ameliorate their financial constraints by having banker directors. Appointing retired bankers to boards may give firms the benefits of banker directors without the costs.

This paper is the first to: document the prevalence of banker directors at smaller corporations; present econometric evidence on banker-director appointments at firms ranging from small to large; and identify bank dependency as a factor limiting appointments of affiliated banker directors.

Amid increased size and complexity of the banking industry, operational risk has a greater potential to occur in more harmful ways than many other sources of risk. This paper seeks to provide a succinct overview of the current regulatory framework of operational risk under the New Basel Accord with a view to inform a critical debate about the influence of data collection, loss reporting, and model specification on the consistency of risk‐sensitive capital rules.

The paper's approach is to investigate the regulatory implications of varying characteristics of operational risk and different methods to identify operational risk exposure.

The findings reveal that effective operational risk measurement hinges on how the reporting of operational risk losses and the model sensitivity of quantitative methods affect the generation of consistent risk estimates.

The presented findings offer tractable recommendations for a more coherent and consistent regulation of operational risk.

This case study considers what marketing action the producers of halloumi in the Republic of Cyprus ought to take to secure their domestic and export markets. Halloumi is promoted as the national branded product of Cyprus. Its manufacture in Cyprus is mainly undertaken by large dairy producers, but a substantial part of production still remains with small commercial enterprises and farms. Consumption in the Republic is mediated through tourism that acts both to increase consumption and as a conduit to create export demand. The current structure of support for, and supply of milk for the cheese in general, and halloumi in particular, will change when Cyprus enters the EU in 2004.

This study aims to implement a novel approach of using the Realized generalized autoregressive conditional heteroskedasticity (GARCH) model within the conditional extreme value theory (EVT) framework to generate quantile forecasts. The Realized GARCH-EVT models are estimated with different realized volatility measures. The forecasting ability of the Realized GARCH-EVT models is compared with that of the standard GARCH-EVT models.

One-step-ahead forecasts of Value-at-Risk (VaR) and expected shortfall (ES) for five European stock indices, using different two-stage GARCH-EVT models, are generated. The forecasting ability of the standard GARCH-EVT model and the asymmetric exponential GARCH (EGARCH)-EVT model is compared with that of the Realized GARCH-EVT model. Additionally, five realized volatility measures are used to test whether the choice of realized volatility measure affects the forecasting performance of the Realized GARCH-EVT model.

In terms of the out-of-sample comparisons, the Realized GARCH-EVT models generally outperform the standard GARCH-EVT and EGARCH-EVT models. However, the choice of the realized estimator does not affect the forecasting ability of the Realized GARCH-EVT model.

It is one of the earliest implementations of the two-stage Realized GARCH-EVT model for generating quantile forecasts. To the best of the authors’ knowledge, this is the first study that compares the performance of different realized estimators within Realized GARCH-EVT framework. In the context of high-frequency data-based forecasting studies, a sample period of around 11 years is reasonably large. More importantly, the data set has a cross-sectional dimension with multiple European stock indices, whereas most of the earlier studies are based on the US market.

This paper investigates the influence of the ongoing crisis of Russia's incursion on Ukraine on the risk dynamics of energy futures contracts with high-frequency data on four different futures contracts using risk metrics of value at risk (VaR) and conditional value at risk (CVaR) for the USA market.

The author used different generalised autoregressive conditional heteroscedasticity - Extreme Value Theory (GARCH)-EVT models and compared the performance of each of the competing models. Backtesting evidence shows that VaR and CVaR combined with GARCH-EVT better estimate risk.

The study results show that combined risk metrics are efficient and adaptive to estimating the risk dynamics and backtesting of the models, revealing that the autoregressive moving average (ARMA) (1,1)-asymmetric power autoregressive conditional heteroscedasticity (APARCH) model performs relatively better than other models.

The paper has practical implications for different market participants. From the risk manager's and day traders' angles, the market participants can estimate the risk exposure in the energy futures contract and take positions accordingly. The results are important for oil-importing countries due to the developing supply crisis and price escalation, which can brew inflation in the economy.

To the best of the author's knowledge, the paper is the first to throw light on the risk angle of energy futures contracts during the ongoing crisis of the Russia–Ukraine war.

The purpose of this paper is to examine the impact of bank branch location on the likelihood of bank failure during the most recent financial crisis.

This paper estimates the probit regression to identify the causes of bank failures and attempts to determine the role of branch location in bank performance.

Using data from failed and surviving banks in Georgia and Florida, this paper finds that diversifying the balance sheet and operating in more competitive markets reduced failure rates, but branching intensity, measured by number of branches and distance of branches from the home office did not significantly reduce the probability of failure. This suggests that, at least in today ' s market, it is not important to bank stability to have a branching network a significant distance from the home office.

This paper carefully considers the role of branch location in the likelihood of bank failure during financial distress. As such, it contributes to the historical policy debate regarding regulation prohibiting or minimizing banks ' ability to branch. It also contributes to our understanding of how banks structure their branching networks in the contemporary banking environment.