It Pays to Violate: How Effective are the Basel Accord Penalties?

The internal models amendment to the Basel Accord allows banks to use internal models to forecast Value-at-Risk (VaR) thresholds, which are used to calculate the required capital that banks must hold in reserve as a protection against negative changes in the value of their trading portfolios. As capital reserves lead to an opportunity cost to banks, it is likely that banks could be tempted to use models that underpredict risk, and hence lead to low capital charges. In order to avoid this problem the Basel Accord introduced a backtesting procedure, whereby banks using models that led to excessive violations are penalised through higher capital charges. This paper investigates the performance of five popular volatility models that can be used to forecast VaR thresholds under a variety of distributional assumptions. The results suggest that, within the current constraints and the penalty structure of the Basel Accord, the lowest capital charges arise when using models that lead to excessive violations, thereby suggesting the current penalty structure is not severe enough to control risk management. In addition, this paper suggests an alternative penalty structure that is more effective at aligning the interests of banks and regulators.GARCH;risk management;forecasting;Value-at-Risk (VaR);Basel accord penalties;simulations;violations

Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range

Value-at-Risk (VaR) is commonly used for financial risk measurement. It has recently become even more important, especially during the 2008-09 global financial crisis. We propose some novel nonlinear threshold conditional autoregressive VaR (CAViaR) models that incorporate intra-day price ranges. Model estimation and inference are performed using the Bayesian approach via the link with the Skewed-Laplace distribution. We examine how a range of risk models perform during the 2008-09 financial crisis, and evaluate how the crisis affects the performance of risk models via forecasting VaR. Empirical analysis is conducted on five Asia-Pacific Economic Cooperation stock market indices as well as two exchange rate series. We examine violation rates, back-testing criteria, market risk charges and quantile loss function values to measure and assess the forecasting performance of a variety of risk models. The proposed threshold CAViaR model, incorporating range information, is shown to forecast VaR more efficiently than other models, across the series considered, which should be useful for financial practitioners.Value-at-Risk; CAViaR model; Skewed-Laplace distribution; intra-day range; backtesting; Markov chain Monte Carlo

Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range

Value-at-Risk (VaR) is commonly used for financial risk measurement. It has recently become even more important, especially during the 2008-09 global financial crisis. We pro- pose some novel nonlinear threshold conditional autoregressive VaR (CAViaR) models that incorporate intra-day price ranges. Model estimation and inference are performed using the Bayesian approach via the link with the Skewed-Laplace distribution. We examine how a range of risk models perform during the 2008-09 financial crisis, and evaluate how the crisis aects the performance of risk models via forecasting VaR. Empirical analysis is conducted on five Asia-Pacific Economic Cooperation stock market indices as well as two exchange rate series. We examine violation rates, back-testing criteria, market risk charges and quantile loss function values to measure and assess the forecasting performance of a variety of risk models. The proposed threshold CAViaR model, incorporating range information, is shown to forecast VaR more eficiently than other models, across the series considered, which should be useful for financial practitioners.Value-at-Risk; CAViaR model; Skewed-Laplace distribution; intra-day range; backtesting, Markov chain Monte Carlo.

An econometric analysis of SARS and Avian flu on international tourist arrivals to Asia

This paper compares the impacts of SARS and human deaths arising from Avian Flu on international tourist arrivals to Asia. The effects of SARS and human deaths from Avian Flu will be compared directly according to human deaths. The nature of the short run and long run relationship is examined empirically by estimating a static line fixed effect model and a difference transformation dynamic model, respectively. Empirical results from the static fixed effect and difference transformation dynamic models are consistent, and indicate that both the short run and long run SARS effect have a more significant impact on international tourist arrivals than does Avian Flu. In addition, the effects of deaths arising from both SARS and Avian Flu suggest that SARS is more important to international tourist arrivals than is Avian Flu. Thus, while Avian Flu is here to stay, its effect is currently not as significant as that of SARS.Avian flu;international tourism;SARS;dynamic panel data model;static fixed effects model

Risk register and risk intelligence: the challenge of operational risks in the energy sector

This paper presents the needs and the challenges encountered in developing a company-wide risk register in the energy sector. The study presented comes from an electricity generation company and it was useful to indicate areas where the concept of risk registers could be extended to make better use of existing data and to support continuous improvement of risk management. Six key areas are discussed 1) aggregation of risks across the business, 2) supporting controls over mitigation measures, 3) improved estimation of event likelihood, 4) integrating with critical asset registers, 5) improving risk communication, and 6) linking with day-to-day operational practice. The paper concludes with a framework for placing risk registers at the heart of Process Safety

Cost benefit evaluation of maintenance options for aging equipment using monetised risk values: A practical application

With constant pressure to reduce maintenance costs as well as short-term budget constraints in a changing market environment, asset managers are compelled to continue operating aging assets while deferring maintenance and investment. The scope of the paper is to get an overview of the methods used to evaluate risks and opportunities for deferred maintenance interventions on aging equipment, and underline the importance to include monetised risk considerations and timeline considerations, to evaluate different scenarios connected with the possible options. Monetised risk values offer the opportunity to support risk-based decision-making using the data collected from the field. The paper presents examples of two different methods and their practical applicability in two case studies in the energy sector for a company managing power stations. The use of the existing and the new proposed solutions are discussed on the basis of their applicability to the concrete examples

Cost Benefit Evaluation of Maintenance Options for Aging Equipment Using Monetised Risk Values: A practical application

With constant pressure to reduce maintenance costs as well as short-term budget constraints in a changing market environment, asset managers are compelled to continue operating aging assets while deferring maintenance and investment. The scope of the paper is to get an overview of the methods used to evaluate risks and opportunities for deferred maintenance interventions on aging equipment, and underline the importance to include monetised risk considerations and timeline considerations, to evaluate different scenarios connected with the possible options. Monetised risk values offer the opportunity to support risk-based decision-making using the data collected from the field. The paper presents examples of two different methods and their practical applicability in two case studies in the energy sector for a company managing power stations. The use of the existing and the new proposed solutions are discussed on the basis of their applicability to the concrete examples