The difference between market risk and potential market risk is emphasized and a measure of the latter risk is proposed. Specifically, it is argued that the spectrum of smooth Lyapunov exponents can be utilized in what we call (λ, σ)-analysis, which is a method to monitor the aforementioned risk measures. The reason is that these exponents focus on the stability properties (λ) of the stochastic...

This paper established the ARMA-GJR-AL model of dynamic risk VaR and CVaR measurement. Considering from aspects of the correlation and volatility and residual distribution characteristics, studying the dynamic risk measures of VaR and CVaR based on ARMA-GJR-AL model. Through empirical research, Risk prediction and accuracy of inspection are given of the Shanghai stock market and the New York st...

We propose a new estimator for expected shortfall that uses asymptotic expansions to account for the asymmetry and heavy tails in financial returns. We provide all the necessary formulas for decomposing estimators of value-at-risk and expected shortfall based on asymptotic expansions and show that this new methodology is very useful for analyzing and predicting the risk properties of portfolios...

Deregulation in the power industry drives competition. It also increases the risk of doing business. Therefore it is important to manage and assess the risk. Value at risk (VaR) analysis has been used in financial institutions to evaluate portfolios of assets for some time, but the application of the approach in the power industry has not been established. The VaR of serving customer demand usi...

Everyone who measures the market risk using the Value at Risk (VaR) approach should test if the assumed model is correct. This procedure is called backtesting. There are many different tests available, but usually risk managers are not concerned about their power. The aim of this paper is to analyze some chosen backtesting methods focusing on the problem of power of the tests and limited data s...

Risks faced by traders from price movements are sometimes magnified by the actions of other traders. Riskmanagement systems which neglect this feature may give a seriously misleading picture of the true risks. The hazards arising from this potential blindspot are at their most dangerous when the prevailing conventional wisdom lulls traders into a false sense of security on the attractiveness of...

Mainly due to new capital adequacy standards for banking and insurance, an increased interest exists in the aggregation properties of risk measures like Value-atRisk (VaR). We show how VaR can change from subto superadditivity depending on the properties of the underlying model. Mainly, the switch from a finite to an infinite mean model gives a completely different asymptotic behaviour. Our mai...

An important question for corporate finance officers is whether risk management systems, such as Value at Risk (VaR), currently are producing accurate results. In contrast to previous research on assessing the accuracy of risk systems or VaR, which has focused on backtesting a large sample of historical observations, we provide tools for real-time assessment, using a time window that varies ada...

The theory of copulas provides a useful tool for modeling dependence in risk management. In insurance and finance, as well as in other applications, dependence of extreme events is particularly important, hence there is a need for the detailed study of the tail behaviour of the multivariate copulas. In this paper we investigate the class of copulas having homogeneous lower tails. We show that h...

A typical shortcoming of most current credit portfolio models is the lack of a stochastic modeling of risk factors, such as interest rates or credit spreads, during the revaluation process at the risk horizon. Within the simple credit risk model underlying the Internal Ratings-based approach of Basel II with incorporated correlated interest rate risk the effect which results from neglecting the...