It is common wisdom that the 9/11 terrorist attacks boosted political and financial uncertainty and resulted in severe stock market meltdowns in the months after the attacks. Taking a sectoral focus of the market for US common stock, we apply statistical extreme value analysis (EVT) to assess whether downside risk measures like Value-at-Risk (VaR) and extremal sector linkages were significantly...

We propose a method for estimating VaR and related risk measures describing the tail of the conditional distribution of a heteroscedastic nancial return series. Our approach combines quasi maximum likelihood tting of GARCH models to estimate the current volatility and extreme value theory (EVT) for estimating the tail of the innovation distribution of the GARCH model. We use our method to estim...

We propose a new method for estimating the extreme quantiles for a function of several dependent random variables. In contrast to the conventional approach based on extreme value theory, we do not impose the condition that the tail of the underlying distribution admits an approximate parametric form, and, furthermore, our estimation makes use of the full observed data. The proposed method is se...

How to effectively evaluate price of volatility risk is the basis of risk management in electricity market. Electricity price connotes a grey system, due to uncertainty and incomplete information for partial external or inner parameters. A two-stage model for estimating value-at-risk based on grey system and extreme value theory is proposed. Firstly, in order to capture the dependencies, season...

The Persian Gulf is an important economic and geo-political region. Owing to its oil and gas resources, it is one of the busiest waterways in the world. There are many operating oil wells in the northern part of the Persian Gulf . As a result, the risk of contaminant dispersion is high. The deliberate discharge of 6.3 million barrels of crude oil during the 1991 war against Kuwait in this regio...

Abstract The extremal index θ , a measure of the degree of local dependence in the extremes of a stationary process, plays an important role in extreme value analyses. We estimate θ semiparametrically, using the relationship between the distribution of block maxima and the marginal distribution of a process to define a semiparametric model. We show that these semiparametric estimators are simpl...