Extreme Value Theory

Haan, Leo de; Ferreira, Ana

doi:10.1007/0-387-34471-3

Cited by 1,904 publications

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“…Note thatC is the joint cdf of the vector (1−U, 1−V ). Tail copulas and variants thereof characterize extremal dependence of the vector (X, Y ), see de Haan and Ferreira (2006). One of the variants of Λ U is given by the stable tail dependence function l(x, y) = x + y − Λ U (x, y).…”

Section: Introductionmentioning

confidence: 99%

A note on nonparametric estimation of bivariate tail dependence

Bücher

2014

Statistics &Amp; Risk Modeling

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Nonparametric estimation of tail dependence can be based on a standardization of the marginals if their cumulative distribution functions are known. In this paper it is shown to be asymptotically more efficient if the additional knowledge of the marginals is ignored and estimators are based on ranks. The discrepancy between the two estimators is shown to be substantial for the popular Clayton model. A brief simulation study indicates that the asymptotic conclusions transfer to finite samples.

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Section: Introductionmentioning

confidence: 99%

A note on nonparametric estimation of bivariate tail dependence

Bücher

2014

Statistics &Amp; Risk Modeling

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“…In other words, the two-dimensional EVT condition models the marginals through one-dimensional EVT and it models the tail dependence through the L(x; y) function. As noted by de Haan and Ferreira (2006), 1 L(1; 1) 2. A value for L(1; 1) equal to 1 indicates complete tail dependence.…”

Section: Multivariate Evt: Tail Dependencementioning

confidence: 72%

“…As an example of a two-dimensional case, assume a system of two banks, with loss returns X and Y . Following de Haan and Ferreira (2006), the two-dimensional EVT assumes that there exists a G(x; y) such that…”

Section: Multivariate Evt: Tail Dependencementioning

confidence: 99%

Risk-Factor Portfolios and Financial Stability

Garita

2010

SSRN Journal

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This paper de…nes a risk-stability index (RSI) that takes into account the extreme dependence structure and the conditional probability of joint failure (CPJF) among risk factors in a portfolio. In combination, both the RSI and CPJF provide a valuable tool for analyzing risk from complementary perspectives; thereby allowing the measurement of (i) common distress of risk factors in a portfolio, (ii) distress between speci…c risk factors, and (iii) distress to a portfolio related to a speci…c risk factor. With an application to a …nancial system comprised of 18 banks from around the world, the results herein show that …nancial stability must be viewed as a continuum, since risk varies from period to period. The risk-stability index indicates that U.S. banks tend to cause the most stress to the global …nancial system (as de…ned herein), followed by Asian and European banks. The results also show that Asian banks seem to experience the most persistence of distress, followed by U.S. and European banks. The panel VAR results show that monetary policy should "lean against the wind", since it has a signi…cant e¤ect in reducing the (potential) instability of a …nancial system. JEL Classi…cation: C10, E44, F15, F36, F37

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“…If the model GARCH(1,1) satisfies the parameters sum   11 1, then the model describes the process of unlimited growth of conditional variability. Such a model is known as integrated GARCH model -IGARCH(1,1).…”

Section: Garch Modelmentioning

confidence: 99%

A Comparative Analysis of Value at Risk Measurement on Emerging Stock Markets: Case of Montenegro

Cerović

Lipovina-Božović

Vujošević

2015

Business Systems Research Journal

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Background: The concept of value at risk gives estimation of the maximum loss of financial position at a given time for a given probability. The motivation for this analysis lies in the desire to devote necessary attention to risks in Montenegro, and to approach to quantifying and managing risk more thoroughly. Objectives: This paper considers adequacy of the most recent approaches for quantifying market risk, especially of methods that are in the basis of extreme value theory, in Montenegrin emerging market before and during the global financial crisis. In particular, the purpose of the paper is to investigate whether extreme value theory outperforms econometric and quantile evaluation of VaR in emerging stock markets such as Montenegrin market. Methods/Approach: Daily return of Montenegrin stock market index MONEX20 is analyzed for the period January, -February, 2014. Value at Risk results based on GARCH models, quantile estimation and extreme value theory are compared. Results: Results of the empirical analysis show that the assessments of Value at Risk based on extreme value theory outperform econometric and quantile evaluations. Conclusions: It is obvious that econometric evaluations (ARMA(2,0)-GARCH(1,1) and RiskMetrics) proved to be on the lower bound of possible Value at Risk movements. Risk estimation on emerging markets can be focused on methodology using extreme value theory that is more sophisticated as it has been proven to be the most cautious model when dealing with turbulent times and financial turmoil.

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Extreme Value Theory

Cited by 1,904 publications

References 0 publications

A note on nonparametric estimation of bivariate tail dependence

A note on nonparametric estimation of bivariate tail dependence

Risk-Factor Portfolios and Financial Stability

A Comparative Analysis of Value at Risk Measurement on Emerging Stock Markets: Case of Montenegro

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