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Extremal Quantiles and Value-at-Risk
SSRN Electronic Journal, 2006This article looks at the theory and empirics of extremal quantiles in economics, in particular value-at-risk. The theory of extremes has gone through remarkable developments and produced valuable empirical findings in the last 20 years. In the discussion, we put a particular focus on conditional extremal quantile models and methods, which have ...
Victor Chernozhukov, Songzi Du
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Canadian Mathematical Bulletin, 1998
AbstractThe function Δ(x, N) as defined in the title is closely associated via Δ(N) = supx |Δ(x, N)| to several problems in the upper bound sieve. It is also known via a classical theorem of Franel that certain conjectured bounds involving averages of Δ(x, N) are equivalent to the Riemann Hypothesis.
null P. Codecà, M. Nair
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AbstractThe function Δ(x, N) as defined in the title is closely associated via Δ(N) = supx |Δ(x, N)| to several problems in the upper bound sieve. It is also known via a classical theorem of Franel that certain conjectured bounds involving averages of Δ(x, N) are equivalent to the Riemann Hypothesis.
null P. Codecà, M. Nair
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Siberian Mathematical Journal, 2004
Summary: It is shown that every finite-dimensional skew field whose center is an extremal valued field is defect free. We construct an example of an algebraically complete valued field such that a finite-dimensional skew field over it has a non-trivial defect, that is, there exist algebraically complete valued fields that are not extremal.
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Summary: It is shown that every finite-dimensional skew field whose center is an extremal valued field is defect free. We construct an example of an algebraically complete valued field such that a finite-dimensional skew field over it has a non-trivial defect, that is, there exist algebraically complete valued fields that are not extremal.
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Extreme Returns From Extreme Value Stocks
The Journal of Investing, 2005Investigations into value-based ‘anomalies’ such as the P/E effect typically sort shares into quintiles, or at most deciles. These are blunt instruments. We test whether most of the extra value in the lower end of the P/E spectrum is to be found in the very lowest P/E shares, and whether the worst investments reside in the few shares with the highest P/
Anderson, K., Brooks, Chris
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Extreme market risk and extreme value theory
Mathematics and Computers in Simulation, 2013zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Abhay K. Singh +2 more
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The Extreme Value Evolving Predictor
IEEE Transactions on Fuzzy Systems, 2022This paper introduces a new evolving fuzzy-rule-based algorithm for online data streams, named Extreme Value evolving Predictor (EVeP). It offers a statistically well-founded approach to defining the evolving fuzzy granules that form the antecedent and the consequent parts of the rules. The evolving fuzzy granules correspond to radial inclusion Weibull
Amanda O. C. Ayres +1 more
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Extreme value analysis in biometrics
Biometrical Journal, 2009AbstractWe review some approaches of extreme value analysis in the context of biometrical applications. The classical extreme value analysis is based on iid random variables. Two different general methods are applied, which will be discussed together with biometrical examples.
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How to probe for an extreme value
ACM Transactions on Algorithms, 2010In several systems applications, parameters such as load are known only with some associated uncertainty, which is specified, or modeled, as a distribution over values. The performance of the system optimization and monitoring schemes can be improved by spending resources such as time or bandwidth in observing or
Ashish Goel +2 more
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Value at Risk and Extreme Values
IFAC Proceedings Volumes, 1998Abstract this paper gives a general exposition of the subject of Value at Risk (VaR), which is now considered as a standard measure of market risks. It is defined as the maximal loss of the portfolio for a given probability over a given period. This measure is sensitive to the tails of the distribution of returns; extreme value theory is used here to
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Testing Extreme Value Conditions
Extremes, 2002A modification of the Cramér-von Mises statistics for testing the tail behaviour of i.i.d. sample CDF \(F\) is considered. Its version for nonnegative tail index \(\gamma\) is of the form \[ T_{k,n}=\int \left( {1\over \hat\gamma} (\log X_{n-[kt],n}-\log X_{n-k,n})+\log t \right)^2 t^2\, dt, \] where \(X_{i,n}\) is the \(i\)th order statistics, \(\hat ...
Dietrich, D +2 more
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