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{{Redirect-synonym|TVAR|[[Time variance]]}} | |||
'''Tail value at risk''' ('''TVaR'''), also known as '''tail conditional expectation''' ('''TCE''') or '''conditional tail expectation''' ('''CTE'''), is a [[risk measure]] associated with the more general [[value at risk]]. It quantifies the expected value of the loss given that an event outside a given probability level has occurred. | |||
==Background== | |||
There are a number of related, but subtly different, formulations for TVaR in the literature. A common case in literature is to define TVaR and [[average value at risk]] as the same measure.<ref name=Bar/> Under some formulations, it is only equivalent to [[expected shortfall]] when the underlying [[cumulative distribution function|distribution function]] is [[continuous function|continuous]] at <math>\operatorname{VaR}_{\alpha}(X)</math>, the value at risk of level <math>\alpha</math>.<ref name=web1/> Under some other settings, TVaR is the conditional expectation of loss above a given value, whereas the expected shortfall is the product of this value with the probability of it occurring.<ref name = "Sweeting"/> The former definition may not be a [[coherent risk measure]] in general, however it is coherent if the underlying distribution is continuous.<ref name=Acerbi/> The latter definition is a coherent risk measure.<ref name = "Sweeting" /> TVaR accounts for the severity of the failure, not only the chance of failure. The TVaR is a measure of the [[Expected value|expectation]] only in the tail of the distribution. | |||
==Mathematical definition== | |||
Given a [[random variable]] <math>X</math> which is the payoff of a portfolio at some future time and given a parameter <math>0 < \alpha < 1</math> then the tail value at risk is defined by<ref name=Artzner/><ref name=Landsman/><ref name=Landsman2/><ref name=Valdez/> | |||
: <math>\operatorname{TVaR}_{\alpha}(X) = \operatorname{E} [-X|X \leq -\operatorname{VaR}_{\alpha}(X)] = \operatorname{E} [-X | X \leq x^{\alpha}] ,</math> | |||
where <math>x^{\alpha}</math> is the upper <math>\alpha</math>-[[quantile]] given by <math>x^{\alpha} = \inf\{x \in \mathbb{R}: \Pr(X \leq x) > \alpha\}</math>. Typically the payoff random variable <math>X</math> is in some [[Lp space|L<sup>p</sup>-space]] where <math>p \geq 1</math> to guarantee the existence of the expectation. | |||
==References== | |||
{{Reflist|refs= | |||
<ref name=Bar>{{cite journal|last=Bargès|coauthors=Cossette, Marceau|title=TVaR-based capital allocation with copulas|journal=Insurance: Mathematics and Economics|year=2009|volume=45|pages=348–361|url=http://www.sciencedirect.com/science/article/pii/S0167668709000912|accessdate=20 July 2012|doi=10.1016/j.insmatheco.2009.08.002}}</ref> | |||
<ref name=web1>{{cite web|url=https://statistik.ets.kit.edu/download/doc_secure1/7_StochModels.pdf|title=Average Value at Risk|format=pdf|accessdate=February 2, 2011}}</ref> | |||
<ref name = "Sweeting">{{cite book | |||
| last = Sweeting | |||
| first = Paul | |||
| title = Financial Enterprise Risk Management | |||
| series = International Series on Actuarial Science | |||
| year = 2011 | |||
| publisher = [[Cambridge University Press]] | |||
| isbn = 978-0-521-11164-5 | |||
| lccn = 2011025050 | |||
| pages = 397–401 | |||
| chapter = 15.4 Risk Measures | |||
}}</ref> | |||
<ref name=Acerbi>{{cite journal|first1=Carlo|last1=Acerbi|first2=Dirk|last2= Tasche|title=On the coherence of Expected Shortfall|year=2002|journal=Journal of Banking and Finance|volume=26|number=7|pages=1487–1503|url=http://arxiv.org/pdf/cond-mat/0104295%22%20/|format=pdf|accessdate=April 25, 2012}}</ref> | |||
<ref name=Artzner>{{cite journal|last=Artzner|first=Philippe|last2=Delbaen|first2=Freddy|last3=Eber|first3=Jean-Marc|last4=Heath|first4=David|year=1999|title=Coherent Measures of Risk|journal=Mathematical Finance|volume=9|issue=3|pages=203–228|url=http://www.math.ethz.ch/~delbaen/ftp/preprints/CoherentMF.pdf|format=pdf|accessdate=February 3, 2011}}</ref> | |||
<ref name=Landsman>{{cite journal|first1=Zinoviy|last1=Landsman|first2=Emiliano|last2=Valdez|title=Tail Conditional Expectations for Exponential Dispersion Models|date=February 2004|url=http://www.actuaries.org/ASTIN/Colloquia/Bergen/Landsman_Valdez.pdf|format=pdf|accessdate=February 3, 2011}}</ref> | |||
<ref name=Landsman2>{{cite journal|first1=Zinoviy|last1=Landsman|first2=Udi|last2=Makov|first3=Tomer|last3=Shushi|title=Tail Conditional Expectations for Generalized Skew - Elliptical distributions |date=July 2013|url=http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2298265|format=pdf|accessdate=June 30, 2013}}</ref> | |||
<ref name=Valdez>{{cite journal|first=Emiliano|last=Valdez|title=The Iterated Tail Conditional Expectation for the Log-Elliptical Loss Process|date=May 2004|url=http://www.asb.unsw.edu.au/schools/actuarialstudies/Documents/E.A.%20Valdez%20-%20The%20Iterated%20Tail%20Conditional%20Expectation%20for%20the%20Log-Elliptical%20Loss%20Process.pdf|format=pdf|accessdate=February 3, 2010}}</ref> | |||
}} | |||
{{DEFAULTSORT:Tail Value At Risk}} | |||
[[Category:Actuarial science]] | |||
[[Category:Mathematical finance]] | |||
[[Category:Financial risk]] | |||
{{Econometrics-stub}} | |||
{{Finance-stub}} |
Revision as of 15:50, 13 May 2013
Tail value at risk (TVaR), also known as tail conditional expectation (TCE) or conditional tail expectation (CTE), is a risk measure associated with the more general value at risk. It quantifies the expected value of the loss given that an event outside a given probability level has occurred.
Background
There are a number of related, but subtly different, formulations for TVaR in the literature. A common case in literature is to define TVaR and average value at risk as the same measure.[1] Under some formulations, it is only equivalent to expected shortfall when the underlying distribution function is continuous at , the value at risk of level .[2] Under some other settings, TVaR is the conditional expectation of loss above a given value, whereas the expected shortfall is the product of this value with the probability of it occurring.[3] The former definition may not be a coherent risk measure in general, however it is coherent if the underlying distribution is continuous.[4] The latter definition is a coherent risk measure.[3] TVaR accounts for the severity of the failure, not only the chance of failure. The TVaR is a measure of the expectation only in the tail of the distribution.
Mathematical definition
Given a random variable which is the payoff of a portfolio at some future time and given a parameter then the tail value at risk is defined by[5][6][7][8]
where is the upper -quantile given by . Typically the payoff random variable is in some Lp-space where to guarantee the existence of the expectation.
References
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