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Resources Policy, 2023
In this study, we consider as a predictor of gold return predictability, an alternative measure of systematic risk using the tail risk obtained from the four variants (Adaptive, Symmetric absolute value, Asymmetric slope and Indirect GARCH) of the Conditional Autoregressive Value at Risk (CAViaR) of Engle and Manganelli (2004).
Salisu, A. A. +3 more
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In this study, we consider as a predictor of gold return predictability, an alternative measure of systematic risk using the tail risk obtained from the four variants (Adaptive, Symmetric absolute value, Asymmetric slope and Indirect GARCH) of the Conditional Autoregressive Value at Risk (CAViaR) of Engle and Manganelli (2004).
Salisu, A. A. +3 more
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The Journal of Investing, 2014
For purposes of risk management, typically used returns distributions are asymptotic to zero, the most popular being the Gaussian and Power Functions. Yet, this asymptotic property of tail risk is relatively unexploited in thinking about the most vexing of managerial behaviors, the tendency to ignore the most threatening hazards facing the organization.
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For purposes of risk management, typically used returns distributions are asymptotic to zero, the most popular being the Gaussian and Power Functions. Yet, this asymptotic property of tail risk is relatively unexploited in thinking about the most vexing of managerial behaviors, the tendency to ignore the most threatening hazards facing the organization.
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Tail risk in energy portfolios
Energy Economics, 2013This article analyzes the tail behavior of energy price risk using a multivariate approach, in which the exposure to energy markets is given by a portfolio of oil, gas, coal, and electricity. To accommodate various dependence and tail decay patterns, this study models energy returns using different generalized hyperbolic conditional distributions and ...
Carlos González-Pedraz +2 more
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2020
La plupart des modèles de prévisions macroéconomiques ne tiennent pas compte du risque de crise, soit le risque d’une baisse marquée et soudaine du produit intérieur brut (PIB). Pourtant, les décideurs se préoccupent de ce type de risque extrême étant donné les coûts socioéconomiques substantiels qui en découleraient.
Duprey, Thibaut, Ueberfeldt, Alexander
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La plupart des modèles de prévisions macroéconomiques ne tiennent pas compte du risque de crise, soit le risque d’une baisse marquée et soudaine du produit intérieur brut (PIB). Pourtant, les décideurs se préoccupent de ce type de risque extrême étant donné les coûts socioéconomiques substantiels qui en découleraient.
Duprey, Thibaut, Ueberfeldt, Alexander
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SSRN Electronic Journal, 2021
In this study we comprehensively investigate the usefulness of the tail risk measures proposed in the literature, evaluating the tail risk measures on the basis of their statistical and economic validity. Our main conclusion is that the option-implied measure of Bollerslev and Todorov (2011b) outperforms all others.
Maik Dierkes +3 more
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In this study we comprehensively investigate the usefulness of the tail risk measures proposed in the literature, evaluating the tail risk measures on the basis of their statistical and economic validity. Our main conclusion is that the option-implied measure of Bollerslev and Todorov (2011b) outperforms all others.
Maik Dierkes +3 more
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Tail Risk in the Tail: Estimating High Quantiles When a Related Variable is Extreme
Journal of the American Statistical AssociationIn this article we address the problem of high quantile estimation conditional on a related variable being extreme. The problem set-up is of interest in a number applications to evaluate tail risk of a focal variable in the tail of a conditioning variable.
Natalia Nolde, Chen Zhou, Menglin Zhou
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Value-at-risk with heavy-tailed risk factors
Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on Computational Intelligence for Financial Engineering (CIFEr) (Cat. No.00TH8520), 2002This paper develops methods for computationally efficient calculation of value-at-risk (VAR) in the presence of heavy-tailed risk factors. The methods model market risk factors through a multivariate t-distribution, which has both heavy tails and empirical support.
Paul Glasserman +2 more
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Conditional tail behaviour and Value at Risk
Quantitative Finance, 2007In this paper we study the tail behaviour of eight major market indexes stratifying data according to the violation of a high threshold on the previous day. The distributional differences found can be exploited to improve VaR calculations in several settings, giving rise to what we call ‘MCVaR’.
Bellini F., FIGA' TALAMANCA, GIANNA
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SSRN Electronic Journal, 2009
In order to address the risk of systemic crises it is of paramount importance to have advance information about banks' exposures to large (negative) shocks. In this paper we develop a simple method for quantifying such exposures in a forward-looking manner.
Martin Knaup, Wolf Wagner
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In order to address the risk of systemic crises it is of paramount importance to have advance information about banks' exposures to large (negative) shocks. In this paper we develop a simple method for quantifying such exposures in a forward-looking manner.
Martin Knaup, Wolf Wagner
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Tailing Tail Risk in the Hedge Fund Industry
SSRN Electronic Journal, 2012This paper aims to assess dynamic tail risk exposure in the hedge fund sector using daily data. We use a copula function to model both lower and upper tail dependence between hedge-fund and broad-market returns as a function of market uncertainty. We proxy the latter by means of a single index that combines the options-implied market volatility, the ...
Walter Distaso +2 more
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