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The extreme value theory as a tool to measure market risk
Avdulaj, Krenar - 2011
Assessing the extreme events is crucial in financial risk management. All risk managers and financial institutions want to know the risk of their portfolio under rare events scenarios. We illustrate a multivariate market risk estimating method which employs Monte Carlo simulations to estimate...
Persistent link: https://www.econbiz.de/10010322252
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Efficient estimation of copula-based semiparametric Markov models
Chen, Xiaohong; Wu, Wei Biao; Yi, Yanping - 2009
This paper considers efficient estimation of copula-based semiparametric strictly stationary Markov models. These … models are characterized by nonparametric invariant distributions and parametric copula functions; where the copulas capture … maximum likelihood estimation (MLE) for the copula parameter, the invariant distribution and the conditional quantiles. We …
Persistent link: https://www.econbiz.de/10010288444
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A Stochastic Dominance Approach to the Basel III Dilemma: Expected Shortfall or VaR?
Chang, Chia-Lin; Jiménez-Martín, Juan-Ángel; … - 2015
The Basel Committee on Banking Supervision (BCBS) (2013) recently proposed shifting the quantitative risk metrics system from Value-at-Risk (VaR) to Expected Shortfall (ES). The BCBS (2013) noted that "a number of weaknesses have been identified with using VaR for determining regulatory capital...
Persistent link: https://www.econbiz.de/10011288403
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Multivariate dynamic intensity peaks-over-threshold models
Hautsch, Nikolaus; Herrera, Rodrigo - 2015
We propose a multivariate dynamic intensity peaks-over-threshold model to capture extreme events in a multivariate time series of returns. The random occurrence of extreme events exceeding a threshold is modeled by means of a multivariate dynamic intensity model allowing for feedback effects...
Persistent link: https://www.econbiz.de/10011335446
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Value-at-risk on Central and Eastern European stock markets: An empirical investigation using GARCH models
Bubák, Vít - 2008
Using daily return data from the four major Central and Eastern European stock markets including fourteen highly liquid stocks and ATX (Vienna), PX (Prague), BUX (Budapest), and WIG20 (Warsaw) market indices, we model the value-at-risk using a set of univariate GARCH-type models. Our results...
Persistent link: https://www.econbiz.de/10010322212
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GARCH Models for Daily Stock Returns: Impact of Estimation Frequency on Value-at-Risk and Expected Shortfall Forecasts
Ardia, David; Hoogerheide, Lennart - 2013
We analyze the impact of the estimation frequency - updating parameter estimates on a daily, weekly, monthly or quarterly basis - for commonly used GARCH models in a large-scale study, using more than twelve years (2000-2012) of daily returns for constituents of the S&P 500 index. We assess the...
Persistent link: https://www.econbiz.de/10010326343
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Bayesian Risk Forecasting for Long Horizons
Borowska, Agnieszka; Hoogerheide, Lennart; Koopman, Siem Jan - 2019
We present an accurate and efficient method for Bayesian forecasting of two financial risk measures, Value-at-Risk and Expected Shortfall, for a given volatility model. We obtain precise forecasts of the tail of the distribution of returns not only for the 10-days-ahead horizon required by the...
Persistent link: https://www.econbiz.de/10012114771
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Partially Censored Posterior for Robust and Efficient Risk Evaluation
Borowska, Agnieszka; Hoogerheide, Lennart; Koopman, Siem Jan - 2019
A novel approach to inference for a specific region of the predictive distribution is introduced. An important domain of application is accurate prediction of financial risk measures, where the area of interest is the left tail of the predictive density of logreturns. Our proposed approach...
Persistent link: https://www.econbiz.de/10012114810
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Backtesting Value-at-Risk and Expected Shortfall in the Presence of Estimation Error
Barendse, Sander; Kole, Erik; van Dijk, Dick - 2019
We investigate the effect of estimation error on backtests of (multi-period) expected shortfall (ES) forecasts. These backtests are based on first order conditions of a recently introduced family of jointly consistent loss functions for Value-at-Risk (VaR) and ES. We provide explicit expressions...
Persistent link: https://www.econbiz.de/10012114811
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Choosing Expected Shortfall over VaR in Basel III Using Stochastic Dominance
Chang, Chia-Lin; Jiménez-Martín, Juan-Ángel; … - 2015
Bank risk managers follow the Basel Committee on Banking Supervision (BCBS) recommendations that recently proposed shifting the quantitative risk metrics system from Value-at-Risk (VaR) to Expected Shortfall (ES). The Basel Committee on Banking Supervision (2013, p. 3) noted that: “a number of...
Persistent link: https://www.econbiz.de/10011451509