Value-at-Risk Prediction: A Comparison of Alternative Strategies

By Keith Kuester, Stefan Mittnik, Marc S. Paolella. 2005

683 citations recorded by the source corpus.

Subfields: Finance, Global and Planetary Change, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/d5c105ffa2508f63a0c1f2123b77189a35e5dcab

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Citations in the corpus

Optimally Harnessing Inter-Day and Intra-Day Information for Daily Value-at-Risk Prediction (2013, neutral): “…the returns density belongs to a location-scale family rt+1 = µt+1 + σt+1εt+1 (1) where location µt+1 and scale σt+1 are =t-measurable functions, and εt+1 is an i.i.d. innovation with zero-location unit-scale probability density Fε (see e.g., Kuester et al., 2006; Chernozhukov and Umantsev, 2001).”
Spillover Effects among Financial Institutions: A State-Dependent Sensitivity Value-at-Risk Approach (2014, neutral): “In fact, recent studies show that these univariate VaR models are already very efﬁcient, so that room for improvements is marginal at best (Kuester et al. (2006)).”
Robust Performance Hypothesis Testing with the Sharpe Ratio (2008, neutral): “The estimator Ψ̂ is obtained via kernel estimation; in particular we propose the prewhitened QS kernel of Andrews and Monahan (1992).6 The standard error s(∆̂∗) is the ‘natural’ standard error computed from the bootstrap data, making use of the special block dependence structure; see Götze and Künsc”
A comprehensive review of Value at Risk methodologies (2014, methodology): “However this method does not seem to be superior to EVT and FHS (Kuester et al., 2006; Cifter and Özün, 2007; Angelidis et al., 2007).”
Estimation and Decomposition of Downside Risk for Portfolios with Non-Normal Returns (2008, methodology): “quantile regression proposed in the literature (see Kuester et al., 2006, for a”
Evaluating Value-at-Risk Models via Quantile Regression (2008, background): “Since the first procedures suggested by Kupiec (1995) and Christoffersen (1998), a lot of research has been done in the search for adequate methodologies to assess and help improve the performance of VaRs, which (preferably) do not require the knowledge of the underlying model.”
Robust Value at Risk Prediction (2007, neutral): “Indeed, it is known that FHS-type VaR forecasts tend to display the proper number of violations; see for instance Kuester, Mittnik, and Paolella (2006) for a recent comparison of these methods.”
Value at Risk with time varying variance, skewness and kurtosis--the NIG-ACD model (2009, neutral): “These results can be compared with the recent study by Kuester et al. (2006) who”
Comparison of Volatility Measures: A Risk Management Perspective (2010, neutral): “Kuester et al. (2006) contains a review and comparison of many proposals.”
The Dark Side of Global Integration: Increasing Tail Dependence (2010, neutral): “asymmetric reactions to positive and negative returns (Engle and Manganelli, 2004) or an AR(1)-GARCH(1,1) specification (Kuester et al., 2006).”
The Impact of Terrorism on Financial Markets: An Empirical Study (2011, background): “In their recent paper, Kuester et al. (2006) give an extensive and detailed overview and comparison of alternative strategies to predict VaR.”
ROBUST BACKTESTING TESTS FOR VALUE-AT-RISK MODELS (2011, background): “(2004) or Kuester, Mittnik and Paolella (2006) , condition (2 ) is a necessary but not su‐cient”
Estimating Value at Risk and Expected Shortfall Using Expectiles (2007, background): “very well in terms of VaR estimation in the study of Kuester, Mittnik and Paolella (2006) .”