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Dynamic quantile models · Study

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ArticleDynamic quantile models

Christian Gouriéroux2008

Article2008

Dynamic quantile models

Christian Gouriéroux · Joann Jasiak

92 citations·0/0 files stored·Journal of Econometrics

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Financial Risk and Volatility Modeling Statistical Distribution Estimation and Applications Statistical Methods and Inference

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References

1998Evaluating Interval Forecasts 2004CAViaR 1998Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data 2006Tests of Conditional Predictive Ability 1996Value at risk: the new benchmark for controlling market risk 2000A Class of Distortion Operators for Pricing Financial and Insurance Risks 2004Unit Root Quantile Autoregression Inference 2005Evaluation and Combination of Conditional Quantile Forecasts

Cited by

2016Nonlinear panel data estimation via quantile regressions 2015Conditional quantiles and tail dependence 2011Kernel density estimation for time series data 2016Quantile autoregression neural network model with applications to evaluating value at risk 2012Pitfalls in backtesting Historical Simulation VaR models 2010Robust Backtesting Tests for Value-at-risk Models

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2016Frontiers in VaR forecasting and backtestingarticle · 5 shared references 2005Volatility Forecastingreport · 5 shared references 2006VOLATILITY AND CORRELATION FORECASTINGarticle · 5 shared references 2013Forecasting value-at-risk using time varying copulas and EVT return distributionsarticle · 5 shared references 2006Evaluating predictive performance of value-at-risk models in emerging markets: a reality checkarticle · 4 shared references 2009Comparison of Volatility Measures: a Risk Management Perspectivearticle · 4 shared references

Details

Year2008

Typearticle

Published2008-09-26

VenueJournal of Econometrics

ISSN-L0304-4076

Languageen

Citations92

Files0 public / 0

ShelfFinancial Risk and Volatility Modeling

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doi10.1016/j.jeconom.2008.09.028

openalex_workW2017044442

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2009

CAViaR-based forecast for oil price risk

2012Optimally Harnessing Inter-Day and Intra-Day Information for Daily Value-at-Risk Prediction