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Modeling autoregressive conditional skewness and kurtosis with multi-quantile CAViaR

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  • White, Halbert
  • Kim, Tae-Hwan
  • Manganelli, Simone

Abstract

Engle and Manganelli (2004) propose CAViaR, a class of models suitable for estimating conditional quantiles in dynamic settings. Engle and Manganelli apply their approach to the estimation of Value at Risk, but this is only one of many possible applications. Here we extend CAViaR models to permit joint modeling of multiple quantiles, Multi-Quantile (MQ) CAViaR. We apply our new methods to estimate measures of conditional skewness and kurtosis defined in terms of conditional quantiles, analogous to the unconditional quantile-based measures of skewness and kurtosis studied by Kim and White (2004). We investigate the performance of our methods by simulation, and we apply MQ-CAViaR to study conditional skewness and kurtosis of S&P 500 daily returns. JEL Classification: C13, C32

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Bibliographic Info

Paper provided by European Central Bank in its series Working Paper Series with number 0957.

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Date of creation: Nov 2008
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Handle: RePEc:ecb:ecbwps:20080957

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Related research

Keywords: Asset returns; CAViaR; conditional quantiles; Dynamic quantiles; Kurtosis; Skewness;

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Cited by:
  1. Durán-Vázquez, Rocio & Lorenzo-Valdes, Arturo & Ruiz-Porras, Antonio, 2012. "Un modelo GARCH con asimetría condicional autorregresiva para modelar series de tiempo: Una aplicación para el Indice de Precios y Cotizaciones
    [A GARCH model with autorregresive conditional asym
    ," MPRA Paper 42548, University Library of Munich, Germany.
  2. Krishnakumar, Jaya & Kabili, Andi & Roko, Ilir, 2012. "Estimation of SEM with GARCH errors," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3153-3181.
  3. White, Halbert & Kim, Tae-Hwan & Manganelli, Simone, 2010. "VAR for VaR: measuring systemic risk using multivariate regression quantiles," MPRA Paper 35372, University Library of Munich, Germany.
  4. Duran-Vazquez, Rocio & Lorenzo-Valdes, Arturo & Ruiz-Porras, Antonio, 2013. "Un modelo GARCH con asimetria condicional autorregresiva para modelar series de tiempo: Una aplicacion para los rendimientos del Indice de Precios y Cotizaciones de la BMV
    [A GARCH model with autor
    ," MPRA Paper 46328, University Library of Munich, Germany.
  5. Tae-Hwan Kim & Christophe Muller, 2012. "Bias Transmission and Variance Reduction in Two-Stage Quantile Regression," Working Papers halshs-00793372, HAL.
  6. Huo, Lijuan & Kim, Tae-Hwan & Kim, Yunmi, 2012. "Robust estimation of covariance and its application to portfolio optimization," Finance Research Letters, Elsevier, vol. 9(3), pages 121-134.
  7. Charle Augusto Llondoño, 2011. "Regresión del cuantil aplicada al modelo de redes neuronales artificiales. Una aproximación de la estructura CAViaR para el mercado de valores colombi," ENSAYOS SOBRE POLÍTICA ECONÓMICA, BANCO DE LA REPÚBLICA - ESPE.

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