IDEAS home Printed from https://ideas.repec.org/r/eee/jbfina/v32y2008i2p269-282.html
   My bibliography  Save this item

The role of autoregressive conditional skewness and kurtosis in the estimation of conditional VaR

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Karmakar, Madhusudan, 2013. "Estimation of tail-related risk measures in the Indian stock market: An extreme value approach," Review of Financial Economics, Elsevier, vol. 22(3), pages 79-85.
  2. Grigory Franguridi, 2014. "Higher order conditional moment dynamics and forecasting value-at-risk (in Russian)," Quantile, Quantile, issue 12, pages 69-82, February.
  3. Ergün, A. Tolga & Jun, Jongbyung, 2010. "Time-varying higher-order conditional moments and forecasting intraday VaR and Expected Shortfall," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(3), pages 264-272, August.
  4. Wu, Xinyu & Xia, Michelle & Zhang, Huanming, 2020. "Forecasting VaR using realized EGARCH model with skewness and kurtosis," Finance Research Letters, Elsevier, vol. 32(C).
  5. Alex Huang, 2013. "Value at risk estimation by quantile regression and kernel estimator," Review of Quantitative Finance and Accounting, Springer, vol. 41(2), pages 225-251, August.
  6. Yang (Greg) Hou & Mark Holmes, 2020. "Do higher order moments of return distribution provide better decisions in minimum-variance hedging? Evidence from US stock index futures," Australian Journal of Management, Australian School of Business, vol. 45(2), pages 240-265, May.
  7. Ekaterina Smetanina & Wei Biao Wu, 2021. "Asymptotic theory for QMLE for the real‐time GARCH(1,1) model," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(5-6), pages 752-776, September.
  8. Díaz, Antonio & Esparcia, Carlos, 2021. "Dynamic optimal portfolio choice under time-varying risk aversion," International Economics, Elsevier, vol. 166(C), pages 1-22.
  9. Wilson Calmon & Eduardo Ferioli & Davi Lettieri & Johann Soares & Adrian Pizzinga, 2021. "An Extensive Comparison of Some Well‐Established Value at Risk Methods," International Statistical Review, International Statistical Institute, vol. 89(1), pages 148-166, April.
  10. Benjamin R. Auer & Benjamin Mögel, 2016. "How Accurate are Modern Value-at-Risk Estimators Derived from Extreme Value Theory?," CESifo Working Paper Series 6288, CESifo.
  11. Xing Yan & Weizhong Zhang & Lin Ma & Wei Liu & Qi Wu, 2020. "Parsimonious Quantile Regression of Financial Asset Tail Dynamics via Sequential Learning," Papers 2010.08263, arXiv.org.
  12. Edimilson Costa Lucas & Wesley Mendes Da Silva & Gustavo Silva Araujo, 2017. "Does Extreme Rainfall Lead to Heavy Economic Losses in the Food Industry?," Working Papers Series 462, Central Bank of Brazil, Research Department.
  13. Bonato, Matteo & Demirer, Riza & Gupta, Rangan & Pierdzioch, Christian, 2018. "Gold futures returns and realized moments: A forecasting experiment using a quantile-boosting approach," Resources Policy, Elsevier, vol. 57(C), pages 196-212.
  14. Huang, Zhuo & Liang, Fang & Wang, Tianyi & Li, Chao, 2021. "Modeling dynamic higher moments of crude oil futures," Finance Research Letters, Elsevier, vol. 39(C).
  15. Julia S. Mehlitz & Benjamin R. Auer, 2021. "Time‐varying dynamics of expected shortfall in commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(6), pages 895-925, June.
  16. Fang, Libing & Chen, Baizhu & Yu, Honghai & Qian, Yichuo, 2018. "Identifying systemic important markets from a global perspective: Using the ADCC ΔCoVaR approach with skewed-t distribution," Finance Research Letters, Elsevier, vol. 24(C), pages 137-144.
  17. Del Brio, Esther B. & Mora-Valencia, Andrés & Perote, Javier, 2017. "The kidnapping of Europe: High-order moments' transmission between developed and emerging markets," Emerging Markets Review, Elsevier, vol. 31(C), pages 96-115.
  18. Hou, Yang (Greg) & Li, Steven, 2020. "Volatility and skewness spillover between stock index and stock index futures markets during a crash period: New evidence from China," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 166-188.
  19. Zhu, Pengfei & Lu, Tuantuan & Chen, Shenglan, 2022. "How do crude oil futures hedge crude oil spot risk after the COVID-19 outbreak? A wavelet denoising-GARCHSK-SJC Copula hedge ratio estimation method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
  20. Sobreira, Nuno & Louro, Rui, 2020. "Evaluation of volatility models for forecasting Value-at-Risk and Expected Shortfall in the Portuguese stock market," Finance Research Letters, Elsevier, vol. 32(C).
  21. Lin, Chu-Hsiung & Changchien, Chang-Cheng & Kao, Tzu-Chuan & Kao, Wei-Shun, 2014. "High-order moments and extreme value approach for value-at-risk," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 421-434.
  22. Esparcia, Carlos & Jareño, Francisco & Umar, Zaghum, 2022. "Revisiting the safe haven role of Gold across time and frequencies during the COVID-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
  23. Chesney, Marc & Reshetar, Ganna & Karaman, Mustafa, 2011. "The impact of terrorism on financial markets: An empirical study," Journal of Banking & Finance, Elsevier, vol. 35(2), pages 253-267, February.
  24. Agbeyegbe, Terence D., 2015. "An inverted U-shaped crude oil price return-implied volatility relationship," Review of Financial Economics, Elsevier, vol. 27(C), pages 28-45.
  25. Sylvia J. Soltyk & Felix Chan, 2023. "Modeling time‐varying higher‐order conditional moments: A survey," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 33-57, February.
  26. Panagiotis Samartzis & Nikitas Pittis & Nikolaos Kourogenis & Phoebe Koundouri, 2013. "Factor Models of Stock Returns: GARCH Errors versus Autoregressive Betas," DEOS Working Papers 1318, Athens University of Economics and Business.
  27. Phoebe Koundouri & Nikolaos Kourogenis & Nikitas Pittis & Panagiotis Samartzis, 2016. "Factor Models of Stock Returns: GARCH Errors versus Time‐Varying Betas," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(5), pages 445-461, August.
  28. Madhusudan Karmakar, 2013. "Estimation of tail‐related risk measures in the Indian stock market: An extreme value approach," Review of Financial Economics, John Wiley & Sons, vol. 22(3), pages 79-85, September.
  29. León, Ángel & Ñíguez, Trino-Manuel, 2020. "Modeling asset returns under time-varying semi-nonparametric distributions," Journal of Banking & Finance, Elsevier, vol. 118(C).
  30. Dai, Xingyu & Xiao, Ling & Wang, Qunwei & Dhesi, Gurjeet, 2021. "Multiscale interplay of higher-order moments between the carbon and energy markets during Phase III of the EU ETS," Energy Policy, Elsevier, vol. 156(C).
  31. Jian Yang & Yinggang Zhou & Zijun Wang, 2010. "Conditional Coskewness in Stock and Bond Markets: Time-Series Evidence," Management Science, INFORMS, vol. 56(11), pages 2031-2049, November.
  32. Marie-Anne Cam & Vikash Ramiah, 2014. "The influence of systematic risk factors and econometric adjustments in catastrophic event studies," Review of Quantitative Finance and Accounting, Springer, vol. 42(2), pages 171-189, February.
  33. Cathy Yi†Hsuan Chen & Thomas C. Chiang, 2016. "Empirical Analysis of the Intertemporal Relationship between Downside Risk and Expected Returns: Evidence from Time†varying Transition Probability Models," European Financial Management, European Financial Management Association, vol. 22(5), pages 749-796, November.
  34. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
  35. Michał Woźniak & Marcin Chlebus, 2021. "HCR & HCR-GARCH – novel statistical learning models for Value at Risk estimation," Working Papers 2021-10, Faculty of Economic Sciences, University of Warsaw.
  36. Pérignon, Christophe & Smith, Daniel R., 2010. "Diversification and Value-at-Risk," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 55-66, January.
  37. Steven J. Cochran & Iqbal Mansur & Babatunde Odusami, 2016. "Conditional higher order moments in metal asset returns," Quantitative Finance, Taylor & Francis Journals, vol. 16(1), pages 151-167, January.
  38. Straetmans, Stefan & Chaudhry, Sajid M., 2015. "Tail risk and systemic risk of US and Eurozone financial institutions in the wake of the global financial crisis," Journal of International Money and Finance, Elsevier, vol. 58(C), pages 191-223.
  39. Phoebe Koundouri & Nikolaos Kourogenis & Nikitas Pittis & Panagiotis Samartzis, 2015. "Factor Models as 'Explanatory Unifiers' versus 'Explanatory Ideals' of Empirical Regularities of Stock Returns," DEOS Working Papers 1507, Athens University of Economics and Business.
  40. Hammoudeh, Shawkat & Araújo Santos, Paulo & Al-Hassan, Abdullah, 2013. "Downside risk management and VaR-based optimal portfolios for precious metals, oil and stocks," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 318-334.
  41. Wang, Tianyi & Liang, Fang & Huang, Zhuo & Yan, Hong, 2022. "Do realized higher moments have information content? - VaR forecasting based on the realized GARCH-RSRK model," Economic Modelling, Elsevier, vol. 109(C).
  42. Odusami, Babatunde O, 2021. "Forecasting the Value-at-Risk of REITs using realized volatility jump models," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
  43. Anjum, Hassan & Malik, Farooq, 2020. "Forecasting risk in the US Dollar exchange rate under volatility shifts," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
  44. Huang, Alex YiHou, 2010. "An optimization process in Value-at-Risk estimation," Review of Financial Economics, Elsevier, vol. 19(3), pages 109-116, August.
  45. Abad, Pilar & Benito, Sonia, 2013. "A detailed comparison of value at risk estimates," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 258-276.
  46. Trung H. Le & Apostolos Kourtis & Raphael Markellos, 2023. "Modeling skewness in portfolio choice," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(6), pages 734-770, June.
  47. Hou, Yang & Holmes, Mark, 2017. "On the effects of static and autoregressive conditional higher order moments on dynamic optimal hedging," MPRA Paper 82000, University Library of Munich, Germany.
  48. Xue Jiang & Liyan Han & Yang Xu, 2021. "How does skewness perform in the Chinese commodity futures market?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(8), pages 1268-1285, August.
  49. Wang, Zijun, 2012. "The causal structure of bond yields," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 93-102.
  50. Marius Lux & Wolfgang Karl Härdle & Stefan Lessmann, 2020. "Data driven value-at-risk forecasting using a SVR-GARCH-KDE hybrid," Computational Statistics, Springer, vol. 35(3), pages 947-981, September.
  51. Cheng, Wan-Hsiu & Hung, Jui-Cheng, 2011. "Skewness and leptokurtosis in GARCH-typed VaR estimation of petroleum and metal asset returns," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 160-173, January.
  52. Su, Jung-Bin, 2014. "Empirical analysis of long memory, leverage, and distribution effects for stock market risk estimates," The North American Journal of Economics and Finance, Elsevier, vol. 30(C), pages 1-39.
  53. Benjamin Mögel & Benjamin R. Auer, 2018. "How accurate are modern Value-at-Risk estimators derived from extreme value theory?," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 979-1030, May.
  54. Alex YiHou Huang, 2010. "An optimization process in Value‐at‐Risk estimation," Review of Financial Economics, John Wiley & Sons, vol. 19(3), pages 109-116, August.
  55. Hood, Matthew & Malik, Farooq, 2018. "Estimating downside risk in stock returns under structural breaks," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 102-112.
  56. Hua, Jian & Manzan, Sebastiano, 2013. "Forecasting the return distribution using high-frequency volatility measures," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4381-4403.
  57. Hiroyuki Kawakatsu, 2022. "Modeling Realized Variance with Realized Quarticity," Stats, MDPI, vol. 5(3), pages 1-25, September.
  58. Yeguang Chi & Wenyan Hao & Yifei Zhang, 2022. "Volatility model applications in China's SSE50 options market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(9), pages 1704-1720, September.
  59. Wu, Qi & Yan, Xing, 2019. "Capturing deep tail risk via sequential learning of quantile dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 109(C).
  60. You, Leyuan & Daigler, Robert T., 2010. "Is international diversification really beneficial?," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 163-173, January.
  61. Trung H. Le, 2024. "Forecasting VaR and ES in emerging markets: The role of time‐varying higher moments," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 402-414, March.
  62. Petros Messis & Achilleas Zapranis, 2014. "Herding behaviour and volatility in the Athens Stock Exchange," Journal of Risk Finance, Emerald Group Publishing, vol. 15(5), pages 572-590, November.
  63. Benjamin R. Auer, 2019. "Does the strength of capital market anomalies exhibit seasonal patterns?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(1), pages 91-103, January.
  64. Moreno, David & Rodríguez, Rosa, 2009. "The value of coskewness in mutual fund performance evaluation," Journal of Banking & Finance, Elsevier, vol. 33(9), pages 1664-1676, September.
  65. Ibrahim Ergen, 2015. "Two-step methods in VaR prediction and the importance of fat tails," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 1013-1030, June.
  66. Pilar Abad Romero & Sonia Benito Muela & Miguel Angel Sánchez Granero & Carmen López, 2013. "Evaluating the performance of the skewed distributions to forecast Value at Risk in the Global Financial Crisis," Documentos de Trabajo del ICAE 2013-40, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  67. Hassan A. Fallahgoul & Young S. Kim & Frank J. Fabozzi, 2016. "Elliptical tempered stable distribution," Quantitative Finance, Taylor & Francis Journals, vol. 16(7), pages 1069-1087, July.
  68. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.