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Autoregresive conditional volatility, skewness and kurtosis

Citations

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Cited by:

  1. Dark Jonathan Graeme, 2010. "Estimation of Time Varying Skewness and Kurtosis with an Application to Value at Risk," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(2), pages 1-50, March.
  2. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
  3. Christodoulakis, George A., 2005. "Financial forecasts in the presence of asymmetric loss aversion, skewness and excess kurtosis," Finance Research Letters, Elsevier, vol. 2(4), pages 227-233, December.
  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. Wei Kuang, 2021. "Dynamic VaR forecasts using conditional Pearson type IV distribution," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 500-511, April.
  6. Massimiliano Giacalone & Demetrio Panarello, 2022. "A Nonparametric Approach for Testing Long Memory in Stock Returns’ Higher Moments," Mathematics, MDPI, vol. 10(5), pages 1-21, February.
  7. Vacca, Gianmarco & Zoia, Maria Grazia & Bagnato, Luca, 2022. "Forecasting in GARCH models with polynomially modified innovations," International Journal of Forecasting, Elsevier, vol. 38(1), pages 117-141.
  8. Zhu, Pengfei & Lu, Tuantuan & Shang, Yue & Zhang, Zerong & Wei, Yu, 2023. "Can China's national carbon trading market hedge the risks of light and medium crude oil? A comparative analysis with the European carbon market," Finance Research Letters, Elsevier, vol. 58(PA).
  9. Suryo Adi Rakhmawan & Tahir Mahmood & Nasir Abbas & Muhammad Riaz, 2024. "Unifying mortality forecasting model: an investigation of the COM–Poisson distribution in the GAS model for improved projections," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 30(4), pages 800-826, October.
  10. 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.
  11. Geon Ho Choe & Kyungsub Lee, 2013. "High moment variations and their application," Papers 1311.4973, arXiv.org.
  12. Kei Nakagawa & Yusuke Uchiyama, 2020. "GO-GJRSK Model with Application to Higher Order Risk-Based Portfolio," Mathematics, MDPI, vol. 8(11), pages 1-12, November.
  13. Cui, Jinxin & Maghyereh, Aktham, 2024. "Unveiling interconnectedness: Exploring higher-order moments among energy, precious metals, industrial metals, and agricultural commodities in the context of geopolitical risks and systemic stress," Journal of Commodity Markets, Elsevier, vol. 33(C).
  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. Roy Cerqueti & Pierpaolo D’Urso & Livia Giovanni & Raffaele Mattera & Vincenzina Vitale, 2024. "Fuzzy clustering of time series based on weighted conditional higher moments," Computational Statistics, Springer, vol. 39(6), pages 3091-3114, September.
  16. 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.
  17. 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).
  18. 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.
  19. Chen, Bin-xia & Sun, Yan-lin, 2024. "Risk characteristics and connectedness in cryptocurrency markets: New evidence from a non-linear framework," The North American Journal of Economics and Finance, Elsevier, vol. 69(PA).
  20. Ñíguez, Trino-Manuel & Perote, Javier, 2017. "Moments expansion densities for quantifying financial risk," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 53-69.
  21. Liu, Xiaochun, 2015. "Modeling time-varying skewness via decomposition for out-of-sample forecast," International Journal of Forecasting, Elsevier, vol. 31(2), pages 296-311.
  22. 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.
  23. Kräussl, Roman & Lehnert, Thorsten & Senulytė, Sigita, 2016. "Euro crash risk," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 417-428.
  24. Georges Hübner & Thomas Lejeune, 2015. "Portfolio choice and investor preferences : A semi-parametric approach based on risk horizon," Working Paper Research 289, National Bank of Belgium.
  25. Bruno Feunou & Mohammad R. Jahan-Parvar & Roméo Tédongap, 2016. "Which parametric model for conditional skewness?," The European Journal of Finance, Taylor & Francis Journals, vol. 22(13), pages 1237-1271, October.
  26. Yi-Hsien Wang & Chung-Chu Chuang, 2009. "Selecting the portfolio investment strategy under political structure change in United States," Quality & Quantity: International Journal of Methodology, Springer, vol. 43(5), pages 845-854, September.
  27. Zhu, Pengfei & Tang, Yong & Wei, Yu & Dai, Yimin & Lu, Tuantuan, 2021. "Relationships and portfolios between oil and Chinese stock sectors: A study based on wavelet denoising-higher moments perspective," Energy, Elsevier, vol. 217(C).
  28. Umar, Zaghum & Usman, Muhammad & Choi, Sun-Yong & Rice, John, 2023. "Diversification benefits of NFTs for conventional asset investors: Evidence from CoVaR with higher moments and optimal hedge ratios," Research in International Business and Finance, Elsevier, vol. 65(C).
  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. Narayan, Paresh Kumar & Liu, Ruipeng, 2018. "A new GARCH model with higher moments for stock return predictability," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 56(C), pages 93-103.
  31. Hallam, Mark & Olmo, Jose, 2014. "Forecasting daily return densities from intraday data: A multifractal approach," International Journal of Forecasting, Elsevier, vol. 30(4), pages 863-881.
  32. Zhang, Hanxiong & Auer, Benjamin R. & Vortelinos, Dimitrios I., 2018. "Performance ranking (dis)similarities in commodity markets," Global Finance Journal, Elsevier, vol. 35(C), pages 115-137.
  33. Zhu, Zhoufan & Zhang, Ningning & Zhu, Ke, 2024. "Big portfolio selection by graph-based conditional moments method," Journal of Empirical Finance, Elsevier, vol. 78(C).
  34. Dai, Jun & Zhou, Haigang & Zhao, Shaoquan, 2017. "Determining the multi-scale hedge ratios of stock index futures using the lower partial moments method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 502-510.
  35. Wu, Xinyu & Xie, Haibin, 2021. "A realized EGARCH-MIDAS model with higher moments," Finance Research Letters, Elsevier, vol. 38(C).
  36. Belén Nieto & Alfonso Novales Cinca & Gonzalo Rubio, 2011. "Why do variance swaps exist?," Documentos de Trabajo del ICAE 2011-06, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  37. León, Ángel & Ñíguez, Trino-Manuel, 2021. "The transformed Gram Charlier distribution: Parametric properties and financial risk applications," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 323-349.
  38. Nieto, Belén & Novales, Alfonso & Rubio, Gonzalo, 2014. "Variance swaps, non-normality and macroeconomic and financial risks," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 257-270.
  39. Alizadeh, Amir H. & Gabrielsen, Alexandros, 2013. "Dynamics of credit spread moments of European corporate bond indexes," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3125-3144.
  40. Trino-Manuel Ñíguez & Javier Perote, 2012. "Forecasting Heavy-Tailed Densities with Positive Edgeworth and Gram-Charlier Expansions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(4), pages 600-627, August.
  41. Zhou, Donghai & Liu, Xiaoxing & Tang, Chun, 2024. "Does the international oil market interact with China’s financial market? New evidence from time-varying higher moments," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
  42. 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.
  43. Murilo Voltarelli & Rouverson Silva & Vicente Silva & Fábio Cavichioli & Ariel Compagnon, 2013. "Performance Mechanized Set Tractor-Planter of Sugarcane Planting in Two Operation Shifts," Journal of Agricultural Science, Canadian Center of Science and Education, vol. 5(11), pages 1-54, October.
  44. Ñíguez, Trino-Manuel & Paya, Ivan & Peel, David & Perote, Javier, 2012. "On the stability of the constant relative risk aversion (CRRA) utility under high degrees of uncertainty," Economics Letters, Elsevier, vol. 115(2), pages 244-248.
  45. Serna, Gregorio, 2023. "On the predictive ability of conditional market skewness," The Quarterly Review of Economics and Finance, Elsevier, vol. 91(C), pages 186-191.
  46. Zhou, Yuqin & Wu, Shan & Zhang, Zeyi, 2022. "Multidimensional risk spillovers among carbon, energy and nonferrous metals markets: Evidence from the quantile VAR network," Energy Economics, Elsevier, vol. 114(C).
  47. 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).
  48. Liu, Zhifeng & Huynh, Toan Luu Duc & Dai, Peng-Fei, 2021. "The impact of COVID-19 on the stock market crash risk in China," Research in International Business and Finance, Elsevier, vol. 57(C).
  49. Peng-Fei Dai & Xiong Xiong & Zhifeng Liu & Toan Luu Duc Huynh & Jianjun Sun, 2021. "Preventing crash in stock market: The role of economic policy uncertainty during COVID-19," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-15, December.
  50. Bouri, Elie & Jalkh, Naji, 2023. "Spillovers of joint volatility-skewness-kurtosis of major cryptocurrencies and their determinants," International Review of Financial Analysis, Elsevier, vol. 90(C).
  51. Travkin, Alexandr, 2013. "Pair copula constructions in portfolio optimization ploblem," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 32(4), pages 110-133.
  52. Cheng, Xixin & Li, W.K. & Yu, Philip L.H. & Zhou, Xuan & Wang, Chao & Lo, P.H., 2011. "Modeling threshold conditional heteroscedasticity with regime-dependent skewness and kurtosis," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2590-2604, September.
  53. Hou, Yang & Li, Steven & Wen, Fenghua, 2019. "Time-varying volatility spillover between Chinese fuel oil and stock index futures markets based on a DCC-GARCH model with a semi-nonparametric approach," Energy Economics, Elsevier, vol. 83(C), pages 119-143.
  54. Zhu, Ke & Li, Wai Keung, 2013. "A new Pearson-type QMLE for conditionally heteroskedastic models," MPRA Paper 52344, University Library of Munich, Germany.
  55. Umar, Zaghum & Usman, Muhammad & Umar, Muhammad & Ktaish, Farah, 2024. "Interdependencies and risk management strategies between green cryptocurrencies and traditional energy sources," Energy Economics, Elsevier, vol. 136(C).
  56. Arnold Polanski & Evarist Stoja, 2010. "Incorporating higher moments into value-at-risk forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(6), pages 523-535.
  57. 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).
  58. Atance, David & Serna, Gregorio, 2024. "Time-varying expected returns, conditional skewness and Bitcoin return predictability," The Quarterly Review of Economics and Finance, Elsevier, vol. 96(C).
  59. Stanislav Anatolyev & Natalia Kryzhanovskaya, 2009. "Directional Prediction of Returns under Asymmetric Loss: Direct and Indirect Approaches," Working Papers w0136, New Economic School (NES).
  60. Del Brio, Esther B. & Perote, Javier, 2012. "Gram–Charlier densities: Maximum likelihood versus the method of moments," Insurance: Mathematics and Economics, Elsevier, vol. 51(3), pages 531-537.
  61. Chu, Wen-Jun & Fan, Li-Wei & Zhou, P., 2024. "Extreme spillovers across carbon and energy markets: A multiscale higher-order moment analysis," Energy Economics, Elsevier, vol. 138(C).
  62. Usman, Muhammad & Umar, Zaghum & Choi, Sun-Yong & Teplova, Tamara, 2024. "Quantifying endogenous and exogenous shocks to financial sector systemic risk: A comparison of GFC and COVID-19," The Quarterly Review of Economics and Finance, Elsevier, vol. 94(C), pages 281-293.
  63. Doaa Akl Ahmed & Mamdouh M. Abdelsalam, 2015. "Modelling the Density of Egyptian Quarterly CPI Inflation," Working Papers 936, Economic Research Forum, revised Aug 2015.
  64. Chen, Zhenlong & Liu, Junjie & Hao, Xiaozhen, 2024. "Can asymmetry, long memory, and current return information improve crude oil volatility prediction? ——Evidence from ASHARV-MIDAS model," Finance Research Letters, Elsevier, vol. 64(C).
  65. Boudt, Kris & Lu, Wanbo & Peeters, Benedict, 2015. "Higher order comoments of multifactor models and asset allocation," Finance Research Letters, Elsevier, vol. 13(C), pages 225-233.
  66. Jiménez, Inés & Mora-Valencia, Andrés & Perote, Javier, 2023. "Multivariate dynamics between emerging markets and digital asset markets: An application of the SNP-DCC model," Emerging Markets Review, Elsevier, vol. 56(C).
  67. Zhu, Pengfei & Tang, Yong & Wei, Yu & Lu, Tuantuan, 2021. "Multidimensional risk spillovers among crude oil, the US and Chinese stock markets: Evidence during the COVID-19 epidemic," Energy, Elsevier, vol. 231(C).
  68. Shum, Wai Yan, 2020. "Modelling conditional skewness: Heterogeneous beliefs, short sale restrictions and market declines," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
  69. Luo, Changqing & Qu, Yi & Su, Yaya & Dong, Liang, 2024. "Risk spillover from international crude oil markets to China’s financial markets: Evidence from extreme events and U.S. monetary policy," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).
  70. 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).
  71. Carnero, M. Angeles & León, Angel & Ñíguez, Trino-Manuel, 2023. "Skewness in energy returns: estimation, testing and retain-->implications for tail risk," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 178-189.
  72. Lai, Jing-yi, 2012. "Shock-dependent conditional skewness in international aggregate stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 72-83.
  73. Liu, Xiaochun & Luger, Richard, 2015. "Unfolded GARCH models," Journal of Economic Dynamics and Control, Elsevier, vol. 58(C), pages 186-217.
  74. Kyungsub Lee, 2013. "Probabilistic and statistical properties of moment variations and their use in inference and estimation based on high frequency return data," Papers 1311.5036, arXiv.org, revised Jul 2015.
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