0472346 20240103213753.020170309235959.9 85013269709 000394467800006 10.1515/snde-2016-0044 17 s. P cav_un_epca*02557881081-1826211 (2017)81-97 copula quantile regression realized volatility value-at-risk cav_un_auth*0294289 Ekonometrie Department of Econometrics E E Department of Econometrics 50% Avdulaj Krenar UTIA-B CZ Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0242028 Ekonometrie Department of Econometrics E E Department of Econometrics 50% Baruník Jozef UTIA-B CZ Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2017/E/avdulaj-0472346.pdf cav_un_auth*0281000 GBP402/12/G097 GA ČR CZ Accurately measuring and forecasting value-at-risk (VaR) remains a challenging task at the heart of financial economic theory. Recently, quantile regression models have been used successfully to capture the conditional quantiles of returns and to forecast VaR accurately. In this paper, we further explore nonlineari- ties in data and propose to couple realized measures with the nonlinear quantile regression framework to explain and forecast the conditional quantiles of financial returns. The nonlinear quantile regression models are implied by the copula specifications and allow us to capture possible nonlinearities, tail dependence, and asymmetries in the conditional quantiles of financial returns. Using high frequency data that covers most liquid US stocks in seven sectors, we provide ample evidence of asymmetric conditional dependence with dif- ferent levels of dependence, which are characteristic for each industry. The backtesting results of estimated VaR favour our approach. AH 50000 50200 50202 2018 2 RVO:67985556 http://hdl.handle.net/11104/0271353 cav_un_auth*0308308 Institute of Economic Studies, Faculty of Social Sciences, Charles University in Prague IES FSV UK CZ S 3+4 Article|Proceedings Paper Economics|Social Sciences Mathematical Methods 3+4 Article|Proceedings Paper Economics|Social Sciences Mathematical Methods 3+4 Article|Proceedings Paper Economics|Social Sciences Mathematical Methods ECONOMICS|SOCIALSCIENCES.MATHEMATICALMETHODS 0.734 0.115 11.1 0.00064 0.302 401 0.668 0.823 26 Q3 18.997 30.8 Q4 Q2 0.35 Q3 34.136 2017 85013269709 SCOPUS PUBMED 000394467800006 WOS cav_un_epca*0255788 Studies in Nonlinear Dynamics and Econometrics 1081-1826 1558-3708 Roč. 21 č. 1 2017 81 97