0533565 20240103224611.720201026235959.9 85084595565 000618640300001 10.1016/j.finmar.2020.100562 23 s. P cav_un_epca*02585061386-418152Elsevier Panel quantile regression Realized measures Value-at-risk cav_un_auth*0242028 Baruník Jozef UTIA-B Ekonometrie Department of Econometrics E E Department of Econometrics CZ Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0344057 Čech František UTIA-B Ekonometrie Department of Econometrics E E Department of Econometrics CZ Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2020/E/barunik-0533565.pdf https://www.sciencedirect.com/science/article/pii/S1386418120300318 GX19-28231X GA ČR CZ cav_un_auth*0385135 We investigate how to measure common risks in the tails of return distributions using the recently proposed panel quantile regression model for financial returns. By exploring how volatility crosses all quantiles of the return distribution and using a fixed effects estimator, we can control for otherwise unobserved heterogeneity among financial assets. Direct benefits are revealed in a portfolio value-at-risk application, where our modeling strategy performs significantly better than several benchmark models. In particular, our results show that the panel quantile regression model for returns consistently outperforms all competitors in the left tail. Sound statistical performance translates directly into economic gains. WOS AH 50000 50200 50202 2022 2 RVO:67985556 http://hdl.handle.net/11104/0311940 1 cav_un_auth*0359004 IES FSV UK CZ S 100562 1 Article Business Finance C BUSINESS.FINANCE 3.825 0.795 12.2 0.00219 1.502 2519 74 1.661 51.97 2.56 272 Q1 3.079 39 Q2 59.9 Q2 Q1 0.99 Q2 59.91 2021 85084595565 SCOPUS PUBMED 000618640300001 WOS cav_un_epca*0258506 Journal of Financial Markets 1386-4181 1878-576X Roč. 52 č. 1 2021 Elsevier