2026-04-13T07:04:14Zhttps://recercat.cat/oai/request

oai:recercat.cat:2445/1937072025-12-05T05:50:13Zcom_2072_1057col_2072_478808col_2072_478917

00925njm 22002777a 4500 dc Vidal-Llana, Xenxo author Guillén, Montserrat author 2023-02-16T15:10:29Z 2023-02-16T15:10:29Z 2022-11-17 2023-02-16T15:10:29Z Evaluating value at risk (VaR) for a firm's returns during periods of financial turmoil is a challenging task because of the high volatility in the market. We propose estimating conditional VaR and expected shortfall (ES) for a given firm's returns using quantile regression with cross-sectional (CSQR) data about other firms operating in the same market. An evaluation using US market data between 2000 and 2020 shows that our approach has certain advantages over a CAViaR model. Identification of low-risk firms and a reduction in computing times are additional advantages of the new method described. Avaluació del risc Valor (Economia) Anàlisi de regressió Risk assessment Value (Economics) Regression analysis Cross-sectional quantile regression for estimating conditional VaR of returns during periods of high volatility