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https://dipositint.ub.edu/dspace/handle/2445/193707
Title: | Cross-sectional quantile regression for estimating conditional VaR of returns during periods of high volatility |
Author: | Vidal-Llana, Xenxo Guillén, Montserrat |
Keywords: | Avaluació del risc Valor (Economia) Anàlisi de regressió Risk assessment Value (Economics) Regression analysis |
Issue Date: | 17-Nov-2022 |
Publisher: | Elsevier |
Abstract: | 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. |
Note: | Reproducció del document publicat a: https://doi.org/10.1016/j.najef.2022.101835 |
It is part of: | North American Journal of Economics and Finance, 2022, vol. 63, p. 101835 |
URI: | http://hdl.handle.net/2445/193707 |
Related resource: | https://doi.org/10.1016/j.najef.2022.101835 |
ISSN: | 1062-9408 |
Appears in Collections: | Articles publicats en revistes (Econometria, Estadística i Economia Aplicada) |
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729805.pdf | 1.54 MB | Adobe PDF | View/Open |
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