Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/30729
Title: | Extremal quantiles and stock price crashes | Authors: | Andreou, Panayiotis Anyfantaki, Sofia Maasoumi, Esfandiar Sala, Carlo |
Major Field of Science: | Social Sciences | Field Category: | Economics and Business | Keywords: | Extremal quantiles;extreme value theory;quantile regression;stock price crashes | Issue Date: | 1-Jan-2023 | Source: | Econometric Reviews, 2023, vol. 42, iss. 9-10, pp. 703 - 724 | Volume: | 42 | Issue: | 9-10 | Start page: | 703 | End page: | 724 | Journal: | Econometric Reviews | Abstract: | We employ extreme value theory to identify stock price crashes, featuring low-probability events that produce large, idiosyncratic negative outliers in the conditional distribution. Traditional methods employ approximations under Gaussian assumptions and central moments. This is inherently imprecise and susceptible to misspecifications, especially for tail events. We instead propose new definitions and measures for crash risk based on conditional extremal quantiles (CEQ) of idiosyncratic stock returns. CEQ provide information on quantile-specific impact of covariates, and shed light on prior empirical puzzles and shortcomings in identifying crashes. Additionally, to capture the magnitude of crashes, we provide an expected shortfall analysis of the losses due to crash. Our findings have important implications for a burgeoning literature in financial economics that relies on traditional approximations. | URI: | https://hdl.handle.net/20.500.14279/30729 | ISSN: | 07474938 | DOI: | 10.1080/07474938.2023.2241223 | Rights: | © Taylor & Francis Group | Type: | Article | Affiliation : | Cyprus University of Technology Durham University Business School Bank of Greece Emory University Ramon Llull University |
Publication Type: | Peer Reviewed |
Appears in Collections: | Άρθρα/Articles |
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