Measurement of common risks in tails: A panel quantile regression model for financial returns
Jozef Baruník () and
Journal of Financial Markets, 2021, vol. 52, issue C
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.
Keywords: Panel quantile regression; Realized measures; Value-at-risk (search for similar items in EconPapers)
JEL-codes: C14 C23 G17 G32 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:finmar:v:52:y:2021:i:c:s1386418120300318
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