A semiparametric nonlinear quantile regression model for financial returns

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11230%2F17%3A10338032" target="_blank" >RIV/00216208:11230/17:10338032 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1515/snde-2016-0044" target="_blank" >http://dx.doi.org/10.1515/snde-2016-0044</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1515/snde-2016-0044" target="_blank" >10.1515/snde-2016-0044</a>

Result language

angličtina

Original language name

A semiparametric nonlinear quantile regression model for financial returns

Original language description

Accurately measuring and forecasting value-at-risk (VaR) remains a challenging task at the heart of financial economic theory. Recently, quantile regression models have been used successfully to capture the conditional quantiles of returns and to forecast VaR accurately. In this paper, we further explore nonlinearities in data and propose to couple realized measures with the nonlinear quantile regression framework to explain and forecast the conditional quantiles of financial returns. The nonlinear quantile regression models are implied by the copula specifications and allow us to capture possible nonlinearities, tail dependence, and asymmetries in the conditional quantiles of financial returns. Using high frequency data that covers most liquid US stocks in seven sectors, we provide ample evidence of asymmetric conditional dependence with different levels of dependence, which are characteristic for each industry. The backtesting results of estimated VaR favour our approach.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

50201 - Economic Theory

Project

<a href="/en/project/GBP402%2F12%2FG097" target="_blank" >GBP402/12/G097: DYME-Dynamic Models in Economics</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Studies in Nonlinear Dynamics and Econometrics

ISSN

1081-1826

e-ISSN

—

Volume of the periodical

21

Issue of the periodical within the volume

1

Country of publishing house

US - UNITED STATES

Number of pages

17

Pages from-to

81-97

UT code for WoS article

000394467800006

EID of the result in the Scopus database

2-s2.0-85013269709