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Tail Risk Measure of Implied Volatility Based on Bayesian Conditional Autoregressive Expectile Model

Year: 2024

Type: conference-paper

Abstract: In this paper, tail risk measure of financial markets is investigated by Bayesian conditional autoregressive expectile model. By introducing implied volatility as the influencing factor and the assumption of asymmetric Gaussian distribution, symmetric and asymmetric models with respect to the log-return are proposed. The accuracy and effectiveness of the proposed models are verified by numerical experiments, empirical analysis and back-testing. From the results of empirical study, we can conclude that implied volatility has positive impact on the tail risk. And market tail risks are more sensitive to the negative information.

Source: International Conference on Big Data, Artificial Intelligence and Risk Management (ICBAR)

DOI: 10.1145/3718751.3718920

Authors: Jinling Tian, Yu Fu

Institution: Shandong University of Science and Technology

Language: English

Topic: Financial Risk and Volatility Modeling

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: bronze

OpenAlex ID: W4409869002

FWCI:

Cites: 12

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Related to: 10