Version 1
: Received: 4 November 2024 / Approved: 5 November 2024 / Online: 5 November 2024 (13:30:13 CET)
How to cite:
Jha, A.; Shirvani, A.; Rachev, S. T.; Fabozzi, F. J. Beyond the Traditional VIX: A Novel Approach to Identifying Uncertainty Shocks in the Financial Markets. Preprints2024, 2024110320. https://doi.org/10.20944/preprints202411.0320.v1
Jha, A.; Shirvani, A.; Rachev, S. T.; Fabozzi, F. J. Beyond the Traditional VIX: A Novel Approach to Identifying Uncertainty Shocks in the Financial Markets. Preprints 2024, 2024110320. https://doi.org/10.20944/preprints202411.0320.v1
Jha, A.; Shirvani, A.; Rachev, S. T.; Fabozzi, F. J. Beyond the Traditional VIX: A Novel Approach to Identifying Uncertainty Shocks in the Financial Markets. Preprints2024, 2024110320. https://doi.org/10.20944/preprints202411.0320.v1
APA Style
Jha, A., Shirvani, A., Rachev, S. T., & Fabozzi, F. J. (2024). Beyond the Traditional VIX: A Novel Approach to Identifying Uncertainty Shocks in the Financial Markets. Preprints. https://doi.org/10.20944/preprints202411.0320.v1
Chicago/Turabian Style
Jha, A., Svetlozar T. Rachev and Frank J. Fabozzi. 2024 "Beyond the Traditional VIX: A Novel Approach to Identifying Uncertainty Shocks in the Financial Markets" Preprints. https://doi.org/10.20944/preprints202411.0320.v1
Abstract
We introduce a new identification strategy for uncertainty shocks to explain macroeconomic volatility in financial markets. The Chicago Board Options Exchange Volatility Index (VIX) measures market expectations of future volatility, but traditional methods based on second-moment shocks and time-varying volatility of the VIX often fail to capture the non-Gaussian, heavy-tailed nature of asset returns. To address this, we construct a revised VIX by fitting a double-subordinated Normal Inverse Gaussian Lévy process to S\&P 500 option prices, providing a more comprehensive measure of volatility that reflects the extreme movements and heavy tails observed in financial data. Using an axiomatic approach, we introduce a general family of risk-reward ratios, computed with our revised VIX and fitted over a fractional time series to more accurately identify uncertainty shocks in financial markets.
Keywords
Asset Pricing; Volatility; Long Memory; Uncertainty Shocks; Financial Market Modeling
Subject
Business, Economics and Management, Economics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
