Beyond the Traditional VIX: A Novel Approach to Identifying Uncertainty Shocks in Financial Markets

Ayush Jha, Abootaleb Shirvani, Svetlozar T. Rachev, Frank J. Fabozzi

Research output: Contribution to journalArticlepeer-review

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 the market expectations of future volatility, but traditional methods based on second-moment shocks and the time-varying volatility of the VIX often do not effectively to capture the non-Gaussian, heavy-tailed nature of asset returns. To address this, we constructed a revised VIX by fitting a double-subordinated Normal Inverse Gaussian Lévy process to S&P 500 log returns, to provide a more comprehensive measure of volatility that captures the extreme movements and heavy tails observed in financial data. Using an axiomatic framework, we developed a family of risk–reward ratios that, when computed with our revised VIX and fitted to a long-memory time series model, provide a more precise identification of uncertainty shocks in financial markets.

Original languageEnglish
Article number11
JournalJournal of Risk and Financial Management
Volume18
Issue number1
DOIs
StatePublished - Jan 2025

Keywords

  • asset pricing
  • financial market modeling
  • long memory
  • uncertainty shocks
  • volatility

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