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Effective Factors under Stock Market Regimes
- 1 University of Toronto Scarborough Campus
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Abstract
The Chicago Board Options Exchange (CBOE) Volatility Index (VIX) is a measurement of volatility in the stock market, which is closely associated with the return of the risk premium. This paper categorized the monthly log returns of VIX by Gaussian Mixture Models (GMM) and investigates the driving factors of VIX among the Equity Market Volatility (EMV) trackers under different regimes using the elastic net linear regression model. As a result of categorization, two regimes in log returns of VIX are found. Regime 1 with a lower mean covers most of the months, while regime 2 with a higher mean captures the months of extreme log returns. In months of both regimes, the policy-related factor significantly and independently affects VIX. Another factor that largely affects VIX in regime 1 is the macroeconomy and other factors have little impact on VIX in regime 1. Infectious disease, policy, and government related factors are more important in affecting VIX in regime 2.
Keywords
financial economics, machine learning, CBOE Volatility Index (VIX), US news-based equity market uncertainty (EMV)
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Cite this article
Zhang,J. (2023). Effective Factors under Stock Market Regimes. Advances in Economics, Management and Political Sciences,13,52-58.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 2nd International Conference on Business and Policy Studies
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