S&P volatility, VIX, and asymptotic volatility estimates
Yosef Bonaparte,
Arjun Chatrath and
Rohan Christie-David
Finance Research Letters, 2023, vol. 51, issue C
Abstract:
We examine the efficacy of the VIX as a predictor of 30-day forward S&P 500 volatility. We find that its accuracy hovers between 20% and 25%, depending on sampling period. An alternative framework, built on asymptotic distribution theory (AVE), predicts this volatility with an accuracy between 90% to 95%. The adjusted R-square adjudicates for accuracy. Other goodness-of-fit measures corroborate this evidence. We suggest that this outcome is underpinned by the fact that (a) options price behaviors do not adequately reflect stock market volatility patterns, and (b) our methodology accounts more comprehensively for idiosyncratic risk.
Keywords: VIX; Realized volatility; Asymptotic distribution theory (search for similar items in EconPapers)
JEL-codes: G10 G12 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:51:y:2023:i:c:s1544612322005694
DOI: 10.1016/j.frl.2022.103392
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