S&P volatility, VIX, and asymptotic volatility estimates
•The efficacy of the VIX as a predictor of 30-day forward S&P 500 volatility is between 20% and 25%, depending on sampling period.•Our framework, built on asymptotic distribution theory (AVE), predicts this volatility with an accuracy between 90% to 95%.•The adjusted R-square adjudicates for acc...
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Published in | Finance research letters Vol. 51; p. 103392 |
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Format | Journal Article |
Language | English |
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01.01.2023
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Abstract | •The efficacy of the VIX as a predictor of 30-day forward S&P 500 volatility is between 20% and 25%, depending on sampling period.•Our 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.•Why is this? 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.•What about implications? The evidence from this study has important implications. One, the VIX, which relies on current prices of options will provide poor and perhaps misleading guidance of future volatility. Two, standard statistical frameworks like the one we employ outperforms the VIX, and three, market participants should regard the VIX as a measure of current sentiment rather than as a volatility-forecasting tool.
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. |
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AbstractList | •The efficacy of the VIX as a predictor of 30-day forward S&P 500 volatility is between 20% and 25%, depending on sampling period.•Our 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.•Why is this? 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.•What about implications? The evidence from this study has important implications. One, the VIX, which relies on current prices of options will provide poor and perhaps misleading guidance of future volatility. Two, standard statistical frameworks like the one we employ outperforms the VIX, and three, market participants should regard the VIX as a measure of current sentiment rather than as a volatility-forecasting tool.
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. |
ArticleNumber | 103392 |
Author | Christie-David, Rohan Bonaparte, Yosef Chatrath, Arjun |
Author_xml | – sequence: 1 givenname: Yosef surname: Bonaparte fullname: Bonaparte, Yosef email: yosef.bonaparte@ucdenver.edu organization: University of Colorado - Denver, Denver, CO, United States – sequence: 2 givenname: Arjun surname: Chatrath fullname: Chatrath, Arjun organization: University of Portland, Portland, OR, United States – sequence: 3 givenname: Rohan orcidid: 0000-0002-0822-1743 surname: Christie-David fullname: Christie-David, Rohan email: Rohan.Christie-David@tamusa.edu organization: Texas A&M University - San Antonio, San Antonio, TX, United States |
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Cites_doi | 10.1002/jae.800 10.1016/j.jeconom.2010.03.034 10.1016/j.jeconom.2014.05.008 10.1016/0304-4076(85)90149-6 10.1016/j.jmoneco.2012.10.012 10.1016/j.frl.2022.102887 10.1016/j.frl.2022.102995 10.1111/j.1540-6261.2004.00647.x 10.1093/rfs/hhi027 10.3905/JPM.2009.35.3.098 10.1093/rfs/hhn038 10.1016/j.frl.2022.102981 |
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