2016
DOI: 10.1002/fut.21824
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AVIX: An Improved VIX Based on Stochastic Interest Rates and an Adaptive Screening Mechanism

Abstract: An improved model-free implied variation index (AVIX) is proposed in this article. The AVIX is developed under a generalized semi-martingale process with stochastic interest rates. An adaptive option screening mechanism is proposed to accommodate different market conditions. The effect of dividend protection is also considered. An empirical study of the China 50 ETF option market suggests that the AVIX is a better barometer of aggregate implied variation and investor sentiment than the traditional VIX. It reac… Show more

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Cited by 9 publications
(13 citation statements)
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“…We find that iVX has a strong forecasting power for realized volatility of its underlying ETF market in the short term, particularly during market declines. Besides, the intraday iVX is positively related to the underlying price in our full sample, which is consistent with the daily results of Zheng et al () using iVIX. Further, we examine whether investor structure plays a role in the positive correlations by comparing iVX and VXFXI (CBOE China ETF Volatility Index) .…”
Section: Introductionsupporting
confidence: 92%
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“…We find that iVX has a strong forecasting power for realized volatility of its underlying ETF market in the short term, particularly during market declines. Besides, the intraday iVX is positively related to the underlying price in our full sample, which is consistent with the daily results of Zheng et al () using iVIX. Further, we examine whether investor structure plays a role in the positive correlations by comparing iVX and VXFXI (CBOE China ETF Volatility Index) .…”
Section: Introductionsupporting
confidence: 92%
“…If Hypothesis were to hold after being tested with high‐frequency data, we would observe results similar to those in Zheng et al (). More important, we highlight the correlations between iVX and negative returns of the SSE 50 ETF, and use a series of subsample analyses during the large drops to yield more details.…”
Section: Data Methodology and Hypothesessupporting
confidence: 78%
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