Modeling and predicting the CBOE market volatility index

Marcelo Fernandes, Marcelo Medeiros () and Marcel Scharth ()

Journal of Banking & Finance, 2014, vol. 40, issue C, 1-10

Abstract: This paper performs a thorough statistical examination of the time-series properties of the daily market volatility index (VIX) from the Chicago Board Options Exchange (CBOE). The motivation lies not only on the widespread consensus that the VIX is a barometer of the overall market sentiment as to what concerns investors’ risk appetite, but also on the fact that there are many trading strategies that rely on the VIX index for hedging and speculative purposes. Preliminary analysis suggests that the VIX index displays long-range dependence. This is well in line with the strong empirical evidence in the literature supporting long memory in both options-implied and realized variances. We thus resort to both parametric and semiparametric heterogeneous autoregressive (HAR) processes for modeling and forecasting purposes. Our main findings are as follows. First, we confirm the evidence in the literature that there is a negative relationship between the VIX index and the S&P 500 index return as well as a positive contemporaneous link with the volume of the S&P 500 index. Second, the term spread has a slightly negative long-run impact in the VIX index, when possible multicollinearity and endogeneity are controlled for. Finally, we cannot reject the linearity of the above relationships, neither in sample nor out of sample. As for the latter, we actually show that it is pretty hard to beat the pure HAR process because of the very persistent nature of the VIX index.

Keywords: Heterogeneous autoregression; Implied volatility; Neural networks; VIX (search for similar items in EconPapers)
JEL-codes: C22 C53 E44 G12 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (119)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378426613004172
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Modeling and predicting the CBOE market volatility index (2013)
Working Paper: Modeling and predicting the CBOE market volatility index (2007)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:40:y:2014:i:c:p:1-10

DOI: 10.1016/j.jbankfin.2013.11.004

Access Statistics for this article

Journal of Banking & Finance is currently edited by Ike Mathur

More articles in Journal of Banking & Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().