Modeling and predicting the CBOE market volatility index
Journal of Banking and Finance ,
v. 40, 2014
p. 1-10,
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.
Marcelo Fernandes, Marcelo Medeiros, Marcel Scharth Figueiredo Pinto.