The Determinants of the Model-Free Positive and Negative Volatilities

Abstract

In this paper we analyze the role of macroeconomic and financial determinants in explaining stock market volatilities in the U.S. market. Both implied and realized volatility are computed model-free and decomposed into positive and negative components, thereby allowing us to compute directional volatility risk premia. We capture the behaviour of each component of implied volatility and risk premium in relation to their different determinants. The negative implied volatility appears to be linked more towards financial conditions variables such as uncertainty and geopolitical risk indexes, whereas positive implied volatility is driven more by macro variables such as inflation and GDP. There is a clear shift in importance from macro towards financial determinants moving from the pre towards the post financial crisis. A mixed frequency Granger causality approach uncovers causality relationships between volatilities and risk premia and macro variables and vice versa, a finding which is not detected with a conventional low frequency VAR model.

Tourism and economic growth: Multi-country evidence from mixed-frequency Granger causality tests

“…However, international TA is a floating variable and by aggregating a predictor variable into a lower frequency may conceal important predictive information. Therefore, we use the mixed-frequency VAR (MF-VAR) approach of Ghysels et al (2016) to congenialise different frequency variables within the same empirical model so as to overcome the temporal aggregation bias (see Bevilacqua et al, 2019; Boffelli et al, 2016; Ferrara and Guérin, 2018; Ghysels, 2016). To address the time-variability patterns, we extend the full-sample approach of Ghysels et al (2016) to a time-varying MF-VAR framework by using a rolling window method.…”

The SKEW index: Extracting what has been left

“…In order to decompose the VIX index the same formula used for the total VIX is applied (see Kilic and Shaliastovich, 2019;Bevilacqua et al, 2019). For VIX + we keep calls only (K i ≥ K 0 ), while for VIX − we keep puts only (K i ≤ K 0 ).…”

“…In order to facilitate a more like-for-like comparison we also decompose the VIX into its positive and negative components following (Kilic and Shaliastovich, 2019;Bevilacqua et al, 2019). We apply the same OTM options selection and filter rules as in section 2.…”