Exploring the dynamic nonlinear relationship between crude oil price and implied volatility indices: A new perspective from MMV-MFDFA

Abstract

This paper investigates the cross-correlations between the crude oil market and three implied volatility indices for the crude oil market, the stock markets in emerging and developed economies. We employed a newly developed method—the multiscale multivariate multifractal detrended fluctuation analysis (MMV-MFDFA) within the framework of the fractal market hypothesis (FMH). The research target here is to detect the fractal autocorrelation characteristics for the time series covered in this study. The empirical results demonstrate that cross-correlated behaviors have multifractal features. The cross-correlated behaviors of smaller fluctuations are persistent while large fluctuations are anti-persistent between crude oil and OVX. The cross-correlated behaviors between crude oil and implied indices of the developed and emerging markets are anti-persistent both small and large fluctuations. Crude oil price fluctuations and the implied volatility indices change in a positive direction in the short term, but in the reverse direction in the long term. In addition, the multifractal strength between crude oil and implied volatility index for crude oil market is larger than that between crude oil and emerging and developed stock markets. Political, economic, and military shocks, with relatively large influence have a major impact on the internal volatility of the system. The findings of nonlinear and multifractal correlations between crude oil and implied volatility indices suggest that, due to existing of market inefficiency and multifractality,​ investors can, to some extent, predict the future trends of crude oil price movements based on changes in the volatility indices, thereby adjusting their investment strategies to avoid risks.