Correlations and volatility spillovers between oil prices and the stock prices of clean energy and technology companies

In this paper, multivariate GARCH models are used to model conditional correlations and to analyze the volatility spillovers between oil prices and the stock prices of clean energy companies and technology companies. Four different multivariate GARCH models (BEKK, diagonal, constant conditional correlation, and dynamic conditional correlation) are compared and contrasted. The dynamic conditional correlation model is found to fit the data the best and generates results showing that the stock prices of clean energy companies correlate more highly with technology stock prices than with oil prices. On average, a $1 long position in clean energy companies can be hedged for 20 cents with a short position in the crude oil futures market.

Research Highlights► The volatility dynamics between oil prices and the stock prices of clean energy and technology companies are modeled. ► The dynamic conditional correlation MGARCH model fits the data the best. ► The stock prices of clean energy companies correlate more highly with technology stock prices than with oil prices. ► On average, a $1 long position in clean energy companies can be hedged for 20 cents with a short position in the crude oil futures market. ► Optimal portfolio weights are calculated.