Abstract

Motivated by the drive to improve the performance and growth of clean energy technology amidst related high-tech innovations, the vulnerability of clean energy and high-tech stock prices to oil shocks is examined, by illustrating the potential bubbles and time-varying interactions among the commodities over the period from January 2004 to December 2017. In this regard, we contribute to the literature in two aspects. First, we analyze an empirically important issue with the SADF (Supremum Augmented Dickey-Fuller) approach for explosive bubbles in oil price, clean energy, and high-tech stock prices. Second, the Markov Chain Monte Carlo (MCMC) approach of the Bayesian time-varying parameter Vector Autoregressions model with stochastic volatility (TVP-SVAR) technique is used to account for time-varying and state dependent interactions between commodities. We found that the time varying behavior of the dependence among clean energy, high technology stocks and oil prices is mainly due to major bubbles identified in the underlying series. We established contrasting evidence between the responses of clean energy and high-tech stocks to oil disruption shocks. Moreover, the stock return volatilities of high technology stocks have no effect on investors’ expectations of clean energy returns across different time horizons. Overall, this study presents significantly relevant policy guideline.

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