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The paper aims to analyze the evolution of oil prices and renewable energy production in Italy during the first wave of the COVID-19 pandemic crisis with daily data for the period January 2020-September 2020 through several time series techniques (long memory test and spectral causality analysis) and Wavelet Analysis tools. Italy has been the first country all over the world to be severely hit by the pandemic, reacting immediately with strong restrictive measures. The applied results show that oil prices and renewable energy sources were highly correlated during the pandemic shock. Moreover, causality tests reveal a unidirectional flow running from solar, hydro, and wind sources to oil prices, highlighting the relevance of the effect of the energy transition on the oil market. It is also imperative for a country that is a net energy resources importer to achieve a more sustainable way of production and accelerate the energy transition process, especially during phases of high fossil fuel prices. [ABSTRACT FROM AUTHOR]

This paper examines renewable and technological prices' asymmetric multifractality and efficiency in international and Chinese marketplaces. The asymmetric multifractal detrended fluctuation analytics (A-MFDFA), multifractal detrended fluctuation analytics (MFDFA), and fractal dimension techniques are employed for multifractality and herding behavior. In addition, market deficiency measures (MDM) and hurst exponents are used to construct the inefficiency index (MLM- Magnitude of long-memory) during and before Covid-19. The empirical outcomes supported the existence of asymmetric multifractality across all renewable and technological marketplaces. This multifractality has been observed in up-and-down trends. Moreover, during the COVID-19 outbreak, inefficiency in CELS and SPGlobal's green energy prices increased, which is more apparent in the descending trends. Fractal dimension outcomes suggest a herding behavior in these markets during pandemic. The SPTSX green energy pricing statistics demonstrate that its upward multifractality is larger than the downward in both phases, signifying the strong efficiency position in the market. The SPIC-SH green energy pricing displayed considerable asymmetric multifractality, higher levels of efficiency, and even low levels of market uncertainty during COVID-19. The findings imply that all financial market players should prioritize various green energy investments depending on its asymmetric efficiency and predictability. It will help in their decision-making and reduces herding behavior in the market. • Asymmetric multifractal behavior is tested in global renewable and technological prices. • A-MFDFA and MFDFA and fractal dimension are used to analyze efficiency, scaling and herding behavior during and before COVID. • CELS and SPGlobal's green energy prices showed herding behavior before and inefficacy during COVID. • Green Technology and Chinese green energy prices were stable during COVID. • All green and technological prices were more stable before COVID-19. [ABSTRACT FROM AUTHOR]