Abstract
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.
Published Version
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