The impact of Covid-19 on clean energy stocks : a quantile regression study

Abstract

This paper utilizes a quantile regression to investigate the behavior of clean energy markets during the Covid-19 outbreak, whilst uncovering the events of the pandemic that affected their performance. To carry out these tests, the indices we adopted were PBD, PBW, PZD, TAN, NasdaqAsia, NasdaqEurope, and S&PEnergy. Then, we used EMV and EPU to represent the Covid-19 pandemic alongside four different dummy variables, each representing a dissimilar event during the pandemic, this analysis is based on the quantile regression method (QAR), developed by Koenker and Basset Jr (1978). Daily data of stock prices were collected from January 2, 2018, to January 27, 2021. The findings reveal that the EPU index had more of a significant impact than the EMV index. This was because political uncertainty followed the announcement of the pandemic; therefore, the effects on the returns of the indices occurred due to their level of exposure in the United States. Our findings also reveal that out of the four dummy variables, dummy variable three had an all-around significant impact on most of the indices. This is seen as dummy variable three was the start of confinement in New York. This result goes hand in hand with the followed effect the EPU index had on the chosen clean energy indices.