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Rodrigo Caballero-Fernández. Universidad Autónoma de Nuevo León, México. E-mail: rodrigofinanciero@gmail.com

Alicia Fernanda Galindo-Manrique. Instituto Tecnológico y de Estudios Superiores de Monterrey, México. E-mail: alicia.galindo@tec.mx

Alma Berenice Méndez-Sáenz. Universidad Autónoma de Nuevo León, México. E-mail: alma.mendezsn@uanl.edu.mx


The quick spread of Covid-19 saw enormous impacts on economies and financial markets (Chen & Yeh, 2021). In March 2020, the S&P 500 index dropped by more than 7% in three single days. In response to adverse effects triggered by the pandemic on the stock market returns, investors moved to ETFs as a liquid and secure investment to recover from negative abnormal returns (Mazur et al. 2020). Sector ETFs are trending upwards globally and play a key role in asset management when financial crisis arrives. The objective of this research to analyse the effect of the Covid-19 pandemic on the financial, health, technology, energy and consumer sector ETFs performance. We compare this performance in a pre-pandemic and post-pandemic scenario analysing five industries: financial, technology, health, energy, and consumer discretionary sectors. The fuzzy Jensen´s alpha is used to compare both scenarios within these industries. Due to the amount of data in our sample to solve the linear programming problems, we apply the methodology of genetic algorithms with the EVOLVER software. To carry out the analysis we use the ETF of iShares S/P 500 of five industries: financial, energy, health, information technology and consumer discretionary sectors. The timespan considered was divided in two scenarios: A post-pandemic scenario from January 02, 2019, to December 31, 2019 and a scenario that occurs during the pandemic from January 02, 2020 to December 31, 2020. The result obtained demonstrate that the industry with the best possibility to obtain abnormal or unexpected returns during 2020 pandemic was the healthcare sector. Conversely, the financial industry presented the lowest possibility to obtain abnormal or unexpected returns.

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