2021
DOI: 10.1016/j.mex.2020.101198
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Predicting the European stock market during COVID-19: A machine learning approach

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Cited by 46 publications
(28 citation statements)
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“…Regarding Europe Khattak et al (2021) used a machine learning technique from January 1 to June 26, 2020, to investigate the influence of the European market of 21 shocks during the covid-19 pandemic crisis. They found that the European market was affected mainly by the index of Singapore, Switzerland, Spain, France, Germany, and the S&P500.…”
Section: Literature Reviewmentioning
confidence: 99%
See 1 more Smart Citation
“…Regarding Europe Khattak et al (2021) used a machine learning technique from January 1 to June 26, 2020, to investigate the influence of the European market of 21 shocks during the covid-19 pandemic crisis. They found that the European market was affected mainly by the index of Singapore, Switzerland, Spain, France, Germany, and the S&P500.…”
Section: Literature Reviewmentioning
confidence: 99%
“…France is the second power in the EU member countries after Germany, so it is significant to investigate the effect of the pandemic on its pharmaceutical industry because, as a leading economy, it might have contagious effects on the other EU members. Khattak et al (2021) found that Germany and France were the predictors that influenced most of the European market due to the Covid-19 crisis.…”
Section: Introductionmentioning
confidence: 99%
“…This study provides the following insights. The results show an existence of a long-run relationship among employment, labor productivity and trade openness 1 One of the important lessons from the current COVID-19 pandemic is that countries have become more open and, as a result, they have become more susceptible to external shocks like the COVID-19 outbreak; see Akram et al (2020), Vidya, andPrabheesh (2020), Chen et al (2020), Devpura (2020), Devpura and Narayan (2020), Iyke (2020a, b, c), Khattak et al (2020), Liu, Sun and Zhang (2020), Liu, Choo and Lee (2020), Mishra et al (2020), Narayan (2020a, b, c), Narayan, Devpura and Wang (2020), Narayan, Phan and Liu (2020), Narayan, Gong and Ahmed (2020), Phan and Narayan (2020), Sha and Sharma (2020), Sharma &Sha (2020), andSharma (2020) for studies exploring the impact of the COVID-19 pandemic on economies). Therefore, understanding how openness affects indicators like employment and productivity is of importance to economic agents.…”
Section: Introductionmentioning
confidence: 97%
“…In addition to equities, the influence of the other assets classes like cryptocurrency (Conlon & McGee, 2020;Demir et al, 2020), gold (Gharib et al, 2021); Mensi et al, 2020), real estate (Milcheva, 2021;Ling et al, 2020), oil price (Sharif et al, 2020;Wu et al, 2021) and bonds (Falato et al, 2020) have been explored by the research. Furthermore, by examining the potential internal and external determinants, Khattak et al (2021) explored the potential predictors of European financial market during COVID-19 crisis. In this literature, they have used Least Absolute Shrinkage and Selection Operator (LASSO) Machine Learning technique for both selections of the model and regularization in the analysis.…”
Section: Introductionmentioning
confidence: 99%