Uncertainty Due to Infectious Diseases and Stock–Bond Correlation
Konstantinos Gkillas (),
Christoforos Konstantatos () and
Costas Siriopoulos ()
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Konstantinos Gkillas: Department of Management Science & Technology, University of Patras, Megalou Aleksandrou 1, Koukouli, 26334 Patras, Greece
Christoforos Konstantatos: Department of Business Administration, University of Patras, University Campus—Rio, P.O. Box 1391, 26504 Patras, Greece
Costas Siriopoulos: College of Business, Zayed University, Abu Dhabi P.O. Box 144534, United Arab Emirates
Econometrics, 2021, vol. 9, issue 2, 1-18
We study the non-linear causal relation between uncertainty-due-to-infectious-diseases and stock–bond correlation. To this end, we use high-frequency 1-min data to compute daily realized measures of correlation and jumps, and then, we employ a nonlinear Granger causality test with the use of artificial neural networks so as to investigate the predictability of this type of uncertainty on realized stock–bond correlation and jumps. Our findings reveal that uncertainty-due-to-infectious-diseases has significant predictive value on the changes of the stock–bond relation.
Keywords: artificial neural networks; Granger causality test; nonlinearity; uncertainty; infectious diseases; stock–bond correlation (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jecnmx:v:9:y:2021:i:2:p:17-:d:539153
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