Source of Publication
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.
Artificial neural networks, Granger causality test, Infectious diseases, Nonlinearity, Stock–bond correlation, Uncertainty
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Gkillas, Konstantinos; Konstantatos, Christoforos; and Siriopoulos, Costas, "Uncertainty due to infectious diseases and stock–bond correlation" (2021). All Works. 4208.
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Open Access Type
Gold: This publication is openly available in an open access journal/series