Granger causality of bivariate stationary curve time series

Han Lin Shang, Kaiying Ji and Ufuk Beyaztas

Journal of Forecasting, 2021, vol. 40, issue 4, 626-635

Abstract: We study causality between bivariate curve time series using the Granger causality generalized measures of correlation. With this measure, we can investigate which curve time series Granger‐causes the other; in turn, it helps determine the predictability of any two curve time series. Illustrated by a climatology example, we find that the sea surface temperature Granger‐causes sea‐level atmospheric pressure. Motivated by a portfolio management application in finance, we single out those stocks that lead or lag behind Dow Jones industrial averages. Given a close relationship between S&P 500 index and crude oil price, we determine the leading and lagging variables.

Date: 2021
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https://doi.org/10.1002/for.2732

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Persistent link: https://EconPapers.repec.org/RePEc:wly:jforec:v:40:y:2021:i:4:p:626-635

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