Granger causality of bivariate stationary curve time series
JOURNAL OF FORECASTING, cilt.40, sa.4, ss.626-635, 2021 (SSCI, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 40 Sayı: 4
- Basım Tarihi: 2021
- Doi Numarası: 10.1002/for.2732
- Dergi Adı: JOURNAL OF FORECASTING
- Derginin Tarandığı İndeksler: Social Sciences Citation Index (SSCI), Scopus, International Bibliography of Social Sciences, ABI/INFORM, Business Source Elite, Business Source Premier, Compendex, EconLit, INSPEC, Public Affairs Index, Sociological abstracts, zbMATH
- Sayfa Sayıları: ss.626-635
- Anahtar Kelimeler: functional time series, G‐, causality, Granger causality, GENERALIZED CORRELATION, INFERENCE
- Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
- Marmara Üniversitesi Adresli: Evet
Özet
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.