Linkages among the Foreign Exchange, Stock, and Bond Markets in Japan and the United States

Yi Jiang, Shohei Shimizu
Proceedings of the 2023 Causal Analysis Workshop Series, PMLR 223:1-19, 2023.

Abstract

While economic theory explains the linkages among the financial markets of different countries, empirical studies mainly verify the linkages through Granger causality, without considering latent variables or instantaneous effects. Their findings are inconsistent regarding the existence of causal linkages among financial markets, which might be attributed to differences in the focused markets, data periods, and methods applied. Our study adopts causal discovery methods including VAR-LiNGAM and LPCMCI with domain knowledge to explore the linkages among financial markets in Japan and the United States (US) for the post Covid-19 pandemic period under divergent monetary policy directions. The VAR-LiNGAM results reveal that the previous day’s US market influences the following day’s Japanese market for both stocks and bonds, and the bond markets of the previous day impact the following day’s foreign exchange (FX) market directly and the following day’s Japanese stock market indirectly. The LPCMCI results indicate the existence of potential latent confounders. Our results demonstrate that VAR-LiNGAM uniquely identifies the directed acyclic graph (DAG), and thus provides informative insight into the causal relationship when the assumptions are considered valid. Our study contributes to a better understanding of the linkages among financial markets in the analyzed data period by supporting the existence of linkages between Japan and the US for the same financial markets and among FX, stock, and bond markets, thus highlighting the importance of leveraging causal discovery methods in the financial domain.

Cite this Paper

BibTeX
@InProceedings{pmlr-v223-jiang23a, title = {Linkages among the Foreign Exchange, Stock, and Bond Markets in Japan and the United States}, author = {Jiang, Yi and Shimizu, Shohei}, booktitle = {Proceedings of the 2023 Causal Analysis Workshop Series}, pages = {1--19}, year = {2023}, editor = {Kummerfeld, Erich and Ma, Sisi and Rawls, Eric and Andrews, Bryan}, volume = {223}, series = {Proceedings of Machine Learning Research}, month = {14 Aug}, publisher = {PMLR}, pdf = {https://proceedings.mlr.press/v223/jiang23a/jiang23a.pdf}, url = {https://proceedings.mlr.press/v223/jiang23a.html}, abstract = {While economic theory explains the linkages among the financial markets of different countries, empirical studies mainly verify the linkages through Granger causality, without considering latent variables or instantaneous effects. Their findings are inconsistent regarding the existence of causal linkages among financial markets, which might be attributed to differences in the focused markets, data periods, and methods applied. Our study adopts causal discovery methods including VAR-LiNGAM and LPCMCI with domain knowledge to explore the linkages among financial markets in Japan and the United States (US) for the post Covid-19 pandemic period under divergent monetary policy directions. The VAR-LiNGAM results reveal that the previous day’s US market influences the following day’s Japanese market for both stocks and bonds, and the bond markets of the previous day impact the following day’s foreign exchange (FX) market directly and the following day’s Japanese stock market indirectly. The LPCMCI results indicate the existence of potential latent confounders. Our results demonstrate that VAR-LiNGAM uniquely identifies the directed acyclic graph (DAG), and thus provides informative insight into the causal relationship when the assumptions are considered valid. Our study contributes to a better understanding of the linkages among financial markets in the analyzed data period by supporting the existence of linkages between Japan and the US for the same financial markets and among FX, stock, and bond markets, thus highlighting the importance of leveraging causal discovery methods in the financial domain.} }
Endnote
%0 Conference Paper %T Linkages among the Foreign Exchange, Stock, and Bond Markets in Japan and the United States %A Yi Jiang %A Shohei Shimizu %B Proceedings of the 2023 Causal Analysis Workshop Series %C Proceedings of Machine Learning Research %D 2023 %E Erich Kummerfeld %E Sisi Ma %E Eric Rawls %E Bryan Andrews %F pmlr-v223-jiang23a %I PMLR %P 1--19 %U https://proceedings.mlr.press/v223/jiang23a.html %V 223 %X While economic theory explains the linkages among the financial markets of different countries, empirical studies mainly verify the linkages through Granger causality, without considering latent variables or instantaneous effects. Their findings are inconsistent regarding the existence of causal linkages among financial markets, which might be attributed to differences in the focused markets, data periods, and methods applied. Our study adopts causal discovery methods including VAR-LiNGAM and LPCMCI with domain knowledge to explore the linkages among financial markets in Japan and the United States (US) for the post Covid-19 pandemic period under divergent monetary policy directions. The VAR-LiNGAM results reveal that the previous day’s US market influences the following day’s Japanese market for both stocks and bonds, and the bond markets of the previous day impact the following day’s foreign exchange (FX) market directly and the following day’s Japanese stock market indirectly. The LPCMCI results indicate the existence of potential latent confounders. Our results demonstrate that VAR-LiNGAM uniquely identifies the directed acyclic graph (DAG), and thus provides informative insight into the causal relationship when the assumptions are considered valid. Our study contributes to a better understanding of the linkages among financial markets in the analyzed data period by supporting the existence of linkages between Japan and the US for the same financial markets and among FX, stock, and bond markets, thus highlighting the importance of leveraging causal discovery methods in the financial domain.
APA
Jiang, Y. & Shimizu, S.. (2023). Linkages among the Foreign Exchange, Stock, and Bond Markets in Japan and the United States. Proceedings of the 2023 Causal Analysis Workshop Series, in Proceedings of Machine Learning Research 223:1-19 Available from https://proceedings.mlr.press/v223/jiang23a.html.

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