  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.
