In this paper, we adopt the nonlinear autoregressive distributed lags (NARDL) model extended by Shin et al. (2014) to investigate the relationship between the treasury yield spread and economic policy uncertainty (EPU) in Japan. This model helps us to explore the short- and long-run asymmetric reactions of explained variables through positive and negative partial sum decompositions of changes in the explanatory variable(s). In our research, the testing of the NARDL specification reveals the existence of a significant long-run asymmetric equilibrium between the yield spread and EPU in Japan. On the other hand, we find a significant positive nexus between the treasury yield spread and EPU reduction in the long run. We speculate that because of low inflation, a poor economic outlook and the low interest rate environment since 1990, financial agents are markedly sensitive to negative shocks resulting from EPU. This means that when facing a good economy, bond agents are quick to sell, especially with higher-risk long-term interest rate bonds. Meanwhile, because the Bank of Japan announced the Stock Purchasing Plan in October 2002 and from the point view of portfolio management, while the influence of a positive economic outlook dominates the negative outlook, flight from quality has no role in asset portfolio adjustment. The empirical implications are that the long history of unconventional monetary policy supports the demand for both bonds and stock markets. When taking the stock market into consideration, the correlations between the yield spread, EPU and stock market capture the full wealth effects of the low interest rate environment in Japan.

This paper studies the dynamic relationships between the Baltic Dry Index (BDI) and the BRICS stock markets by wavelet analysis for the period from January 1996 to March 2019. Compared to the causality based on linearity and the choosing of the period of lags, as well as given the significant evidence of nonlinearity, we used wavelet analysis to analyze the dynamic relationships between the two series in both time and frequency domains, which helped us to demonstrate the causality across different horizons. Due to wavelet analysis, we found that the BDI and the Brazilian stock market had a significantly positive relationship from 2002 to 2011 in the medium term and that the Brazilian stock market led the BDI from 2002 to 2004 and from 2009 to 2011. The wavelet analysis showed that the Russian and Indian stock markets dominated the BDI from 2005 to 2016 in the long term and from 2002 to 2011 in the medium term, respectively. The South African stock market and the BDI had a medium term, positive, and co-movement relationships. The empirical results of Brazil and South African indicated that commodity import-and export-related countries have similar interactions. Lastly, wavelet analysis revealed that the BDI lead the Chinese stock market from 1996 to 1998 in the medium term, while the Chinese stock market turned to dominate the BDI from 2001 to 2011, both in the medium and long term. Contribution/ Originality:This study used new estimation methodology of a wavelet-based approach to analyze the dynamic relationship between BDI and BRICS stock markets in time and frequency domains, and successfully distinguished the lead-lag relationship between the BDI and the five stock markets, that the conventional methodology could not distinguish.