This paper is the first to examine the evolution of price discovery in agricultural commodity markets across the four distinct phases determined by trade friction and trade policy uncertainty. Using cointegrated vector autoregressive model and common factor weights, we report that corn, cotton, soybean meal, and sugar (palm oil, soybean, soybean oil, and wheat) futures (spot) play a dominant role in price discovery during the full sample period. Moreover, the leadership in price discovery evolves over time in conjunction with changes in trade friction phases. However, such results vary across commodities. We also report that most of the agricultural commodity markets are predominantly led by futures markets in price discovery during phase Ⅲ, except for the wheat market. Our results indicate that taking trade friction into consideration would benefit portfolio managements and diversifying agricultural trade partners holds significance.

The China-U.S. trade frictions and COVID-19 pandemic have caused unprecedentedly high economic policy uncertainty since 2017. To resist this high uncertainty, investors may prefer large stocks over small stocks, thereby damaging the size effect. To test this inference, we apply data from China to show that the size effect becomes insignificant after 2017. However, a significant size effect re-emerges among stocks with low valuations or low volatility, and this is positively associated with the increment of the economic policy uncertainty index. We also find that when uncertainty increases, institutional investors increase their holdings in small stocks before 2017, but hold more large stocks after 2017. Our findings consistently suggest that high policy uncertainty may change investors' preferences for firm size and cause the disappearance of the size effect, and only among stocks with low risk, size effects may show up due to low-risk small firms' similar function in resisting market uncertainty as large firms. Other mechanisms, such as the quality premium, unexpected profitability shock, shell value, or M&A option value, are not applicable in explaining the findings in China. Our study contributes to proposing a new mechanism for the time-variability of the size effect.

Climate change has become mankind’s main challenge. Greenhouse gas (GHG) emissions from shipping are not irresponsible for this, representing 3% of the global total; an amount equal to that of Germany’s emissions. The Fourth Greenhouse Gas Study 2020 of the International Maritime Organization (IMO) predicts that the proportion of GHG emissions from shipping will rise further, as global trade continues to recover and grow, along with the economic development of India, China and Africa. China and the European Union have proposed to include shipping in their carbon emissions trading systems (ETS). As a result, the study of the relationship between the carbon finance market and the shipping industry, attempted here for the first time, is particularly important both for policymakers and shipowners. We use wavelet analysis and the spillover index methods to explore the dynamic dependence and information spillovers between the carbon finance market and shipping. We discover a long-term dependence and information linkages between the two markets, with the carbon finance market being the dominant one. Major events, such as the 2009 global financial crisis; Brexit in 2016; the 2018 China-US trade frictions; and COVID-19 are shown to strengthen the dependence of carbon finance and shipping. We find that the dependence is strongest between the EU carbon finance market and dry bulk shipping, while the link is weaker in the case of tanker shipping. Nonetheless, carbon finance and tanker shipping showed a relatively stronger dependence when OPEC refused to cut production in 2014, and when the China-US trade dispute led to the collapse of oil prices after 2018. We show that information spillovers between carbon finance and shipping are bidirectional and asymmetric. The carbon finance market is the principal transmitter of information. Our results and their interpretation provide guidance to governments on whether (and how) to include shipping in emissions trading schemes, supporting at the same time the environmental sustainability decisions of shipping companies.