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 current paper is concerned with exploring information contained in a series of undisclosed orders that are submitted by the same broker, using this information to estimate the volume contained in the current undisclosed order, and further investigating the trading patterns followed by stockbrokers in the use of undisclosed orders. In an ARMA framework, the estimation results suggest that the information revealed in past-executed undisclosed orders of a stockbroker is explanatory to the volume of the current undisclosed order submitted by the same broker. As a supplement to the current literature relating to the package-trading patterns detected in large disclosed orders, the current study finds that stockbrokers follow the same pattern in the use of undisclosed orders. A practical application of this method is to use it for the prediction of the volume enclosed in a given undisclosed order.