goods than among raw materials (Fig. \[fig:application\] (c)).

Some products show small $|R_p|$ but large $U_p$ owing to large fluctuations $\sigma_p^2 = T^{-1}\sum_t (R_p(t)-\langle R_p\rangle)^2$; the offer and demand for such products tends to be highly variable or historically determined e.g. railways, warships, and uranium. Thus, our predictability metric captures the fact that some products are more (or less) variable than expected, even if their trend is predicted.

Summary and discussion
======================

In this paper we presented a stochastic particle model for the kinetics of products’ shares in international trade, in which sites represent product categories and particles represent a unit of share. From the empirical scaling behavior of the annual variations of product share, the probability of a site to send a particle to another site is set to be proportional to the square of the number of particles at the two sites. Products’ shares are related to the capital invested in those product categories, and therefore such biquadratic transfer rate illuminates a fundamental nature of capital in its activity and interaction.

If the preference to popular products is weaker than that represented by the biquadratic rate, the stationary state will lie in the fluid phase, having no condensation 