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We present a simple and efficient microeconomic model incorporating generic components for trade of cattle at the level of agricultural holdings, using supply-and-demand processes as a basis for animal movements. By combining within-node dynamics of stocks with stochastic jumps describing animal exchanges between nodes, our model reproduces the dynamical network of animal trade between holdings. Variants of the model, either closely calibrated on the data, or based on mechanistic economical assumptions, are considered. In addition to mathematical investigation of the average dynamical behaviour, model performances are assessed on three datasets (including or not intermediary trade operators such as marketplaces and assembly centres), covering 5 years of cattle movement in the départementof Finistère (France), as a case study. Model outputs are compared with data regarding the average size of traded batches per holding and the length of temporal trade chains with the potential to transmit disease across the market. We observe an overall good agreement with the data, with variations between models, depending on the criteria (aggregated or time-varying) and datasets considered. These findings highlight the impact of high-volume nodes such as markets and assembly centres on trade flows, as well as the importance of correctly reproducing temporal features of dynamical trade networks. Our study represents one of the first attempts of building dynamical models of livestock trade networks, incorporating simple economic mechanisms, proving to be useful for analysing and predicting cattle trade movements. Future work in this direction might lead to a more detailed analysis of the subnetworks (e.g. beef, dairy) of this complex market, as well as a better understanding of the economic drivers underlying cattle movement, allowing the improvement of predictions of its temporal features, especially in the context of outbreaks.