In this paper, the optimization of dynamic financial network structure based on minimum spanning tree algorithm is studied. Based on the collection and preprocessing of some historical trading data of the A-share market and the Hong Kong stock market, a dynamic financial network is constructed based on the application of correlation coefficient and minimum spanning tree algorithm (MST), and its characteristic indicators are calculated. After experiments, it can be seen that the algorithm can show high stability and flexibility in response to market changes, which can effectively simplify the network structure and improve its transmission efficiency. This research will provide new methods and ideas for financial market analysis and investment decision-making.