“A BFS-DFS Approach” Semi-Stock-Temporal Graph Traversals for Market Influence

In this study each stock is particularized vertex in Temporal Graph model, and directional co-movements based
create an edge on trading days G_t=(V,〖 E〗_t ). The discrete time layers are fluctuating the market structure, in
imbalance to static graph. Based on Breadth-First Search (BFS) and Depth First Search (DFS), To create a
temporal traversal framework to investigate this dynamic market network. Whereas temporal DFS discovers
vertical sequence of effect across consecutive days, temporal BFS discovers vertical sequence of effect across
Consecutive days, temporal BFS grows level by level across time, capturing the horizontal dispersion of links
between equities on each trading day. The Semi-Temporal graph’s reachability patterns, linked temporal
components, and leading- lagging chains of vertices are all visible through these traversals. This graph-theoretic
viewpoint lays the groundwork for developing multigraph structures, constructing temporal routes, and
incorporating classical methods into financial network research without depending on statistical models.