PosTR: Position Transition Reasoning for Multi-agent Financial Decisions

Multi-agent financial trading systems typically improve decision quality by assigning specialized agents to analyze heterogeneous information sources, such as market signals, historical trends, and fundamental factors. However, their final decisions are often compressed into coarse-grained actions, such as buy, hold, and sell, resulting in a mismatch between rich analytical reasoning and simplified trading execution. When an aggregator receives only such action labels, distinct target-position transitions and their implied market assessments are treated as the same action, a loss we term Decision Semantic Collapse. % To address this limitation, we propose PosTR, a Position Transition Reasoning framework that reformulates multi-agent trading from action prediction into position-transition reasoning. % Instead of directly aggregating discrete trading actions, PosTR introduces an ordered position-state space, where each agent provides a target position, its transition from the previous target position, and a distribution over candidate target positions. This formulation preserves the target-position transition and its implied market assessment while representing uncertainty over the current target position. % , while enabling heterogeneous agent opinions to be fused within a unified state space rather than through action-level voting % Furthermore, PosTR develops a transition-aware credibility mechanism that dynamically evaluates agent reliability. The learned credibility scores reweight trader distributions during consensus formation, while settled branch performance controls the strength of the credibility-based correction. % Experiments with role-specialized agents on eight equities spanning eight sectors show stronger net and risk-adjusted performance than endpoint-only, static-weight, and history-aware baselines. These results highlight that effective multi-agent trading requires reasoning over position-state transitions rather than merely aggregating discrete trading actions.