平准策略何以缓解金融市场认知偏差？

——基于网络博弈视角的研究

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How intervention strategy alleviates market cognitive bias： a study based on network game

NIU Xiao.jian， LIN Shi.wei，SUN Yi.han

Participants in the financial markets execute various actions such as setting industry growth targets， investment behaviors， credit guidance， and stabilizing operations. Industry cognitive biases arise correspondingly in multi.party games. This paper constructs a network game model along the logical chain of “industry growth targets—industry cognitive biases—industry future returns” to explore the direct and network effects of participants’ actions on themselves and their linked entities. It also employs singular value decomposition to derive stabilizing strategies. According to the single.condition equilibrium， deviations in pricing behavior by investors relative to analysts’ growth targets generate industry cognitive biases， which are positively correlated with future returns， thus supporting the idea that the market corrects pricing biases. In the case of multi.condition equilibrium， excessive pricing and credit will decrease the future returns of both the industry itself and those industries linked to it in excess. Growth expectations mainly affect future returns through these excess linkage relationships. Overall， the total effect of the stabilizing strategy remains robustly positive and effectively mitigates cognitive biases and enhances pricing efficiency. It is suggested that governments formulate intervention strategies from the perspective of network games to strengthen the operational efficiency of stabilizing funds.

［摘  要］ 金融市场参与者执行诸如行业增长目标设置、投资行为、信贷引导以及平准操作，行业认知偏差在多方博弈下相应而生。（剩余17247字）