Customer relationship weighted momentum factor-based on supply chain network centrality
factor.formula
Customer Relationship Weighted Momentum Factor (CMOM):
in:
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It represents the return rate of j, the client of i, in the past month. This return rate reflects the client's investment performance and market sentiment, and is the core component of the momentum factor.
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Represents the weight of the relationship between company i and its customer j. The weight is calculated using the network centrality: $w_{ij}^{betweenness} = \frac{c_{ij}}{\sum_{k=1}^{N_i} c_{ik}} $ , where k represents all customers of company i.
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The Edge Betweenness Centrality is the edge between company i and customer j in the supply chain network. It measures the importance of the edge in transmitting information in the network, that is, the number of shortest paths passing through the edge in the network. The higher the value, the more critical the relationship between company i and customer j is in the supply chain network, and the greater the influence of information transmission.
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denotes the number of customers of company i.
factor.explanation
Traditional customer momentum factors usually use sales share as the weight of customer yield. This factor innovatively uses edge betweenness centrality in the supply chain network as the weight. This effectively circumvents the problem of missing sales share data, while more accurately reflecting the importance of customer relationships in the supply chain network. Empirical studies have shown that there is a significant positive correlation between edge betweenness centrality and sales share, so using edge betweenness centrality as a weight can capture similar or even more effective information as sales share. Compared with simple sales share, the network centrality weight can better reflect the correlation and information transmission efficiency of the upstream and downstream of the supply chain, thereby more accurately measuring the impact of customer yield on the target company. This factor can capture the information transmission and sentiment contagion effects in the supply chain network, providing more robust and effective signals for quantitative investment.