Classifying Factor Velocity with Swarm Intelligence: Market Pricing of Fast- and Slow-Moving Factors
Year: 2025
Type: article
Abstract: Utilizing a dataset of 190 risk factors spanning over three decades, we apply a swarm-based classification model to estimate factor velocity and analyze its implications for asset pricing. Our results show that slower-moving factors generate higher abnormal returns than their faster-moving counterparts, underscoring the critical role of price adjustment speed in market dynamics. Furthermore, our results suggest that trading frictions impede the rapid assimilation of information, contributing to the observed return patterns. This research offers new insights into return predictability and demonstrates the potential of swarm intelligence as a powerful tool for financial modeling.
Source: Algorithms
DOI: 10.3390/a18110682
Authors: Ren-Raw Chen, Mengjie Huang, Yi Tang
Institutions: Fordham University, Caldwell University
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,930
OpenAlex ID: W4415649801