From noise to signals: Investor attention as a catalyst for the momentum effect in the Chinese stock market

Zhi-Yu Zhang, Chi Xie, Gang-Jin Wang, You Zhu and Xiao-Xin Li

Global Finance Journal, 2025, vol. 67, issue C

Abstract: The momentum effect is a pricing anomaly that is widely observed in financial markets but not promised in the Chinese stock market. We explore the interaction between investor attention and momentum effects to strengthen momentum-based strategies' profitability by transforming the inherent noise of investor attention into valuable signals. Applying the conditional autoencoder (CAE) asset pricing model, we extract signals from noisy information to estimate stock returns that reflect the expected price adjustments driven by collective attention. Results yield four key conclusions. (i) The signal derived from investor attention acts as a catalyst that significantly enhances momentum strategies' performance, and the attention-based momentum (AttMOM) strategy consistently outperforms the conventional momentum (MOM) strategy in various formation periods. (ii) Although pricing anomalies, such as firm size, influence both strategies' returns, the attention-driven signal enables AttMOM to achieve higher and more stable returns. (iii) Investor attention helps AttMOM to maintain stable profits during market downturns. (iv) Investor attention reinforces the AttMOM strategy's resilience during turbulence, improving its hedging capabilities. Overall, our findings highlight the pivotal role of investor attention in boosting momentum returns, offering valuable insights for investment decision-making.

Keywords: Behavioral finance; Investor attention; Momentum effect; Asset pricing; Autoencoder; Stock market (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:glofin:v:67:y:2025:i:c:s1044028325001024

DOI: 10.1016/j.gfj.2025.101175

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