Sentiment-Driven Nonlinear Relationship Between Financial Market Emotion and Returns: Dynamic Adaptive Modeling Based on LLMs
Year: 2025
Type: conference-paper
Abstract: This study investigates the nonlinear relationship between investor sentiment and market returns in two Chinese financial markets, emphasizing asymmetric effects across bull and bear regimes. Via a fine-tuned Chinese RoBERTa model, we analyze over financial news texts everyday to generate sentiment scores. Two novel indices, the Momentum-Liquidity Index (MLI) and Price Stability Adjusted Equal-Weight Index (PSAEWI), capture short-term volatility and long-term trends. Empirical results, validated through VAR, quantile regression, and XGBoost, confirm sentiment's stronger predictive power in bull markets and its state-dependent interactions, and we further use them in prediction of macro-performance indicator. Also, we propose a real-time monitoring system and a dual-model framework integrates sentiment classification and emotion regression, dynamically weighted by market conditions. Finally, we offer practical applications for investors and regulators in behavioral finance.
Authors: Junyi Fang, Xiaojian Liu, Minshuai Zhou
Institution: Central South University
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: gold
OpenAlex ID: W4415073005