Research on the Construction of Financial Market Sentiment Index and Its Predictive Power for Asset Prices

Fluctuations in financial markets are not only influenced by fundamental factors, but investor sentiment also plays an increasingly important role. Accurately capturing and quantifying market sentiment is of great significance for understanding asset price dynamics. This study is dedicated to exploring the theoretical basis for constructing a comprehensive financial market sentiment index and evaluating its potential impact on asset price prediction. The research first reviews the theoretical developments of investor sentiment in behavioral finance, analyzing how emotional factors influence investment decisions and market dynamics. On this basis, the study proposes a multi-dimensional sentiment indicator framework, including aspects such as social media sentiment, news reporting tendencies, and trading behavior characteristics. Through theoretical analysis, the research discusses how these indicators comprehensively reflect the overall sentiment state of the market. The study also examines the sensitivity differences of various asset classes (such as stocks, bonds, foreign exchange) to sentiment factors, and the potential reasons for these differences. Furthermore, the research discusses the potential non-linear relationships and feedback mechanisms between market sentiment and asset prices. Through theoretical derivation, the study proposes hypotheses about the explanatory power and predictive potential of sentiment indices for short-term price fluctuations. However, the research also points out the theoretical challenges faced in quantifying sentiment impacts, such as the complexity of sentiment transmission mechanisms and the heterogeneity of market participants. This study not only deepens the theoretical understanding of investor behavior and market microstructure but also provides a theoretical framework for future empirical research and index construction.