Correlating Investor Sentiments and Saudi Stock Market Behaviour: A Wavelet-Based Approach

Background: Investor sentiment has long been recognized as a key behavioural factor influencing financial markets, particularly in emerging economies where information asymmetry and speculative behaviour can play significant roles. In the case of Saudi Arabia, the largest stock market in the Middle East, understanding the role of investor sentiment is essential given the country’s rapid economic transformation under Vision 2030 and its increasing integration with global financial markets. Objectives: This study aims to investigate the impact of investor sentiments on the behaviour of the Saudi stock market over the period 2005–2021. Methods/approach: To capture investor mood, we construct sentiment indexes derived from Big Data, specifically Google Search Volume (GSV), which allows us to distinguish between positive and negative sentiment. Methodologically, we employ wavelet coherence analysis and spectral causality tests to examine both the time–frequency dynamics and the directional relationship between investor sentiment and market performance. Results: The findings reveal that positive and negative sentiments exhibit significant variations across time, investment horizons, and industrial sectors. Importantly, the effects of sentiment on stock returns and volatility are asymmetric, with negative sentiment exerting a stronger and more persistent influence. Sectoral analysis further indicates that financial, banking, and insurance industries are the most sensitive to investor sentiment, highlighting their vulnerability to behavioral factors. Conclusion/policy implications: These results provide valuable insights for market participants, who can integrate sentiment indicators into their asset allocation and hedging strategies. Policymakers should consider investor sentiment as a crucial determinant when formulating financial regulations.