Relationship between investor attention and stock returns through wavelet analysis

Purpose - The stock market plays a crucial role in driving economic growth and maintaining economic vibrancy. A key factor shaping the stock market’s dynamics is investor attention (IA). With the rapid growth of behavioral finance, which offers insights into investor behavior, choices and their impact, there is growing concern among scholars about the influence of IA on global stock markets. This underscores the importance of understanding the intricate relationship between IA and market fluctuations on a global scale. Design/methodology/approach - This study employs the Toda-Yamamoto Granger Causality test and Wavelet Analysis, to investigate the time-frequency varying causal relationships. The study analyzes closing price data for 26 Emerging Stock Markets from January 2004 to June 2022, with IA measured using Google search volume indices based on the highest intensity keywords sourced from Bloomberg, Wordstream and Google Trends. Findings - The study identifies numerous instances of strong co-movements between IA and stock returns, predominantly occurring over the medium to long term. This suggests that IA plays a significant role in shaping stock market performance, particularly in driving sustained trends that impact long-term returns. Originality/value - The originality of our study lies in its comprehensive analysis of the varying time–frequency relationships between IA and stock returns across 26 emerging markets, using a robust data set and precise measurement techniques. The results establish the predictive power of IA on market returns covering six different types of crisis, offering novel insights for investors and policymakers in emerging economies.