Predictive power of web search behavior in five ASEAN stock markets

This paper investigates the predictive ability of web search behavior in connection with stock market returns and trading volume in five emerging economies in the ASEAN region using econometric and signal-processing techniques. More specifically, we use Vector Error Correction Model in conjunction with Wavelet analysis and find consistently low predictive ability of search activity in Google. In fact, investors in nearly all five markets appear to be interested in searching terms related to the market after high returns or high trading activities occur. In other words, high returns or high activities precede search interest. Our findings are at odds with the general results reported in earlier studies conducted in developed countries. Additionally, our analysis in the time-frequency domain detects a two-week lead-lag phenomenon in the association between search behavior and market returns for all markets but the Philippines.