The Relationship Between Investor Attention and the BIST 100: An Empirical Analysis via Google Trends Data
DOI:
https://doi.org/10.63556/tisej.2026.1888Keywords:
Behavioral Finance, Investor Attention, Google Trends, BIST 100, Toda-Yamamoto CausalityAbstract
Traditional approaches to the functioning of financial markets are shaped within the framework of the Efficient Market Hypothesis, which posits that information is fully and instantaneously reflected in prices. However, modern financial literature suggests that investors cannot process all information perfectly due to limited cognitive capacities; at this point, "investor attention" emerges as a scarce economic resource that determines market dynamics. This study aims to empirically examine the dynamic interaction between investor interest and the trading volume of the BIST 100, Turkey's benchmark index, within a digitalized information ecosystem. The research utilizes monthly data covering the period from June 2013 to March 2026, where investor interest is represented by an index derived from Google Search Trends and market activity is represented by total trading volume. The direction and significance of the relationship between the variables were analyzed using the Toda-Yamamoto causality test, which offers a robust framework against differences in the integration levels of the series. The analysis findings indicate the existence of a bi-directional causal relationship between investor interest and trading volume. These results empirically support the attention-based theories of behavioral finance, demonstrating that the information search process in digital media triggers transaction density in the market, while simultaneously, increased market volatility fuels the process by creating a new wave of investor interest. The study suggests that digital indicators such as Google Trends can be utilized as an early warning mechanism for predicting market fluctuations, offering strategic implications for policymakers and investors alike.
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