PCA-Based Investor Attention Index and Its Impact on the KSE-100 Excess Returns

First, using the principal component analysis (PCA) approach, we construct an investor attention index from seven variables: abnormal trading volume, extreme returns, past returns, nearness to the 52-week high, nearness to the historical high, Google search volume, and mutual fund inflows. Second, this study examines the impact of the investor attention index on the KSE-100 index excess returns. For this purpose, we collect monthly data from January 2004 to December 2024. The PCA identified four components and constructed attention indices: has highest weights of nearness to the 52-week high, abnormal trading volume, past returns, and mutual funds inflows; has major weights of abnormal trading volume, extreme returns, past returns, and Google search volume; has nearness to the 52-week high, nearness to the historical high, extreme returns, and mutual funds inflows and has nearness to the historical high, extreme returns, Google search volume, and mutual funds inflows. The , and have a positive and significant impact on the excess returns of the KSE-100 index. This suggests that when investors are more motivated to invest, herding behavior increases, leading to improved index performance and higher returns. Subsequently, has a negative but significant impact on index returns, indicating that a lack of investor interest leads to reduced trading activity and weaker index performance. The findings of this study have important implications for policymakers, investors, and mutual fund managers to understand the patterns of investor attention, creating policies and procedures to make the financial markets more transparent and protect the investor’s rights.