Industry-wise Sentimental Herding: An Application of State-Space Model in Pakistan

Abstract

In recent decades, the worldwide consecutive catastrophes in the financial markets emphasize the accelerating prominence of investors’ sentiment on the financial market. Therefore, within academia, a shift from conventional finance to behavioral finance can be noticed and the most eminent topic of interest is the exploration of herding behavior. Inspired by the ongoing altercation on the magnitude and presence of herding in the stock markets, the present study aspires to explore the Pakistan stock market concerning herding behaviour. Investors’ industry-wise market-based herding behavior in the Pakistan stock market has been examined by employing daily data obtained from Bloomberg starting from January 2000 to April 2016. Cross-sectional variabilities in the factor sensitivities (Beta) have been employed to estimate investors' sentimental herding behavior, following the model of Hwang and Salmon (2004). The study found herding to be significant and persistent, independent from market fundamentals, like levels of market returns and volatility of returns. Findings also show that investors do herd considering the industrial classification of financial assets; hence it leads to mispricing of stocks. The study also presents industry differences in herding. Sugar and banking sectors are found to be more prone to herding while textile and manufacturing sectors are found less prone to herding. The results entail cogent implications for the investors pursuing diversification in the Pakistan stock market.