Abstract

Purpose – The main thrust of the present study is to look into the trading patterns of behavior and investment performance exhibited by individual and institutional investor categories in the Qatar Exchange (QE). The paper aims to discuss these issues. Design/methodology/approach – The present study uses daily aggregated investment flows made separately by each investor group, as well as daily closing price observations of the QE stock composite index. The trading patterns of investor categories are examined by estimating a bivariate vector autoregressive process of order p, VAR (p). To determine whether each category performs well or poorly over the entire sample period, each investor category's cumulative returns are estimated and analyzed. Findings – The empirical results reveal that institutional investors pursue positive feedback trading strategies, whereas individual investors tend to be negative feedback traders. Both investor categories appear to be engaged in herding behavior. Additionally, institutional investors perform well over almost the entire sample period. In contrast, individual investors' negative market timing ability dominates their overall poor performance. Practical implications – The investment performance gap found between institutional investors and individual investors in the Qatari capital market may reflect a large information asymmetry in favour of the former category. Indeed, the poor performance of individual investors implies that their trading activities are generally driven by factors and considerations that are irrelevant to fundamentals. Moreover, their irrational trading decisions may play some role in the formation of asset price bubbles. Originality/value – The present study makes the first attempt to provide empirical evidence on the investment patterns and performance of individual and institutional investors trading on the Qatari capital market.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call