Year: 2024
Type: article
Abstract: Purpose: This study examines the relationship between individual trading intensity and stock liquidity, assessing whether individual traders are informed or merely noise traders. We aim to understand individual trading's impact on liquidity in an emerging market setting without market makers.Study design/methodology/approach: We use a comprehensive dataset from intraday individual trading activity across all listed companies in Boursa Kuwait, employing regression models with industry and time fixed effects, different liquidity and probability of informed trading measures, and a Heckman two-stage selection model to control for self-selection bias.Sample and data: The sample includes all listed firms on Boursa Kuwait between January 2013 and December 2018.Results: We have found a significant negative relationship between individual trading intensity and stock liquidity, with higher individual trading associated with lower returns and a lower probability of informed trading (PIN). These findings suggest that individual traders often act as noise traders, increasing liquidity demand and causing price distortions.Originality/value: This study uniquely examines individual trading intensity in a market without market makers, removing the confounding effects of intermediary liquidity providers. Our findings, which reveal the direct impacts of individual trading on liquidity, enhance the literature on noise trading and market efficiency, especially in similar emerging markets.Research limitations/implications: The study is limited to the period before 2019, prior to the introduction of market makers in Boursa Kuwait. This provides a clean analysis but may not reflect the dynamics of mature markets with active market makers. The findings are crucial for stock exchanges focusing on liquidity enhancement programs.
Source: المجلة العربية للعلوم الإدارية.
Authors: Saad A. Alnahedh, Abdullah M. Al-Awadhi
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4405904478