Measuring the effect of investor sentiment on liquidity

Dunham, Lee M.; García, John

doi:10.1108/mf-06-2019-0265

Cited by 16 publications

(16 citation statements)

References 82 publications

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“…Bid–ask spread is widely used to measure the transaction costs associated with the trade. Heflin, Shaw, and Wild ( 2005 ) and Goyenko, Holden, and Trzcinka ( 2009 ) find that two liquidity proxies (the quoted sand the effective spreads) are perceived as being the most accurate measures for liquidity consistent with several studies (such as Chebbi et al, 2021 ; Dunham & Garcia, 2020 ; Mdaghri et al, 2020 ), we measure stock liquidity by utilising the quoted spread (Chung & Zhang, 2014 ) for every firm on a given trading day. It is computed by utilising the daily bid–ask spreads as a proportion of the mid‐price for each firm on a given trading day.…”

Section: Methodology and Datasupporting

confidence: 62%

Impact of government policy responses of COVID‐19 pandemic on stock market liquidity for Australian companies

Kassamany

Zgheib

2022

Australian Economic Papers

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This study investigates the impact of government policy responses of COVID‐19 pandemic on stock market liquidity for listed Australian companies and for 11 different industries separately. A quantitative deductive approach is used for a sample of 1,452 companies with a total of 292,164 firm‐day observations over a period from January 25, 2020 to December 31, 2020 during the outbreak of COVID‐19. Univariate and multivariate (two‐way cluster‐robust panel regression) analysis were conducted. Data were collected from the Oxford COVID‐19 Government Response Tracker, Worldmeter, Refinitiv Workspace and Datastream. Our findings indicate that the influences of the six out of seven stringency policy responses reduced Australian equity market liquidity. However, public information campaigns enhanced market liquidity and hence trading activity. Among the 11 industries, our analysis shows that the non‐pharmaceutical interventions by the Australian government have significant and positive effects on four industries: Consumer non‐cyclicals, healthcare, financial and technology. However, the worse effects were depicted in the industrial (transportation) and energy industries. This study is important for investors, policymakers and regulators to understand the diverse effects of government policy responses of COVID‐19 on stock market liquidity to enhance financial stability. Moreover, understanding this effect is particularly important to decision‐makers such as portfolio and fund managers to manage their portfolios and trading activities during extreme turbulence times, such as COVID‐19. Unlike previous studies that focus on country analysis, this study examines on firm basis the impact of government interventions on stock market liquidity in a well developed Australian stock market.

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Section: Methodology and Datasupporting

confidence: 62%

Impact of government policy responses of COVID‐19 pandemic on stock market liquidity for Australian companies

Kassamany

Zgheib

2022

Australian Economic Papers

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“…23. Dunham and Garcia (2021) The purpose of this paper is to examine the effect of firm-level investor sentiment on a firm's share liquidity. 24.…”

Section: Jain Al (2019)mentioning

confidence: 99%

Mapping Investment Decision Studies: A Bibliometric Review

Wellfren¹,

Lajuni²

2022

IJARBSS

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The significance of investment decisions has increased the field's value among, particularly for investors and researchers. In this study, our review attempts to map trends and development of investment decision studies in the past, present and potential new knowledge or significant gaps in the literature for future references by utilizing bibliometric analysis. This study investigated a total of 3,894 papers retrieved from the Scopus database between 1990 and August 2021. The mapping revealed an upward trend of publications and is expected to continue in the next few years. Simultaneously, analysis based on Harzing's Publish and Perish and VOSviewer has demonstrated the significant increase of investment decisions studies as a result of emerging themes, mostly driven by technology advancement and social movement. Financial reporting and environmental, social, and governance (ESG) issues have been increasingly popular among researchers in recent years. Our mapping exposes the popularity of this topic among past, current and future researchers. As a result, this study's main value is the expansion of knowledge in investment decisions and as foundation for future academic reference. Stakeholders such as policymakers, industry players including scholars should explore potential areas in investment decision studies that will benefit the public as a whole.

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“…Chen et al, 2014), share price volatility (e.g. Bollen et al, 2011), share liquidity (Dunham and Garcia, 2021), delisting probability (Gandhi et al, 2019;Mayew et al, 2015) and analyst herding behavior (Garcia, 2021). However, little is known about the effect of social media sentiment on financial distress.…”

Section: Related Literature and Hypothesis Developmentmentioning

confidence: 99%

Measuring the effect of investor sentiment on financial distress

Dunham

García

2021

Self Cite

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PurposeThis study examines the effect of firm-level investor sentiment on a firm's level of financial distress.Design/methodology/approachThe authors use Bloomberg's firm-level, daily investor sentiment scores derived from firm-level news and Twitter content in a beta-regression model to explain the variability in a firm's financial distress.FindingsThe results indicate that improvements (deterioration) in investor sentiment derived from both news articles and Twitter content lead to a decrease (increase) in the average firm's financial distress level. We also find that the effect of sentiment derived from Twitter on a firm's financial distress is significantly stronger than the sentiment derived from news articles.Research limitations/implicationsOur proxy for financial distress is Bloomberg's financial distress measures, which may be an imperfect measure of financial distress. Our results have important implications for market participants in assessing the determinants of financial distress.Practical implicationsOur sample period covers four years (2015–2019), which is determined by Bloomberg sentiment data availability.Social implicationsMarket participants are increasingly using social media to express views on firms and seek information that might be used to determine a firm's level of financial distress. Our study links investor sentiment derived from social media (Twitter) and traditional news articles to financial distress.Originality/valueBy examining the relationship between a firm's sentiment and its financial distress, this paper advances our understanding of the factors that drive a firm's financial distress. To our knowledge, this is the first study to link US firms' investor sentiment derived from firm-level news and Twitter content to a firm's financial distress.

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Measuring the effect of investor sentiment on liquidity

Cited by 16 publications

References 82 publications

Impact of government policy responses of COVID‐19 pandemic on stock market liquidity for Australian companies

Impact of government policy responses of COVID‐19 pandemic on stock market liquidity for Australian companies

Mapping Investment Decision Studies: A Bibliometric Review

Measuring the effect of investor sentiment on financial distress

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