The Exaggerated Effect Of Twitter On Investors' Biased Reactions To Company And Analyst Disclosures, And Mitigation Measures

The Exaggerated Effect Of Twitter On Investors' Biased Reactions To Company And Analyst Disclosures, And Mitigation Measures
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Book Synopsis The Exaggerated Effect Of Twitter On Investors' Biased Reactions To Company And Analyst Disclosures, And Mitigation Measures by : Yu Long

Download or read book The Exaggerated Effect Of Twitter On Investors' Biased Reactions To Company And Analyst Disclosures, And Mitigation Measures written by Yu Long and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation adopts two experiments to investigate how social media exacerbates investor biases in using disclosures from companies and financial analysts and then proposes mitigation mechanisms. My dissertation is motivated by two critical challenges in today's capital market: social media use and investor biases. Social media has considerably altered the information environment in the U.S. stock market. My dissertation concentrates on Twitter, one of the most popular social media platforms for financial information acquisition. In addition, examining investor biases is critical because these biases lead to biased resource allocation in the capital market and have an adverse impact on market participants' career prospects. In Essay One, I investigate the influence of Twitter on nonprofessional investors' biased judgment about a company's stock potential when the company strategically uses headlines in delivering its earnings news. I find that favorable corporate earnings news with a prominent headline positively affects investor judgments, and this headline effect is more significant in Twitter disclosures than in website disclosures. However, when there is a cautionary warning message on Twitter, the positive effect of headline prominence is weaker. In Essay Two, I investigate the impact of Twitter on nonprofessional investors' biased judgments based on the favorability of analyst names. I find that when an analyst forecast is disclosed on Twitter rather than the website, investors' judgments of the forecasted company are more positively influenced by the analyst's name favorability. However, revealing an analyst's reputation cue helps lessen the impact of their name on investors' investment potential assessments. Overall, the results of my two essays provide both research and practical implications.


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