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Information Intermediaries and Financial Markets.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Information Intermediaries and Financial Markets./
作者:	Wang, Wei.
面頁冊數:	1 online resource (146 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-12, Section: A.
Contained By:	Dissertations Abstracts International84-12A.
標題:	Finance. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30524528click for full text (PQDT)
ISBN:	9798379705107

Information Intermediaries and Financial Markets.
Wang, Wei.

Information Intermediaries and Financial Markets. - 1 online resource (146 pages)

Source: Dissertations Abstracts International, Volume: 84-12, Section: A.

Thesis (Ph.D.)--Indiana University, 2023.

Includes bibliographical references

Information technology greatly facilitates investors' access to information. Its impact on the financial markets depends on (1) how the information is produced (producer side); (2) how investors interpret the information (consumer side). The three chapters investigate the impact of information production on the financial market from these two angles.Chapter 1 studies asset prices and portfolio choices in an exchange economy with an information market. Two providers decide the information quality and price and compete for investors. I demonstrate that when investors are heterogeneous in the costs of using information, an equilibrium exists where ex-ante homogeneous information producers differentiate from ex-post. This equilibrium is not socially optimal. The information quality gap and disagreement are higher in the market equilibrium than in the social optimum. However, the equity return volatility is not necessarily higher. The impacts on stock prices are asymmetric when the information quality gap enlarges. Although disagreement increases in both cases, the equity return volatility is lower when low-quality information deteriorates. When high-quality information improves, the equity return volatility is higher.Chapter 2 investigates the effects of bot-generated tweets on stock prices and the economic mechanism. Using a Twitter-bot detector developed by Observatory on Social Media (OSoMe), BotometerLite, we find that the bot score has predictability about future returns. The predictability lasts for one day and then fades away. The predictability gets reverted in three days, indicating that this predictability is a result of investors' overreaction. The impulse response functions show that human-generated tweet numbers react stronger to bot-generated tweet numbers than bots' reactions to human activity. Cross-sectional analysis shows that small firms have more salient predictability, consistent with the limit of arbitrage.Chapter 3 quantifies the size of uninformed investors by measuring market overreaction. Using texts in 10-Ks of SP500 constituents, I conduct a topical decomposition of managerial tones and find that market reaction is more sensitive to informative topics' tones. A structural estimation shows that uninformed investors account for only 1.06%, pushing the excess return by 0.03 basis points. Overall, investors are selective in processing public information, and market overreaction to managerial tones is insignificant.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798379705107Subjects--Topical Terms:

542899
Finance.
Subjects--Index Terms:

Exchange economyIndex Terms--Genre/Form:

542853
Electronic books.

Information Intermediaries and Financial Markets.
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