Restriction lift date: 2025-04-29
Insights from financial data - old and new
dc.availability.bitstream | embargoed | |
dc.check.date | 2025-04-29 | |
dc.contributor.advisor | Hutchinson, Mark | en |
dc.contributor.advisor | Mulcahy, Mark | en |
dc.contributor.author | Nguyen, Quang Minh Nhi | |
dc.contributor.funder | Vietnamese Government Scholarship | en |
dc.contributor.funder | UCC-Vied MoA | en |
dc.date.accessioned | 2020-05-25T09:55:41Z | |
dc.date.available | 2020-05-25T09:55:41Z | |
dc.date.issued | 2020 | |
dc.date.submitted | 2020 | |
dc.description.abstract | This thesis investigates financial data — the backbone of empirical research in finance — to provide insights into the importance of precisely interpreting existing data as well as the power of findings from new data. Specifically, the first study in this thesis examines the impact of event-day misspecification on the market reaction to FDA new drug approval announcements granted by NYSE listed firms. The second study uses an entirely new dataset of company filings from hedge fund management companies registered in the UK to investigate the true profitability of investment companies which manage hedge funds and to explain why it varies across firms over time. The last study utilizes the same new hedge fund manager filings dataset to investigate whether the hedge fund compensation contract effectively aligns managerial incentives with investor interests. Previous research has offered the attention-grabbing hypothesis as a behavioural explanation for abnormal returns in the day after FDA approval announcements. The first empirical study shows that when the precise timing of announcements is properly identified (i.e. existing data is precisely interpreted), the market reaction is centred on the event day and the increase in firm value is driven by after-market-close approval announcements. The second study shows that hedge fund management companies generated incredibly high profitability and revenue growth prior to 2008. With the onset of the global financial crisis, profitability and growth rates dropped. Analysis of cross-sectional variability in hedge fund management firm profitability finds that the key determinant is firm size. That is, larger firms generate significantly higher profitability and this relationship is particularly severe during the financial crisis period. Existing evidence shows that the standard hedge fund compensation contract incentivises the manager to grow the fund assets they manage, even if it deteriorates investment performance. Facilitated by the novel hedge fund dataset in this thesis, firms which are entirely focused on hedge fund management are distinguished from diversified firms (which generate a relatively small proportion of compensation from hedge funds). The third empirical chapter in this study confirms that the actual compensation of hedge fund only firms increases as fund assets grow, despite the increased cost and performance diseconomies of scale. This result also holds for diversified firms, even though there is a weaker alignment between managerial incentives and fund performance within these firms. Hedge funds managed by diversified firms have a markedly lower performance. | en |
dc.description.status | Not peer reviewed | en |
dc.description.version | Accepted Version | en |
dc.format.mimetype | application/pdf | en |
dc.identifier.citation | Nguyen, Q. M. N. 2020. Insights from financial data - old and new. PhD Thesis, University College Cork. | en |
dc.identifier.endpage | 206 | en |
dc.identifier.uri | https://hdl.handle.net/10468/10025 | |
dc.language.iso | en | en |
dc.publisher | University College Cork | en |
dc.rights | © 2020, Quang Minh Nhi Nguyen. | en |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | en |
dc.subject | Financial data | en |
dc.subject | Hedge funds | en |
dc.subject | Event study | en |
dc.subject | Private companies | en |
dc.title | Insights from financial data - old and new | en |
dc.type | Doctoral thesis | en |
dc.type.qualificationlevel | Doctoral | en |
dc.type.qualificationname | PhD - Doctor of Philosophy | en |
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