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Measuring the Impact of Recurring Events on Financial Assets : 반복적인 사건이 금융자산에 미치는 영향 측정
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | 이영섭 | - |
dc.contributor.author | Edward Keunuk SHIN | - |
dc.date.accessioned | 2021-11-30T06:09:15Z | - |
dc.date.available | 2021-11-30T06:09:15Z | - |
dc.date.issued | 2021-02 | - |
dc.identifier.other | 000000166259 | - |
dc.identifier.uri | https://hdl.handle.net/10371/176405 | - |
dc.identifier.uri | https://dcollection.snu.ac.kr/common/orgView/000000166259 | ko_KR |
dc.description | 학위논문 (석사) -- 서울대학교 대학원 : 국제대학원 국제학과(국제통상전공), 2021. 2. 이영섭. | - |
dc.description.abstract | I documented the impact of recurring events on financial assets using a new event study methodology. The new methodology follows the overall structure of a typical event study, but it also objectively identifies a unique duration of each event to be used for cumulative average abnormal return. Moreover, 2 simple criteria are proposed to objectively detect the direction of price movement. To conduct an event study with the new methodology, I developed an algorithm that has 2 user-defined variables according to the needs of the user. The algorithm measures the impact before, during, and after an event, and conducts significance tests at 90%, 95%, and 99% level. Market indices, stocks, and ETFs were evaluated from 2009 to 2019. The algorithm performed better for unexpected events than it did for expected events. I exposed shortcomings of the methodology and the algorithm, and provided directions for further research. | - |
dc.description.tableofcontents | Chapter 1. Introduction 1
1.1 Motivation 1 1.2 Background 4 1.2.1 Traditional approach 5 Chapter 2. Data 7 2.1 Study Period 7 2.2 Financial Data 7 2.2.1 Exchange Traded Fund (ETF) 10 2.3 Recurring Events 11 2.4 Recurring Event - Financial Asset Pairs 12 Chapter 3. Methodology 14 3.1 Moving Average 17 3.1.1 Simple moving average 18 3.1.2 Weighted moving average 18 3.1.3 Exponentially weighted moving average 19 3.2 Temporal Data Pre-processing 20 3.2.1 Removing data 1 year beyond the event date 20 3.2.2 Matching event date with trading date to set t=0 21 3.2.3 Data range for analysis of each event 21 3.3 Returns 23 3.3.1 Relative to 0% 23 3.3.2 Relative to R 23 3.3.3 Relative to day-of-the-week 25 3.4 Direction 26 3.4.1 Sign criteria 26 3.4.2 Standard deviation criteria 27 3.5 Cumulative Average Return 29 3.5.1 During an event 29 3.5.2 Before and after an event 32 3.5.3 Cumulative average return of a recurring event 33 3.5.4 Significance test 33 Chapter 4. Results and Discussions 35 4.1 Expected Events 35 4.1.1 Public holidays 35 4.1.2 iPhone release 37 4.2 Unexpected Events 39 4.2.1 North Korea military weapons test 39 4.2.2 Airplane crash 42 Chapter 5. Extension 44 5.1 Robustness 44 5.1.1 BAE 44 5.1.2 LOR 45 5.1.3 Random sampling 45 5.2 Limitations 46 5.3 Further Research 47 Chapter 6. Conclusion 50 Bibliography 55 Appendix A 64 Appendix B 67 Appendix C 69 | - |
dc.format.extent | iii, 99 | - |
dc.language.iso | eng | - |
dc.publisher | 서울대학교 대학원 | - |
dc.subject | Event Study | - |
dc.subject | Research Methodology | - |
dc.subject | Event Duration | - |
dc.subject | Event Direction | - |
dc.subject | Cumulative Average Abnormal Return | - |
dc.subject.ddc | 382.9 | - |
dc.title | Measuring the Impact of Recurring Events on Financial Assets | - |
dc.title.alternative | 반복적인 사건이 금융자산에 미치는 영향 측정 | - |
dc.type | Thesis | - |
dc.type | Dissertation | - |
dc.contributor.AlternativeAuthor | 신에드워드근욱 | - |
dc.contributor.department | 국제대학원 국제학과(국제통상전공) | - |
dc.description.degree | Master | - |
dc.date.awarded | 2021-02 | - |
dc.identifier.uci | I804:11032-000000166259 | - |
dc.identifier.holdings | 000000000044▲000000000050▲000000166259▲ | - |
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