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Structures and Randomness in Stock Markets : 주식시장 내부에 있는 구조들과 무작위성 분석
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | Otto van Koert | - |
| dc.contributor.author | 서재현 | - |
| dc.date.accessioned | 2022-04-20T07:53:56Z | - |
| dc.date.available | 2022-04-20T07:53:56Z | - |
| dc.date.issued | 2021 | - |
| dc.identifier.other | 000000166541 | - |
| dc.identifier.uri | https://hdl.handle.net/10371/178986 | - |
| dc.identifier.uri | https://dcollection.snu.ac.kr/common/orgView/000000166541 | ko_KR |
| dc.description | 학위논문(석사) -- 서울대학교대학원 : 자연과학대학 수리과학부, 2021.8. Otto van Koert. | - |
| dc.description.abstract | 이 논문에서는 주식 시장 분석에 있어서 이론적 방법과 데이터 분석 방법을 사용한
다. 실제 시장이 무작위하게 움직이는지에 대한 질문을 던지며 논문을 시작한다. Mapper와 Autoencoder를 이용하여 주식시장의 구조를 비교해본다. | - |
| dc.description.abstract | In this paper, we give a theoretical approach and an approach with
data analysis for stock market. We start with a direct question which is Do the stock market always follow the random walk?. Then we will see structures of time series in stock market by comparing mapper with autoencoder. | - |
| dc.description.tableofcontents | 1 Test of Randomness 4
1.1 Preliminaries 4 1.2 Theoretical Approach for Stochastic Process 5 1.3 Wiener Process 5 1.4 Kolmogorov-Smirnov Test 7 1.5 Shapiro-Wilk Test 8 1.6 Validation for test of randomness 10 1.7 Check the Seasonality 10 2 SARIMA Model 11 2.1 Preliminaries 11 2.2 Autoregressive(AR) 12 2.3 Moving Average(MA) 12 2.4 Autoregressive Integrated Moving Average(ARIMA) 13 2.5 Seasonal Autoregressive Integrated Moving Average(SARIMA) 13 2.6 Forecast the Stock price 14 2.7 Summary 15 3 Events in Randomness 16 3.1 Preliminaries 16 3.2 Poisson Process with jump diffusion 17 3.3 Poisson Distribution 20 3.4 Distribution of Traded Price 21 3.5 Conclusion 23 4 Classify Time Series 24 4.1 Preliminaries 24 4.2 Hellinger distance 25 4.3 Mapper 27 4.4 Autoencoder 28 4.5 Visualization 29 | - |
| dc.format.extent | ii, 32 | - |
| dc.language.iso | eng | - |
| dc.publisher | 서울대학교 대학원 | - |
| dc.subject | time series | - |
| dc.subject | machine learning | - |
| dc.subject | stochastic process | - |
| dc.subject | stock market | - |
| dc.subject | randomess | - |
| dc.subject.ddc | 510 | - |
| dc.title | Structures and Randomness in Stock Markets | - |
| dc.title.alternative | 주식시장 내부에 있는 구조들과 무작위성 분석 | - |
| dc.type | Thesis | - |
| dc.type | Dissertation | - |
| dc.contributor.AlternativeAuthor | Seo Jae Hyun | - |
| dc.contributor.department | 자연과학대학 수리과학부 | - |
| dc.description.degree | 석사 | - |
| dc.date.awarded | 2021-08 | - |
| dc.identifier.uci | I804:11032-000000166541 | - |
| dc.identifier.holdings | 000000000046▲000000000053▲000000166541▲ | - |
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