[논문]Detecting and Analyzing Politically-Themed Stocks Using Text Mining Techniques and Transfer Entropy—Focus on the Republic of Korea’s Case

Choi, Insu; Kim, Woo Chang

doi:10.3390/e23060734

[해외논문] Detecting and Analyzing Politically-Themed Stocks Using Text Mining Techniques and Transfer Entropy—Focus on the Republic of Korea’s Case 원문보기

Entropy, v.23 no.6, 2021년, pp.734 -

Choi, Insu , Kim, Woo Chang

Abstract ▼ AI-Helper

Politically-themed stocks mainly refer to stocks that benefit from the policies of politicians. This study gave the empirical analysis of the politically-themed stocks in the Republic of Korea and constructed politically-themed stock networks based on the Republic of Korea’s politically-themed stocks, derived mainly from politicians. To select politically-themed stocks, we calculated the daily politician sentiment index (PSI), which means politicians’ daily reputation using politicians’ search volume data and sentiment analysis results from politician-related text data. Additionally, we selected politically-themed stock candidates from politician-related search volume data. To measure causal relationships, we adopted entropy-based measures. We determined politically-themed stocks based on causal relationships from the rates of change of the PSI to their abnormal returns. To illustrate causal relationships between politically-themed stocks, we constructed politically-themed stock networks based on causal relationships using entropy-based approaches. Moreover, we experimented using politically-themed stocks in real-world situations from the schematized networks, focusing on politically-themed stock networks’ dynamic changes. We verified that the investment strategy using the PSI and politically-themed stocks that we selected could benchmark the main stock market indices such as the KOSPI and KOSDAQ around political events.

Keyword

참고문헌 (63)

1. Herron M.C. Lavin J. Cram D. Silver J. Measurement of Political Effects in the United States Economy: A Study of the 1992 Presidential Election Econ. Polit. 1999 11 51 81 10.1111/1468-0343.00053

상세보기
2. Knight B. Are Policy Platforms Capitalized into Equity Prices? Evidence from the Bush/Gore 2000 Presidential Election J. Public Econ. 2006 90 751 773 10.1016/j.jpubeco.2005.06.003

상세보기
3. Levy T. Yagil J. The 2012 US Presidential Election Polls and Stock Returns J. Bus. Econ. Res. 2015 5 66 74 10.5296/ber.v5i2.8005
4. Gobran P. Bacon F. Presidential Elections and Industry Stock Returns: A Test of Market Efficiency Int. J. Bus. Behav. Sci. 2017 29 21 31
5. Wagner A.F. Zeckhauser R.J. Ziegler A. Company Stock Price Reactions to the 2016 Election Shock: Trump, Taxes, and Trade J. Financ. Econ. 2018 130 428 451 10.1016/j.jfineco.2018.06.013

상세보기
6. Financial Services Commission Results of Countermeasure against Politically-Themed Stocks of 19th Presidential Election Press Release in the Republic of Korea Seoul, Korea 2017
7. Financial Supervisory Service Survey on Unfair Trade in Politically-Themeds of the 19th Presidential Election Press Release in the Republic of Korea Seoul, Korea 2017
8. Nam G. Politically-Themed Stocks: Characteristics and Investment Risks KCMI Issue Rep. 2017 4 1 13
9. Kwak H.S. Yeo E.J. An Event Study on the Politically-Themed Stocks on the 19th Presidential Election in Korea Korean J. Financ. Manag. 2019 36 209 245
10. Hughes H. Crony capitalism and the East Asian currency and financial ‘crises’ J. Public Policy Ideas 1999 15 3 9
11. Kim B.K. Im H.B. ‘Crony Capitalism’ in South Korea, Thailand and Taiwan: Myth and Reality J. East Asian Stud. 2001 1 5 52 10.1017/S1598240800000230

상세보기
12. Kang D.C. Crony Capitalism: Corruption and Development in South Korea and the Philippines Cambridge University Press Cambridge, UK 2002
13. Kang D.C. Transaction costs and crony capitalism in East Asia Comp. Political Stud. 2003 35 439 458 10.2307/4150189

상세보기
14. Brown S.J. Warner J.B. Using Daily Stock Returns: The Case of Event Studies J. Financ. Econ. 1985 14 3 31 10.1016/0304-405X(85)90042-X

상세보기
15. Armitage S. Event study methods and evidence on their performance J. Econ. Surv. 1995 9 25 52 10.1111/j.1467-6419.1995.tb00109.x

상세보기
16. Hochreiter S. Schmidhuber J. LSTM Can Solve Hard Long Time Lag Problems Adv. Neural. Inform. Process. Syst. 1997 473 479
17. Schuster M. Paliwal K.K. Bidirectional Recurrent Neural Networks IEEE Trans. Signal Process. 1997 45 2673 2681 10.1109/78.650093

상세보기
18. Graves A. Schmidhuber J. Framewise Phoneme Classification with Bidirectional LSTM and Other Neural Network Architectures Neural Netw. 2005 18 602 610 10.1016/j.neunet.2005.06.042 16112549

상세보기
19. Park S.M. Na C.W. Choi M.S. Lee D.H. On B.W. KNU Korean Sentiment Lexicon: Bi-LSTM-Based Method for Building a Korean Sentiment Lexicon J. Intell. Inf. Syst. 2018 24 219 240
20. Song M. Park H. Shin K.S. Attention-Based Long Short-Term Memory Network Using Sentiment Lexicon Embedding for Aspect-Level Sentiment Analysis in Korean Inf. Process. Manag. 2019 56 637 653 10.1016/j.ipm.2018.12.005

상세보기
21. Granger C.W. Investigating Causal Relations by Econometric Models and Cross-Spectral Methods Econom. J. Econ. Soc. 1969 37 424 438 10.2307/1912791

상세보기
22. Quigley L. Statistical Analysis of the Log Returns of Financial Assets Master’s thesis. Master’s Thesis University of Limerick Limerick, Ireland 2008
23. Sheikh A.Z. Qiao H. Non-normality of Market Returns: A Framework for Asset Allocation Decision Making J. Alter. Investig. 2009 12 8 35 10.3905/JAI.2010.12.3.008

상세보기
24. Tsai C.S.-Y. The Real World Is Not Normal Morningstar Alternative Investments Observer Chicago, IL, USA 2011
25. Schinckus C. Is Econophysics a New Discipline? The Neopositivist Argument Phys. A Stat. Mech. Appl. 2010 389 3814 3821 10.1016/j.physa.2010.05.016

상세보기
26. Jovanovic F. Schinckus C. The Emergence of Econophysics: A New Approach in Modern Financial Theory Hist. Polit. Econ. 2013 45 443 474 10.1215/00182702-2334758

상세보기
27. Schreiber T. Measuring Information Transfer Phys. Rev. Lett. 2000 85 461 10.1103/PhysRevLett.85.461 10991308

상세보기
28. Bossomaier T. Barnett L. Harré M. Lizier J.T. An Introduction to Transfer Entropy Springer Berlin/Heidelberg, Germany 2016
29. Marschinski R. Kantz H. Analysing the Information Flow between Financial Time-series Eur. Phys. J. B 2002 30 275 281 10.1140/epjb/e2002-00379-2

상세보기
30. Kwon O. Yang J.S. Information Flow between Composite Stock Index and Individual Stocks Phys. A Stat. Mech. Appl. 2008 387 2851 2856 10.1016/j.physa.2008.01.007

상세보기
31. Dimpfl T. Peter F.J. Using Transfer Entropy to Measure Information Flows Between Financial Markets Stud. Nonlinear Dyn. Econom. 2013 17 85 102 10.1515/snde-2012-0044

상세보기
32. Sandoval L. Structure of a Global Network of Financial Companies Based on Transfer Entropy Entropy 2014 16 4443 4482 10.3390/e16084443

상세보기
33. Sensoy A. Sobaci C. Sensoy S. Alali F. Effective Transfer Entropy Approach to Information Flow between Exchange Rates and Stock Markets Chaos Solitons Fractals 2014 68 180 185 10.1016/j.chaos.2014.08.007

상세보기
34. Bekiros S. Nguyen D.K. Junior L.S. Uddin G.S. Information Diffusion, Cluster Formation and Entropy-Based Network Dynamics in Equity and Commodity Markets Eur. J. Oper. Res. 2017 256 945 961 10.1016/j.ejor.2016.06.052

상세보기
35. Lim K. Kim S. Kim S.Y. Information Transfer across Intra/Inter-Structure of CDS and Stock Markets Phys. A 2017 486 118 126 10.1016/j.physa.2017.05.084

상세보기
36. Jang S.M. Yi E. Kim W.C. Ahn K. Information Flow between Bitcoin and Other Investment Assets Entropy 2019 21 1116 10.3390/e21111116

상세보기
37. Yue P. Cai Q. Yan W. Zhou W.X. Information Flow Networks of Chinese Stock Market Sectors IEEE Access 2020 8 13066 13077 10.1109/ACCESS.2020.2966278

상세보기
38. Yue P. Fan Y. Batten J.A. Zhou W.X. Information Transfer between Stock Market Sectors: A Comparison between the USA and China Entropy 2020 22 194 10.3390/e22020194 33285969

상세보기
39. Doane D.P. Aesthetic Frequency Classifications Am. Stat. 1976 30 181 183

상세보기
40. Freedman D. Diaconis P. On the Histogram as a Density Estimator: L 2 Theory Z. Wahrscheinlichkeitstheor. Verw. Geb. 1981 57 453 476 10.1007/BF01025868

상세보기
41. Allen F. Babus A. Networks in Finance The Network Challenge: Strategy, Profit, and Risk in an Interlinked World 1st ed. Kleindorfer P.R. Wind Y. Gunther R.E. FT Press Upper Saddle River, NJ, USA 2009 367
42. Beije P.R. Groenewegen J. A Network Analysis of Markets J. Econ. Issues 1992 26 87 114 10.1080/00213624.1992.11505263

상세보기
43. Namaki A. Shirazi A.H. Raei R. Jafari G.R. Network Analysis of a Financial Market Based on Genuine Correlation and Threshold Method Phys. A Stat. Mech. Appl. 2011 390 3835 3841 10.1016/j.physa.2011.06.033

상세보기
44. Huang W.Q. Zhuang X.T. Yao S. A Network Analysis of the Chinese Stock Market Phys. A Stat. Mech. Appl. 2009 388 2956 2964 10.1016/j.physa.2009.03.028

상세보기
45. Roy R.B. Sarkar U.K. Identifying Influential Stock Indices from Global Stock Markets: A Social Network Analysis Approach Procedia Comput. Sci. 2011 5 442 449 10.1016/j.procs.2011.07.057

상세보기
46. Liao H. Mariani M.S. Medo M. Zhang Y.C. Zhou M.Y. Ranking in Evolving Complex Networks Phys. Rep. 2017 689 1 54 10.1016/j.physrep.2017.05.001

상세보기
47. Page L. Brin S. Motwani R. Winograd T. The PageRank Citation Ranking: Bringing Order to the Web Stanford Infolab, Stanford University Stanford, CA, USA 1999
48. Kuzuba T.U. Ömercikolu I. Saltolu B. Network Centrality Measures and Systemic Risk: An Application to the Turkish Financial Crisis Phys. A Stat. Mech. Appl. 2014 405 203 215 10.1016/j.physa.2014.03.006

상세보기
49. Yun T.S. Jeong D. Park S. “Too Central to Fail” Systemic Risk Measure Using PageRank Algorithm J. Econ. Behav. Organ. 2019 162 251 272 10.1016/j.jebo.2018.12.021

상세보기
50. Tu C. Cointegration-Based Financial Networks Study in Chinese Stock Market Phys. A Stat. Mech. Appl. 2014 402 245 254 10.1016/j.physa.2014.01.071

상세보기
51. Tang Y. Xiong J.J. Luo Y. Zhang Y.C. How Do the Global Stock Markets Influence One Another? Evidence from Finance Big Data and Granger Causality Directed Network Int. J. Electron. Commer. 2019 23 85 109 10.1080/10864415.2018.1512283

상세보기
52. Higham D.J. Google PageRank as Mean Playing Time for Pinball on the Reverse Web Appl. Math. Lett. 2005 18 1359 1362 10.1016/j.aml.2005.02.020

상세보기
53. Kingma D.P. Ba J. Adam: A Method for Stochastic Optimization arXiv 2014 1412.6980
54. Nam G. Concerns over Political–Themed Stocks Ahead of Korea’s 21st General Election Cap. Mark. Focus 2020 2 1 5
55. Kim W.C. Lee Y. Lee Y.H. Cost of Asset Allocation in Equity Market: How Much Do Investors Lose Due to Bad Asset Class Design? J. Portf. Manag. 2014 41 34 44 10.3905/jpm.2014.41.1.034

상세보기
56. Sharpe W.F. Mutual Fund Performance J. Bus. 1966 39 119 138 10.1086/294846

상세보기
57. Sharpe W.F. The Sharpe Ratio J. Portf. Manag. 1994 21 49 58 10.3905/jpm.1994.409501

상세보기
58. Goedhart M. Koller T. Wessels D. Valuation: Measuring and Managing the Value of Companies John Wiley & Sons Hoboken, NJ, USA 2015
59. Iyengar G. Kang W. Inverse Conic Programming with Applications Oper. Res. Lett. 2005 33 319 330 10.1016/j.orl.2004.04.007

상세보기
60. Lizier J.T. Prokopenko M. Zomaya A.Y. Local Information Transfer as a Spatiotemporal Filter for Complex Systems Phys. Rev. E 2008 77 026110 10.1103/PhysRevE.77.026110 18352093

상세보기
61. Vaswani A. Shazeer N. Parmar N. Uszkoreit J. Jones L. Gomez A.N. Polosukhin I. Attention is all you need arXiv 2017 1706.03762
62. Devlin J. Chang M.W. Lee K. Toutanova K. Bert: Pre-training of deep bidirectional transformers for language understanding arXiv 2019 1810.04805
63. Dashtipour K. Gogate M. Li J. Jiang F. Kong B. Hussain A. A hybrid Persian sentiment analysis framework: Integrating dependency grammar based rules and deep neural networks Neurocomputing 2020 380 1 10 10.1016/j.neucom.2019.10.009

상세보기

LOADING...

활용도 분석정보

상세보기

다운로드

내보내기

활용도 Top5 논문

해당 논문의 주제분야에서 활용도가 높은 상위 5개 콘텐츠를 보여줍니다.
더보기 버튼을 클릭하시면 더 많은 관련자료를 살펴볼 수 있습니다.

표제어: PCR

동의어: Packet Collision Rate

용어 설명 출처 목록 (6)

용어 설명: PCR은 세균 특이성이 있는 primer를 이용하여 적은 수의 세균이 있을지라도 쉽게 검출할 수 있는 유용한 방법이며, 이를 이용하여 구강 내 치면세균막이나 타액에서 직접 세균을 검출할 수 있게 되었다[8].

내보내기 구분	파일저장 인쇄 메일전송
구성항목	기본정보 상세정보 관리번호, 논문명, 저널/프로시딩명, 저자 , 발행년, 권, 호, 시작페이지, 끝페이지, 발행기관 관리번호, 논문명, 대등논문명, 저자 , 저널/프로시딩명, 발행기관, 발행년, 발행언어, 권, 호, 시작페이지, 끝페이지, ISBN, ISSN, 주제분야, 키워드, 초록(한글), 초록(영문), 저자(소속기관)
저장형식	Text(ASCII format) Excel format RefWorks Direct Export RIS format (for Reference Manager, ProCite, EndNote), Scholar's Aids, Mendeley
메일정보	받는사람 (필수) @ 보내는사람 (선택) @ 제목 내용 KISTI 검색결과 이메일 서비스
안내	총 건의 자료가 검색되었습니다. 다운받으실 자료의 인덱스를 입력하세요. (1-10,000) 검색결과의 순서대로 최대 10,000건 까지 다운로드가 가능합니다. 데이타가 많을 경우 속도가 느려질 수 있습니다.(최대 2~3분 소요) 다운로드 파일은 UTF-8 형태로 저장됩니다. 파일의 내용이 제대로 보이지 않을실 때는 웹브라우저 상단의 보기 -> 인코딩 -> 자동선택 여부를 확인하십시오. ~ Text(ASCII format) Excel format

연합인증