DOI QR코드

DOI QR Code

A Case Study on the Establishment of an Equity Investment Optimization Model based on FinTech: For Institutional Investors

핀테크 기반 주식투자 최적화 모델 구축 사례 연구 : 기관투자자 대상

  • 김홍곤 (연세대학교 (투자정보공학과), DGB자산운용) ;
  • 김소담 (연세대학교 정보대학원) ;
  • 김희웅 (연세대학교 정보대학원)
  • Received : 2017.12.28
  • Accepted : 2018.02.23
  • Published : 2018.03.31

Abstract

The finance-investment industry is currently focusing on research related to artificial intelligence and big data, moving beyond conventional theories of financial engineering. However, the case of equity optimization portfolio by using an artificial intelligence, big data, and its performance is rarely realized in practice. Thus, the purpose of this study is to propose process improvements in equity selection, information analysis, and portfolio composition, and lastly an improvement in portfolio returns, with the case of an equity optimization model based on quantitative research by an artificial intelligence. This paper is an empirical study of the portfolio based on an artificial intelligence technology of "D" asset management, which is the largest domestic active-quant-fiduciary management in accordance with the purpose of this paper. This study will apply artificial intelligence to finance, analyzing financial and demand-supply information and automating factor-selection and weight of equity through machine learning based on the artificial neural network. Also, the learning the process for the composition of portfolio optimization and its performance by applying genetic algorithms to models will be documented. This study posits a model that the asset management industry can achieve, with continuous and stable excess performance, low costs and high efficiency in the process of investment.

Keywords

References

  1. 강다연, 장활식, 김종기 2009. "국내 기업 ERP 시스템 도입의 정성적.정량적 성과 비교," 한국콘텐츠학회논문지, (9:4), pp. 142-153. https://doi.org/10.5392/JKCA.2009.9.4.142
  2. 고광수, 이준행 2003. "외국인 거래 정보와 주식시장: 개방 10년의 경험," 재무연구, (16:1), pp. 159-192.
  3. 김원걸, 유성민, 김영상 2016. "인공지능과 핀테크," 한국정보기술학회, (14:1), pp. 23-28.
  4. 김종희 2013. "투자 주체별 정보력 우위 및 추세 역 추종 거래 행위가 주식시장의 수익률에 미치는 영향 분석," 한국증권학회지, (42:4), pp. 667-698.
  5. 박재석, 김민진, 황병일 2016. "핀테크의 발전 배경과 주요 동향," 한국통신학회지, (33:2), pp. 52-58.
  6. 박재연, 유재필, 신현준 2016. "로보어드바이저를 이용한 포트폴리오 관리," 대한산업공학회, (13:3), pp. 467-476.
  7. 배재권 2010. "Voting 알고리즘과 인공신경망을 이용한 부도예측을 위한 통합 알고리즘," 한국비즈니스리뷰, (3:2), pp. 79-101
  8. 양진용 2016. "기업 재무 정보를 활용한 머신 러닝 기반 경영 예측 시스템," 한성대학교 박사학위논문, pp. 9-27.
  9. 여환영, 박영규, 주효근 2017. "펀드 매니저의 특성과 투자행태: 개인적 특성이 성과 지속성, 스타일, 위험 등에 미치는 영향," 한국증권학회지, (46:2), pp. 497-522.
  10. 오경주 2006. "유전자 알고리즘을 이용한 계층 구조 포트폴리오 최적화에 관한 연구: 인덱스 펀드 알고리즘 설계," 한국연구재단. 인문사회분야 기초연구과제, pp. 2-17.
  11. 이동규, 이성훈 2015. "IT와 은행의 새로운 융합형태," 한국정보기술학회지, (13:1), pp. 55-58.
  12. 정동헌, 오경주 2014. "군집분석과 유전자 알고리즘을 활용한 투자자 거래정보 기반 포트폴리오투자전략," 한국데이터정보과학회지, (25:1), pp. 107-117.
  13. 홍승현, 신경식 1999. "유전자 알고리즘을 활용한 인공신경망 모형 최적입력변수의 선정," 한국지능정보시스템학회 학술대회논문집, pp. 365-373.
  14. Anderson, C. R. and Zeithaml, C. P. 1984. "Stage of the product life cycle, business strategy, and business performance," Academy of Management Journal (27:1), pp. 5-24. https://doi.org/10.2307/255954
  15. Bales, R.F. 1950. Artificial Neural Network Modeling. Polish Academy of Sciences, Warsaw, Poland: Springer.
  16. Choe, H., Kho, B. C. and Stulz, R. 1999. "Do Foreign Investors Destabilize Stock Markets? The Korean Experience in 1997," Journal of Financial Economics, (54:2), pp. 227-264. https://doi.org/10.1016/S0304-405X(99)00037-9
  17. Creswell, J. W. 2007. Qualitative inquiry & research design: Choosing among five approaches (2nd ed.), Thousand Oaks, CA: Sage.
  18. Fama, E. 1998. "Market Efficiency, Long-Term Returns, and Behavioral Finance," Journal of Financial Economics, (43:1), pp. 283-306.
  19. Fama, Eugene F. and Kenneth R. French. 1992. "The cross-section of expected stock returns," Journal of Finance, (47), pp. 427-465. https://doi.org/10.1111/j.1540-6261.1992.tb04398.x
  20. Fama, Eugene F. and Kenneth R. French. 1995. "Size and book-to-market factors in earnings and returns," Journal of Finance, (50), pp. 131-155. https://doi.org/10.1111/j.1540-6261.1995.tb05169.x
  21. Gah-Yi Ban, Noureddine El Karoui, Andrew E. B. Lim. 2016. "Machine Learning and Portfolio Optimization," Journal of Management Science, Published online in Articles in Advance 21 Nov 2016.
  22. Goldberg. D.E. 1985. Genetic algorithms and rule learning indynamic system control. Proceedings of the first International Conference on Genetic Algorithms and Their Application, Pittsburgh, pp. 8-15.
  23. Goldberg. D.E. 1989. "Genetic algorithms in search, optimization and machine learning." Addison Wesley Publishing company, Inc., N.Y. 6.
  24. Julian Skan, Richard Lumb, Samad Masood, and Sean K. Conway, "The Boom in Global Fintech Investment", Accenture, 2014.
  25. Kang, J. K, .and R. M. Stulz. 1997. "Why is There a Home Bias? An Analysis of Foreign Portfolio Equity Ownership in Japan," Journal of Financial Economics (42:1), pp. 2-28.
  26. Kim, H.W., Chan, H. C. and Gupta, S. 2015. "Social Media for Business and Society," Asia Pacific Journal of Information Systems, (25:2), pp. 211-233. https://doi.org/10.14329/apjis.2015.25.2.211
  27. Markowitz, H.M. 1952. "Portfolio Selection," Journal of Finance, (7:1), pp. 77-91. https://doi.org/10.1111/j.1540-6261.1952.tb01525.x
  28. Padgett, D. K. 2008. Qualitative methods in social work research, (36), Sage.
  29. R. Roll. 1992. "A mean-variance analysis of the tracking error," Journal of Portfolio Management, (18:1), pp. 13-22. https://doi.org/10.3905/jpm.1992.701922
  30. Rosenblatt, F. 1958. "The Perceptron: A Probabilistic Model For Information Storage And Organization In The Brain," Psychological Review, (65:6), pp. 386-408. https://doi.org/10.1037/h0042519
  31. Sias, R. W. 2004. "Institutional Herding," Review of Financial Studies (17:1), pp. 165-206. https://doi.org/10.1093/rfs/hhg035
  32. Tractica. 2015. "Artificial Intelligence for Enterprise Applications : Deep Learning, Predictive Computing, Image Recognition, Speech Recognition, and Other AI Technologies for Enter prise Markets", Global Market Analysis and Forecasts.
  33. Warren McCulloch. 1943. "A Logical Calculus of the Ideas Immanent in Nervous Activity"
  34. Sharpe, W. F. 1964. Capital Asset Prices: A Theory of Market Equilibrium Under Conditions of Risk, Journal of Finance. (19:3), pp. 425-442. https://doi.org/10.1111/j.1540-6261.1964.tb02865.x
  35. Yin, R. K. 2003. Case study research: Design and methods (3rd ed.), Thousand Oaks, CA: Sage.

Cited by

  1. Multi Strategy 운용 체계 금융 투자 사례연구: E증권사 Prop Trading을 중심으로 vol.22, pp.1, 2018, https://doi.org/10.15813/kmr.2021.22.1.002