Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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ETF risk management

ETF 위험관리에 관한 연구

  • Lee, Woosik (Department of Information Statistics, Anyang University)
  • 이우식 (안양대학교 정보통계학과)
  • Received : 2017.06.22
  • Accepted : 2017.07.24
  • Published : 2017.07.31
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Abstract

The rise of the Robo-advisor represents one of the most profound shifts in FinTech. It also raises concerns about their financial management. As the most Robo-Advisors utilize ETFs, we seek to determine the appropriate risk management model in estimating 95% Value-at-Risk (VaR) and 99% VaR in this paper. The GARCH and the Markov regime wwitching GARCH are evaluated in terms of the accuracy of probability, the independence of extreme events occurrence and both. The result shows that the Markov regime switching GARCH can be a good ETF risk management tool since it can reflect financial market structural changes into the volatility.

로보어드바이저 서비스 제공업체가 금융시장에서 거래되는 ETF를 주력 투자대상으로 집중하고 있다. 이처럼 ETF가 활성화되고 있지만 ETF 위험관리에 관한 연구들은 이뤄지지 않고 있는 상태이다. 본 연구는 변동성의 구조적 변화를 반영한 ETF 손실추정과 ETF 위험관리모형을 평가하였다. 결합 검증통계량 분석결과, GARCH와 마르코프 국면전환 GARCH모형이 시장위험을 적절하게 나타내 주었다. 특히 마르코프 국면전환 GARCH모형이 GARCH모형에 비해 낮은 위반율을 보일뿐 아니라 초과발생들이 독립적이기 때문에 마르코프 국면전환 GARCH모형이 GARCH모형에 비해 좀 더 ETF VaR에 권고될 수 있다.

Keywords

References

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