국내 선물시장의 장기기억과 시장의 효율성에 관한 연구

• 영문명: Long Memory and Market Efficiency in Korean Futures Markets
• 발행기관: 강원대학교 경영경제연구소
• 저자명: 조대형(Dae-Hyoung Cho)
• 간행물 정보: 『아태비즈니스연구』제11권 제4호, 255~269쪽, 전체 15쪽
• 주제분류: 인문학 > 문학
• 파일형태: PDF
• 발행일자: 2020.12.30

영문 초록

Purpose - This paper analyzes the market efficiency focusing on the long memory properties of the domestic futures market. By decomposing futures prices into yield and volatility and looking at the long memory properties of the time series, this study aims to understand the futures market pricing and change behavior and risks, specifically and in detail. Design/methodology/approach - This study analyzes KOSPI 200 futures, KOSDAQ 150 futures, 3 and 10-year government bond futures, US dollar futures, yen futures, and euro futures, which are among the most actively traded on the Korea Exchange. To analyze the long memory and market efficiency, we used the Variance Ratio, Rescaled-Range(R/S), Geweke and Porter-Hudak(GPH) tests as semi- parametric methods, and ARFIMA-FIGARCH model as the parametric method. Findings - It was found that all seven futures supported the efficiency market hypothesis because the property of long memory turned out not to exist in their yield curves. On the other hand, in futures volatility, all 7 futures showed long memory properties in the analysis, which means that if new information is generated in the domestic futures market and the market volatility once expanded due to the impact, it does not decrease or shrink for a long period of time, but continues to affect the volatility. Research implications or Originality - The results of this paper suggest that it can be useful information for predicting changes and risks of volatility in the domestic futures market. In particular, it was found that the long memory properties would be further strengthened in the currency futures and bond rate futures markets after the global financial crisis if the regime changes of the domestic financial market are taken into account in the analysis.

목차

Ⅰ. 서론

Ⅱ. 연구방법론

Ⅲ. 분석자료

Ⅳ. 실증분석 결과

Ⅴ. 결론

References

키워드

Long Memory Variance Ratio Rescaled-Range(R/S) Geweke and Porter-Hudak(GPH) ARFIMA-FIGARCH