The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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A Bootstrap Lagrangian Multiplier Test for Market Microstructure Noise in Financial Assets

금융자산의 시장 미시구조 잡음에 대한 부트스트래핑 라그랑지 승수 검정

  • Kim, Hyo Jin (Department of Statistics, Ewha Womans University) ;
  • Shin, Dong Wan (Department of Statistics, Ewha Womans University) ;
  • Park, Jonghun (Department of Industrial Engineering, Seoul National University) ;
  • Lee, Sang-Goo (Department of Computer Science and Engineering, Seoul National University)
  • Received : 2015.03.09
  • Accepted : 2015.03.25
  • Published : 2015.04.30
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Abstract

Stationary bootstrapping is applied to a Lagrangian multiplier (LM) test to test market microstructure noise (MMN) in financial asset prices. A Monte-Carlo experiment shows that the bootstrapping method improves the size of the original LM test which has some size distortion for conditional heteroscedastic models. The proposed test is illustrated for real data sets like KOSPI index and Won-Dollar exchange rate.

본 논문에서는 정상적 부트스트래핑을 금융 자산 가격에서 시장 미시구조 잡음에 대한 라그랑지 승수 검정에 적용한다. 몬테 카를로 실험을 통해 부트스트래핑 방법이 조건부 이분산 모형을 적용한 기존 라그랑지 승수 검정의 유의수준 왜곡 문제를 개선함을 보인다. 이 검정을 KOSPI 지수와 원-달러 환율과 같은 실제 데이터에 적용한다.

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References

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