A Comparative Study on the Forecasting Performance of Range Volatility Estimators using KOSPI 200 Tick DataA Comparative Study on the Forecasting Performance of Range Volatility Estimators using KOSPI 200 Tick Data
- Other Titles
- A Comparative Study on the Forecasting Performance of Range Volatility Estimators using KOSPI 200 Tick Data
- Authors
- 김은영; 박종해
- Issue Date
- 2009
- Publisher
- 한국재무관리학회
- Keywords
- Range Volatility Estimator; Two-scale Realized Volatility Estimator; Forecasting Performance; KOSPI 200; Range Volatility Estimator; Two-scale Realized Volatility Estimator; Forecasting Performance; KOSPI 200
- Citation
- 재무관리연구, v.26, no.2, pp 181 - 201
- Pages
- 21
- Indexed
- KCI
- Journal Title
- 재무관리연구
- Volume
- 26
- Number
- 2
- Start Page
- 181
- End Page
- 201
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/26522
- ISSN
- 1225-0759
2734-0759
- Abstract
- This study is on the forecasting performance analysis of range volatility estimators(Parkinson, Garman and Klass, and Rogers and Satchell) relative to historical one using two-scale realized volatility estimator as a benchmark.
American sub-prime mortgage loan shock to Korean stock markets happened in sample period(January 2, 2006~March 10, 2008), so the structural change somewhere within this period can make a huge influence on the results. Therefore sample was divided into two sub-samples by May 30, 2007 according to Zivot and Andrews unit root test results. As expected, the second sub-sample was much more volatile than the first sub-sample.
As a result of forecasting performance analysis, Rogers and Satchell volatility estimator showed the best forecasting performance in the full sample and relatively better forecasting performance than other estimators in sub-samples. Range volatility estimators showed better forecasting performance than historical volatility estimator during the period before the outbreak of structural change(the first sub-sample). On the contrary, the forecasting performance of range volatility estimators couldn’t beat that of historical volatility estimator during the period after this event(the second sub-sample). The main culprit of this result seems to be the increment of range volatility caused by that of intraday volatility after structural change.
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