응용통계연구 (The Korean Journal of Applied Statistics)

  • 제26권5호
  • /
  • Pages.807-819
  • /
  • 2013
  • /
  • 1225-066X(pISSN)
  • /
  • 2383-5818(eISSN)
한국통계학회 (The Korean Statistical Society)
권호 표지
DOI QR코드

DOI QR Code

재현그림을 통한 우리나라 주식 자료에 대한 탐색적 자료분석

Exploratory Data Analysis for Korean Stock Data with Recurrence Plots

  • 투고 : 2013.08.22
  • 심사 : 2013.09.30
  • 발행 : 2013.10.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

확증적 시계열 자료분석 전의 그래픽 탐색적 자료분석방법으로서 재현그림을 사용할 수 있다. 재현그림을 통하여 시계열 자료의 구조적 패턴을 확인할 수 있고 이 패턴을 통하여 탐색적으로 시계열 데이터의 구조 변화점을 한 눈에 확인할 수 있게 된다. 우리나라 주식 자료를 이용하여 재현그림이 시계열 자료를 위한 그래픽 탐색적 자료분석방법으로서 유용함을 보였다.

A recurrence plot can be used as a graphical exploratory data analysis tool before confirmatory time series analysis. With the recurrence plot, we can obtain the structural pattern of the time series and recognize the structural change points in a time series at a glance. Korean stock data shows the usefulness of the recurrence plot as a graphical exploratory data analysis tool for time series data.

키워드

참고문헌

  1. Addo, P. A., Billio, M. and Guegan, D. (2013). Nonlinear dynamics and recurrence plots for detecting financial crisis, North American Journal of Economics and Finance, in press.
  2. Belaire-Franch, J., Contreras, D. and Tordera-Lledo, L. (2002). Assessing nonlinear structures in real exchange rates using recurrence plot strategies, Physica D, 171, 249-264. https://doi.org/10.1016/S0167-2789(02)00625-5
  3. Chen, W. (2011). Use of recurrence plot and recurrence quantification analysis in Taiwan unemployment rate time series, Physica A, 390, 1332-1342. https://doi.org/10.1016/j.physa.2010.12.020
  4. Eckmann, J. P., Kamphorst, S. O. and Ruelle, D. (1987). Recurrence plots of dynamical systems, Europhysics Letters, 5, 973-977.
  5. Guhathakurta, K., Bhattacharya, B. and Chowdhury, A. R. (2010). Using recurrence plot analysis to distinguish between endogenous and exogenous stock market crashes, Physica A, 389, 1874-1882. https://doi.org/10.1016/j.physa.2009.12.061
  6. Hwang, E. and Shin, D. W. (2013). Stationary bootstrap prediction intervals for GARCH(p, q), Communications of the Korean Statistical Society, 20, 41-52. https://doi.org/10.5351/CSAM.2013.20.1.041
  7. Iwanski, J. S. and Bradley, E. (1998). Recurrence plots of experimental data: To embed or not to embed, Chaos, 8, 861-871. https://doi.org/10.1063/1.166372
  8. Jang, D. H. (2009). Recurrence plots as an exploratory graphical tool for evaluating randomness, The Korean Journal of Applied Statistics, 22, 1153-1165. https://doi.org/10.5351/KJAS.2009.22.6.1153
  9. Kim, B. M. and Kim, J. H. (2013). Time series models for daily exchange rare data. The Korean Journal of Applied Statistics, 26, 1-14. https://doi.org/10.5351/KJAS.2013.26.1.001
  10. Lee, S. and Noh, J. (2013). An empirical study on explosive volatility test with possibly nonstationary GARCH(1, 1) models, Communications of the Korean Statistical Society, 20, 207-215. https://doi.org/10.5351/CSAM.2013.20.3.207
  11. Marwan, N., Romano, M. C., Thiel, M. and Kurths, J. (2007). Recurrence plots for the analysis of complex systems, Physics Reports, 438, 237-329. https://doi.org/10.1016/j.physrep.2006.11.001
  12. Matassini, L., Kantz, H., Holyst, J. and Hegger, R. (2002). Optimizing of recurrence plots for noise reduction, Physical Review E, 65, 021102. https://doi.org/10.1103/PhysRevE.65.021102
  13. Mindlin, G. M. and Gilmore, R. (1992). Topological analysis and synthesis of chaotic time series, Physica D, 58, 229-242. https://doi.org/10.1016/0167-2789(92)90111-Y
  14. Oh, J. and Kim, S. (2013). Value-at-Risk estimation of the KOSPI returns by employing long-memory volatility models, The Korean Journal of Applied Statistics, 26, 163-185. https://doi.org/10.5351/KJAS.2013.26.1.163
  15. Park, K., Ko, K. and Beak, J. (2013). An one-factor VaR model for stock portfolio, The Korean Journal of Applied Statistics, 26, 471-481. https://doi.org/10.5351/KJAS.2013.26.3.471
  16. Thiel, M., Romano, M. C., Kurths, J., Meucci, R., Allaria, E. and Arecchi, F. T. (2002). Influence of observa-tional noise on the recurrence quantification analysis, Physica D, 171, 138-152. https://doi.org/10.1016/S0167-2789(02)00586-9
  17. Zbilut, J. P. and Webber Jr., C. L. (1992). Embeddings and delays as derived from quantification of recurrence plots, Physics Letters A, 171, 199-203. https://doi.org/10.1016/0375-9601(92)90426-M
  18. Zbilut, J. P., Zaldivar-Commenges, J. M., and Strozzi, F. (2002). Recurrence quantification based Liapunov exponents for monitoring divergence in experimental data, Physics Letters A, 297, 173-181. https://doi.org/10.1016/S0375-9601(02)00436-X

피인용 문헌

  1. Exploratory data analysis for Korean daily exchange rate data with recurrence plots vol.24, pp.6, 2013, https://doi.org/10.7465/jkdi.2013.24.6.1103