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Mathematical Problems in Engineering
Volume 2014 (2014), Article ID 612758, 8 pages
http://dx.doi.org/10.1155/2014/612758
Research Article

Risk Measure and Early-Warning System of China's Stock Market Based on Price-Earnings Ratio and Price-to-Book Ratio

1School of Finance, Zhejiang University of Finance and Economics, Hangzhou 310018, China
2Coordinated Innovation Centre of Wealth Management and Quantitative Investment, Zhejiang University of Finance and Economics, Hangzhou 310018, China
3Center for Research of Regulation and Policy of Zhejiang, Hangzhou 310018, China
4New York Branch, Industrial and Commercial Bank of China, New York, NY 10022, USA

Received 1 December 2013; Accepted 30 January 2014; Published 12 March 2014

Academic Editor: Chuangxia Huang

Copyright © 2014 Rongda Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. X. Liao, The Formation Mechanism and Prevention of Bubble Economy, Economic Management Press, 2008.
  2. Z.-T. Yin, “The outbreak of the first financial crisis in the Republic of China and its inspiration,” Journal of Shandong Institute of Business and Technology, vol. 23, no. 1, pp. 80–86, 2009. View at Google Scholar
  3. C.-J. Hu and Q.-W. Liang, “The thinking about China's stock market by a wide margin rising and sharply slumping,” Special Journal of Zone Economy, vol. 11, pp. 59–64, 2010. View at Google Scholar
  4. G. Sun, Theory and Empirical Analysis of Stock Market Crisis Warning of Our Country, Tianjin University of Finance & Economics, 2001.
  5. X.-W. Lin and B.-Q. Song, “Early warning model by empirical analysis of financial risk in China,” Journal of Fuzhou University, vol. 4, pp. 8–49, 2011. View at Google Scholar
  6. J.-F. Cao, “Warning index construction and empirical analysis of speculative stock market bubble,” China Management Informationization, vol. 12, no. 9, pp. 21–28, 2009. View at Google Scholar
  7. D. G. McMillan, “Nonlinear predictability of stock market returns: evidence from nonparametric and threshold models,” International Review of Economics and Finance, vol. 10, no. 4, pp. 353–368, 2001. View at Publisher · View at Google Scholar · View at Scopus
  8. C.-X. Huang, X. Gong, X.-H. Chen, and F.-H. Wen, “Measuring and forecasting volatility in Chinese stock market using HAR-CJ-M model,” Abstract and Applied Analysis, vol. 2013, Article ID 143194, 13 pages, 2013. View at Publisher · View at Google Scholar
  9. C.-S. Xiao, “A study of the stock market crisis early-warning system,” Southwest Jiaotong University, vol. 38, no. 7, pp. 76–82, 2008. View at Google Scholar
  10. Y. Si, “The applied research of extension comprehensive evaluation of our stock market risk early warning,” Market Modernization, vol. 19, no. 8, pp. 121–128, 2007. View at Google Scholar
  11. L. Qian and Y.-M. Tao, “The precaution mechanism of P/E multiple on the burst of the stock market bubble,” Journal of Donghua University, vol. 36, no. 4, pp. 83–89, 2009. View at Google Scholar
  12. K. Huarng and H.-K. Yu, “A type 2 fuzzy time series model for stock index forecasting,” Physica A, vol. 353, no. 1–4, pp. 445–462, 2005. View at Publisher · View at Google Scholar · View at Scopus
  13. T.-L. Chen, C.-H. Cheng, and H.-J. Teoh, “High-order fuzzy time-series based on multi-period adaptation model for forecasting stock markets,” Physica A, vol. 387, no. 4, pp. 876–888, 2008. View at Publisher · View at Google Scholar · View at Scopus
  14. T. Bollerslev, “Generalized autoregressive conditional heteroskedasticity,” Journal of Econometrics, vol. 31, no. 3, pp. 307–327, 1986. View at Publisher · View at Google Scholar · View at MathSciNet
  15. F.-H. Wen, Z. Li, C.-H. Xie, and S. David, “Study on the fractal and chaotic features of the Shanghai composite index,” Fractals-Complex Geometry Patterns and Scaling in Nature and Society, vol. 20, no. 2, pp. 133–140, 2012. View at Google Scholar
  16. T. Su and Y.-R. Zhan, “VaR estimation based on SWARCH model,” Journal of Quantitative & Technical Economics, vol. 12, pp. 15–24, 2005. View at Google Scholar
  17. D.-Q. Wang, “ARMA-GARCH models and the appl ication of VaR method to Chinese inter-bank borrowing interest rate,” Journal of Systems Engineering, vol. 5, no. 27, pp. 12–19, 2009. View at Google Scholar
  18. Q.-Z. Liu and N.-F. Zhang, “Research on credit risk CVaR measurement method based on GARCH model,” Journal of Statistics and Decision, vol. 10, pp. 56–61, 2010. View at Google Scholar
  19. F. Wen and X. Yang, “Skewness of return distribution and coefficient of risk premium,” Journal of Systems Science & Complexity, vol. 22, no. 3, pp. 360–371, 2009. View at Publisher · View at Google Scholar · View at MathSciNet
  20. T. Jiang, “The measurement and analysis of stock market risk based on GARCH model & David X.L1999 and VaR method: the empirical evidence from Shanghai stock market,” Journal of Financial Research, vol. 78, no. 6, pp. 132–143, 2010. View at Google Scholar
  21. A.-Y. Tao and Z.-Y. Yu, “The contrastive analysis of financial market risk measurement method,” Statistics and Decision, vol. 46, no. 8, pp. 37–43, 2009. View at Google Scholar
  22. C. Pérignon, Z. Y. Deng, and Z. J. Wang, “Do banks overstate their Value-at-Risk?” Journal of Banking and Finance, vol. 32, no. 5, pp. 783–794, 2008. View at Publisher · View at Google Scholar · View at Scopus
  23. Y. Yu and X.-K. Hu, “An Empirical Study of China's stock market theory p/e ratio,” Journal of Economic Vision, vol. 6, pp. 33–35, 2011. View at Google Scholar