The Application of Multiscale Entropy in Stock Index Analysis

• Main Authors: Yi-Ju Huang, 黃檍如
• Other Authors: Tsair-Chuan Lin
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/44811537101104675515

碩士 === 國立臺北大學 === 統計學系 === 102 === The approaches of correlation coefficient, unit root test (such as DF test & ADF test), structural change test (such as Chow test), autoregressive conditional heteroscedasticity (ARCH), vector autoregression model (VAR model) or Johansen cointegration test, etc. are frequently used to test structural changes of stock market indices. However, there are some limitations when using these tools. The literature has found that the multiscale entropy (MSE) can be applied to time series to investigate the issue of change points. Based on this, this paper aimed to apply the multiscale entropy to the stock index of Taiwan Weighted Index (TWII), Hang Seng Index (HSI), Dow Jones Industrial Average Index (DJI), NASDAQ, Financial Times Stock Exchange Index (FTSE) and Cotation Assistée en Continu 40 (CAC40) to test their structural changes and determine the possible time of the change points. From the real data study, we find all of these stock indices have a common structure change point around September of 2008.