Scaling characteristics in the Taiwan stock market
Scaling characteristics in the Taiwan stock market
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DOI：
10.1016/j.physa.2003.10.023
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发表时间：
2004-02
影响因子：
3.3
通讯作者：
Ding-Shun Ho;Chung-Kung Lee;Cheng-Cai Wang;M. Chuang
中科院分区：
文献类型：
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作者：
Ding-Shun Ho;Chung-Kung Lee;Cheng-Cai Wang;M. Chuang
本文运用直方图、谱分析和分形理论等统计工具，对台湾股市1987-2002年间的日均股价指数(TSPI)的规模不变行为及其集聚特征进行了研究。研究发现，TSPI数据具有右偏的频率分布特征。通过自相关分析和功率谱分析，粗略地识别了长时记忆和尺度不变性的可能性。采用计盒法进行单因素分析。时间序列具有明显的尺度不变性，盒维是阈值指数水平的递减函数，具有多重分形特征，即低、高区域尺度不同。为了验证这一假设，通过多重分形论将时间序列转化为有用的紧致形式，即τ(Q)-q和f(α)-α图)。分析证实了所研究的时间序列中存在多重分形特征。台湾股市多重分维现象的成因，可以用股市信息的乘性级联过程来解释。
Some statistical tools, including histogram, spectral analysis and fractal theory, were used on the daily Taiwan stock price index (TSPI) from 1987 to 2002 to examine the possible scale-invariant behavior and the clustering characteristics in Taiwan stock market. It was found that the TSPI data exhibited the characteristic of right-skewed frequency distribution. The long-term memory and the possibility of scale invariance were roughly identified through the analysis of autocorrelation and power spectrum, respectively. The monofractal analysis was then performed by the box-counting method. Scale invariance was clearly found in the time series and the box dimension was shown to be a decreasing function of the threshold index level, implying multifractal characteristics, i.e., the low and high regions scale differently. To test this hypothesis, the time series were transferred into a useful compact form through the multifractal formalism, namely, the τ(q)–q and f(α)–α plots. The analysis confirmed the existence of multifractal characteristics in the investigated time series. The origin of multifractal phenomena in Taiwan stock market might be interpreted in terms of the multiplicative cascade process of stock market information.