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An analysis of the financial crisis in the KOSPI market using Hurst exponents SCIE SCOPUS

Title
An analysis of the financial crisis in the KOSPI market using Hurst exponents
Authors
Kyubin YimGabjin OhKim, S
Date Issued
2014-09-15
Publisher
ELSEVIER
Abstract
Recently, the study of the financial crisis has progressed to include the concept of the complex system, thereby improving the understanding of this extreme event from a neoclassical economic perspective. To determine which variables are related to the financial event caused by the 2008 US subprime crisis using temporal correlations, we investigate the diverse variables that may explain the financial system. These variables include return, volatility, trading volume and inter-trade duration data sets within the TAQ data for 27 highly capitalized individual companies listed on the KOSPI stock market. During 2008 and 2009, the Hurst exponent for the return time series over the whole period was less than 0.5, and the Hurst exponents for other variables, such as the volatility, trading volume and inter-trade duration, were greater than 0.5. Additionally, we analyze the relationships between the variation of temporal correlation and market instability based on these Hurst exponents and the degree of multifractality. We find that for the data related to trading volume, the Hurst exponents do not allow us to detect changes in market status, such as changes from normal to abnormal status, whereas other variables, including the return, volatility and weekly inter-trade duration, indicate a significant change in market status after the Lehman Brothers' bankruptcy. In addition, the multifractality and the measurement defined by subtracting the Hurst exponent of the return time series from that of the volatility time series decrease sharply after the US subprime event and recover approximately 50 days after the Lehman Brothers' collapse. Our findings suggest that the temporal features of financial quantities in the TAQ data set and the market complexity perform very well at diagnosing financial market stability. (C) 2014 Elsevier B.V. All rights reserved.
URI
https://oasis.postech.ac.kr/handle/2014.oak/13563
DOI
10.1016/J.PHYSA.2014.05.033
ISSN
0378-4371
Article Type
Article
Citation
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, vol. 410, page. 327 - 334, 2014-09-15
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