Statistical properties of cross-correlation in the Korean stock market

Oh, Gabjin; Eom, Cheoljun; Wang, F.; Jung, Woo-Sung; Stanley, H. Eugene; Kim, Seunghwan

doi:10.1140/epjb/e2010-90492-x

Cited by 38 publications

(25 citation statements)

References 38 publications

(21 reference statements)

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“…Note that the highest eigenvalue stands out from all the others, being more than three times bigger than the uppermost limit λ + of the theoretical distribution. This is in agreement with many other results, obtained for a great number of financial institutions to which this same formalism has been already applied [71]- [100]. It is believed that this eigenvalue corresponds to the action of a single market, which influences all the other members of the correlation matrix.…”

Section: Datasupporting

confidence: 92%

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Correlation of financial markets in times of crisis

Sandoval

Franca

2012

Physica A: Statistical Mechanics and its Applications

218

106

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Using the eigenvalues and eigenvectors of correlations matrices of some of the main financial market indices in the world, we show that high volatility of markets is directly linked with strong correlations between them. This means that markets tend to behave as one during great crashes. In order to do so, we investigate financial market crises that occurred in the years 1987 (Black Monday), 1998 (Russian crisis), 2001 (Burst of the dot-com bubble and September 11), and 2008 (Subprime Mortgage Crisis), which mark some of the largest downturns of financial markets in the last three decades.

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Section: Datasupporting

confidence: 92%

“…This approach was successfully applied to a large number of financial markets [71]- [100], and also to the relation between world markets [101]- [102]. This approach was also used in the construction of hierarchical structures between different assets of financial markets [103]- [142].…”

Section: Introductionmentioning

confidence: 99%

Correlation of financial markets in times of crisis

Sandoval

Franca

2012

Physica A: Statistical Mechanics and its Applications

218

106

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show abstract

“…In the light of the extensive empirical evidences culled from underlying asset prices [8][9][10][11][12][13][14][15][16][17][18][19][20], clearly, the Black-Scholes-Merton options pricing model cannot explain certain properties of option prices in real markets, such as implied volatility smile and sneer behaviors. By contrast, however, an options pricing theory based on the Lévy process defined by a characteristic triplet (σ, ν, γ) can reproduce the features of option prices traded in real markets.…”

Section: Introductionmentioning

confidence: 99%

Multifractal analysis of implied volatility in index options

2014

Journal of the Korean Physical Society

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In this paper, we analyze the statistical and the non-linear properties of the log-variations in implied volatility for the CAC40, DAX and S&P 500 daily index options. The price of an index option is generally represented by its implied volatility surface, including its smile and skew properties. We utilize a Lévy process model as the underlying asset to deepen our understanding of the intrinsic property of the implied volatility in the index options and estimate the implied volatility surface. We find that the options pricing models with the exponential Lévy model can reproduce the smile or sneer features of the implied volatility that are observed in real options markets. We study the variation in the implied volatility for at-the-money index call and put options, and we find that the distribution function follows a power-law distribution with an exponent of 3.5 ≤ γ ≤ 4.5. Especially, the variation in the implied volatility exhibits multifractal spectral characteristics, and the global financial crisis has influenced the complexity of the option markets.

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“…The industry sector structure of mature market has been systematically studied, such as New York stock exchange and South Korea stock exchange [15]. Recently, the random matrix theory is used to explore eigenmode of industrial production index fluctuation in dissipative structure [16].…”

Section: Related Workmentioning

confidence: 99%

Relationship discovery in public opinion and actual behavior for social media stock data space

Xue

Qiu

et al. 2016

J Wireless Com Network

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With the rise of social data media, the cyber world nearly parallels to the real world. The trajectory of a hot event is reflected in social media by Public Opinion Data Space (OS) and Actual Behavior Data Space (BS). However, the relationships with a variety of mechanisms in each space or between them are often unknown. To solve the above issues, the traditional methods for inferring relationship are by performing a statistical similarity analysis of time sequence from dynamic elements. In specially, the research of clustering nonlinear correlation data object is rare, so we propose Matrix Similarity Clustering Algorithm (MSCA) based on random matrix theory and combined with sliding window technology to cluster the similarity of multidimensional time sequences. This method is effective to detect the trend relationship of time sequences with multiple dynamic elements. In addition, we construct a knowledge map to analyse the relationships in OS and BS.

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Statistical properties of cross-correlation in the Korean stock market

Cited by 38 publications

References 38 publications

Correlation of financial markets in times of crisis

Correlation of financial markets in times of crisis

Multifractal analysis of implied volatility in index options

Relationship discovery in public opinion and actual behavior for social media stock data space

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