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Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems.

Ouyang FY, Zheng B, Jiang XF - PLoS ONE (2015)

Bottom Line: However, the cross-correlation between individual stocks and the return-volatility correlation are time scale dependent.The structure of business sectors is mainly governed by the fast mode when returns are sampled at a couple of days, while by the medium mode when returns are sampled at dozens of days.More importantly, the leverage and anti-leverage effects are dominated by the medium mode.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics, Zhejiang University, Hangzhou 310027, China; School of Electronics and Information, Zhejiang University of Media and Communications, Hangzhou 310018, China; Collaborative Innovation Center of Advanced Microstructures, Nanjing 210093, China.

ABSTRACT
The empirical mode decomposition is applied to analyze the intrinsic multi-scale dynamic behaviors of complex financial systems. In this approach, the time series of the price returns of each stock is decomposed into a small number of intrinsic mode functions, which represent the price motion from high frequency to low frequency. These intrinsic mode functions are then grouped into three modes, i.e., the fast mode, medium mode and slow mode. The probability distribution of returns and auto-correlation of volatilities for the fast and medium modes exhibit similar behaviors as those of the full time series, i.e., these characteristics are rather robust in multi time scale. However, the cross-correlation between individual stocks and the return-volatility correlation are time scale dependent. The structure of business sectors is mainly governed by the fast mode when returns are sampled at a couple of days, while by the medium mode when returns are sampled at dozens of days. More importantly, the leverage and anti-leverage effects are dominated by the medium mode.

No MeSH data available.


Related in: MedlinePlus

The business sectors of the full time series for the TWSE market are compared with those of the fast mode and medium mode for △t = 20 days.The abbreviations are the same as in Fig 3. The module that does not have a name is the one we could not identify.
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pone.0139420.g010: The business sectors of the full time series for the TWSE market are compared with those of the fast mode and medium mode for △t = 20 days.The abbreviations are the same as in Fig 3. The module that does not have a name is the one we could not identify.

Mentions: To obtain the interaction structure of communities, again, the methodology which combines the RMT theory with the planar maximally filtered graph and the alluvial diagram is applied. With this approach, the alluvial diagrams of the business sectors for the four stock markets have been analyzed. In Fig 10, the results for the TWSE market are displayed. All the business sectors for the full time series can be discovered in the medium mode. For the fast mode and slow mode, the identified communities are very different from those of the full time series, and can hardly be associated to business sectors. The other three stock markets also show a similar phenomenon.


Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems.

Ouyang FY, Zheng B, Jiang XF - PLoS ONE (2015)

The business sectors of the full time series for the TWSE market are compared with those of the fast mode and medium mode for △t = 20 days.The abbreviations are the same as in Fig 3. The module that does not have a name is the one we could not identify.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4591268&req=5

pone.0139420.g010: The business sectors of the full time series for the TWSE market are compared with those of the fast mode and medium mode for △t = 20 days.The abbreviations are the same as in Fig 3. The module that does not have a name is the one we could not identify.
Mentions: To obtain the interaction structure of communities, again, the methodology which combines the RMT theory with the planar maximally filtered graph and the alluvial diagram is applied. With this approach, the alluvial diagrams of the business sectors for the four stock markets have been analyzed. In Fig 10, the results for the TWSE market are displayed. All the business sectors for the full time series can be discovered in the medium mode. For the fast mode and slow mode, the identified communities are very different from those of the full time series, and can hardly be associated to business sectors. The other three stock markets also show a similar phenomenon.

Bottom Line: However, the cross-correlation between individual stocks and the return-volatility correlation are time scale dependent.The structure of business sectors is mainly governed by the fast mode when returns are sampled at a couple of days, while by the medium mode when returns are sampled at dozens of days.More importantly, the leverage and anti-leverage effects are dominated by the medium mode.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics, Zhejiang University, Hangzhou 310027, China; School of Electronics and Information, Zhejiang University of Media and Communications, Hangzhou 310018, China; Collaborative Innovation Center of Advanced Microstructures, Nanjing 210093, China.

ABSTRACT
The empirical mode decomposition is applied to analyze the intrinsic multi-scale dynamic behaviors of complex financial systems. In this approach, the time series of the price returns of each stock is decomposed into a small number of intrinsic mode functions, which represent the price motion from high frequency to low frequency. These intrinsic mode functions are then grouped into three modes, i.e., the fast mode, medium mode and slow mode. The probability distribution of returns and auto-correlation of volatilities for the fast and medium modes exhibit similar behaviors as those of the full time series, i.e., these characteristics are rather robust in multi time scale. However, the cross-correlation between individual stocks and the return-volatility correlation are time scale dependent. The structure of business sectors is mainly governed by the fast mode when returns are sampled at a couple of days, while by the medium mode when returns are sampled at dozens of days. More importantly, the leverage and anti-leverage effects are dominated by the medium mode.

No MeSH data available.


Related in: MedlinePlus