Dynamic of the States of Three Different Stock Markets from Correlation and Partial Correlation Changes

Shafiqul Alam; Nahid Akter; Mohammad Rubel Miah; Mohammed Javed Hossain; Ashadun Nobi

doi:doi:10.11648/j.ijber.20211004.16

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Dynamic of the States of Three Different Stock Markets from Correlation and Partial Correlation Changes

Shafiqul Alam, Nahid Akter, Mohammad Rubel Miah, Mohammed Javed Hossain, Ashadun Nobi

Published in International Journal of Business and Economics Research (Volume 10, Issue 4)

Received: 7 July 2021 Accepted: 21 July 2021 Published: 18 August 2021

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Abstract

The core focus of the study is to examine financial states using index effect on stock to stock correlations of developed, developing and emerging market. The three markets such as S&P 500, KOSPI 200 and DSE are declared as developed, developing and emerging market respectively. To study the similarity between stock price changes, we calculate the time series of the daily log return. Closing stock prices of the targeted markets have been used to measure the daily return of the stocks. To analyze the market mobility, Pearson correlation coefficient, partial correlation, and index effect on stock to stock correlation techniques have been applied. The study found that the companies of developed and emerging market are more strongly correlated than those of developing market during big crash. On the other hand, developing market shows less index effect on stock correlations during crisis. Moreover, insignificant index effect has been found in emerging market during calm state. No significant effect of DSE index on stock to stock correlations in the period of global financial crisis has been observed, implying that global financial crisis did not hit to the DSE in this period. Before the market crash, the interactions between stocks became low enough which corresponds to lower value of average correlation for all types of market. Finally, the change of correlation and partial correlation can be a good indicator to identify and predict the financial states of all the markets which will further helps the stakeholders to make proper economic decisions.

Published in	International Journal of Business and Economics Research (Volume 10, Issue 4)
DOI	10.11648/j.ijber.20211004.16
Page(s)	155-161
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

Stock-Stock Correlation, Partial Correlation, Stock-Index Correlation, Market Crash, Global Financial Crisis

References

[1]	Mobarek, A. and Keasey, K. (2000). Weak-form Market Efficiency of an Emerging Market: Evidence from Dhaka Stock Market of Bangladesh. ENBS Conference, 1-30.
[2]	Eom, C., Oh, G. and Kim, S. (2008). Statistical Investigation of Connected Structures of Stock Networks in Financial Time Series. Journal of the Korean Physical Society, 53 (6), 3837-3841.
[3]	King, B. F. (1996). Market and Industry Factors in Stock Price Behavior. The Journal of Business, 39 (1), 139-190.
[4]	Trzcinka, C. (1986). On the Number of Factors in the Arbitrage Pricing Model. The Journal of Finance, 41 (2), 347-368.
[5]	Brown, S. T. (1989). The Number of Factors in Security Returns. The Journal of Finance, 44 (5), 1247-1262.
[6]	Gary, C. and Rothschild, M. (1983). Arbitrage and Mean Variance Analyzing the Large Markets. Econometrica, 51, 1281-1301.
[7]	Kim, D. and Jeong, H. (2005). Systematic Analysis of Group Identification in Stock Market. Physical Review E, 72, 046133.
[8]	Cai, S. M., Zhou, Y. B., Zhou, T. and Zhou, P. L. (2010). Hierachical Organization and Disassortative Mixing of Correlation-based Weighted Financial Networks. International Journal of Modern Physics C, 21, 433–441.
[9]	Gao, Y. C., Wei, Z. W. and Wang, B. H. (2013). Dynamic Evolution of Financial Network and its Relation to Economic Crises. International Journal of Modern Physics C, 24 (02), 1350005.
[10]	Markowitz, H. (1952). Portfolio Selection. The Journal of Finance, 7 (1), 77-91.
[11]	Kenett, D. Y., Shapira, Y., Madi, A., Bransburg-Zabary, S., Gur- Gershgoren, G. and Ben-Jacob, E. (2011a). Index Cohesive Force Analysis Reveals that the US Market Became Prone to Systemic Collapses Since 2002. PloS one, 6, e19378.
[12]	Kenett, Y. N., Kenett, D. Y., Ben-Jacob, E. and Faust, M. (2011b). Global and Local Features of Semantic Networks: Evidence from the Hebrew Mental Lexicon. PloS one, 6, e23912.
[13]	Kenett, D. Y., Tumminello, M., Madi, A., Gur- Gershgoren, G., Mantegna, R. N. and Ben-Jacob, E. (2010). Dominating Clasp of the Financial Sector Revealed by Partial Correlation Analysis of the Stock Market. PLoS one, 5, e15032.
[14]	Madi, A., Kenett, D., Bransburg-Zabary, S., Merbl, Y., Quintana, F., Boccaletti, S., Tauber, A., Cohen, I. and Ben-Jacob, E., (2011). Analyses of Antigen Dependency Networks Unveil Immune System Reorganization between Birth and Adulthood. Chaos: An Interdisciplinary Journal of Nonlinear Science, 21, 016109–016109.
[15]	Jung, Sean S. and Chang, W. (2016). Clustering Stocks using Partial Correlation Coefficients. Physica A, 462, 410–420.
[16]	Mantegna, R. N. (1999). Hierarchical Structure in Financial Markets. European Physical Journal B. https://doi.org/10.1007/s100510050929.
[17]	Bonanno, G., Caldarelli, G., Lillo, F. and Mantegna, R. N. (2003). Topology of Correlation-based Minimal Spanning Trees in Real and Model Markets. Physical Review E, 68, 046130.
[18]	Onnela, J. P., Chakraborti, A., Kaski, K., Kert´esz, J. and Kanto, A. (2003). Dynamics of Market Correlations: Taxonomy and Portfolio Analysis. Physical Review E, 68, 056110.
[19]	Onnela, J. P., Kaski, K. and Kert´esz, J. (2004). Clustering and Information in Correlation based Financial Networks. The European Physical Journal B, March 2004, 38 (2), 353–362.
[20]	Kenett, D. Y., Huang, X., Vodenska, I., Havlin, S. and Stanley, H. E. (2015). Partial Correlation Analysis: Applications for Financial Markets. Quantitative Finance, 15 (4), 569-578, DOI: 10.1080/14697688.2014.946660.
[21]	Aste, T., Shaw, W. and Di-Matteo, T. (2010). Correlation Structure and Dynamics in Volatile Markets. New Journal of Physics, 12, 085009.
[22]	Baba, K., Shibata, R. and Sibuya, M. (2004). Partial Correlation and Conditional Correlation as Measures of Conditional Independence. Australian & New Zealand Journal of Statistics, 46, 657–664.
[23]	Chakraborty, S. N., Alam, S., Milu, S. A. and Nobi A. (2021). Changes of Network Structure of the Stock Indices of S&P 500. AIP Conference Proceedings, 2327, 020026.
[24]	Shapira, Y., Kenett, D. Y. and Ben-Jacob, E (2009). The Index Cohesive Effect on Stock Market Correlations. The European Physical Journal B, 72, 657–669.
[25]	Mantegna, R. N. and Stanley, H. E (2000). An Introduction to Econophysics: Correlation and Complexity in Finance. Cambridge, UK, Cambridge University Press. https://doi.org/10.1063/5.0039405.
[26]	Nobi, A. and Lee, J. W. (2017). Systemic Risk and Hierarchical Transitions of Financial Networks. Chaos 27, 063107.
[27]	Nobi, A., Lee, S., KIM, D. H. and Lee, J. W. (2014). Correlation and Network Topologies in Global and Local Stock Indices, Physics Letters A, 378 (34), 2482–2489.
[28]	Nobi, A., Maeng, S. E., Ha, G. G. and Lee, J. W. (2014). Effects of Global Financial Crisis on Network Structure in Local Stock Market. Physica A, 407, 135-143.
[29]	Wang. G., Xie, C., and Stanley, H. E. (2018). Correlation Structure and Evolution of World Stock Market: Evidence from Pearson Partial Correlation Based Networks. Computational Economics, 51 (3): 607-635. DOI: 10.1007/s10614-016-9627-7.

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APA Style

Shafiqul Alam, Nahid Akter, Mohammad Rubel Miah, Mohammed Javed Hossain, Ashadun Nobi. (2021). Dynamic of the States of Three Different Stock Markets from Correlation and Partial Correlation Changes. International Journal of Business and Economics Research, 10(4), 155-161. https://doi.org/10.11648/j.ijber.20211004.16

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ACS Style

Shafiqul Alam; Nahid Akter; Mohammad Rubel Miah; Mohammed Javed Hossain; Ashadun Nobi. Dynamic of the States of Three Different Stock Markets from Correlation and Partial Correlation Changes. Int. J. Bus. Econ. Res. 2021, 10(4), 155-161. doi: 10.11648/j.ijber.20211004.16

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AMA Style

Shafiqul Alam, Nahid Akter, Mohammad Rubel Miah, Mohammed Javed Hossain, Ashadun Nobi. Dynamic of the States of Three Different Stock Markets from Correlation and Partial Correlation Changes. Int J Bus Econ Res. 2021;10(4):155-161. doi: 10.11648/j.ijber.20211004.16

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@article{10.11648/j.ijber.20211004.16,
  author = {Shafiqul Alam and Nahid Akter and Mohammad Rubel Miah and Mohammed Javed Hossain and Ashadun Nobi},
  title = {Dynamic of the States of Three Different Stock Markets from Correlation and Partial Correlation Changes},
  journal = {International Journal of Business and Economics Research},
  volume = {10},
  number = {4},
  pages = {155-161},
  doi = {10.11648/j.ijber.20211004.16},
  url = {https://doi.org/10.11648/j.ijber.20211004.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijber.20211004.16},
  abstract = {The core focus of the study is to examine financial states using index effect on stock to stock correlations of developed, developing and emerging market. The three markets such as S&P 500, KOSPI 200 and DSE are declared as developed, developing and emerging market respectively. To study the similarity between stock price changes, we calculate the time series of the daily log return. Closing stock prices of the targeted markets have been used to measure the daily return of the stocks. To analyze the market mobility, Pearson correlation coefficient, partial correlation, and index effect on stock to stock correlation techniques have been applied. The study found that the companies of developed and emerging market are more strongly correlated than those of developing market during big crash. On the other hand, developing market shows less index effect on stock correlations during crisis. Moreover, insignificant index effect has been found in emerging market during calm state. No significant effect of DSE index on stock to stock correlations in the period of global financial crisis has been observed, implying that global financial crisis did not hit to the DSE in this period. Before the market crash, the interactions between stocks became low enough which corresponds to lower value of average correlation for all types of market. Finally, the change of correlation and partial correlation can be a good indicator to identify and predict the financial states of all the markets which will further helps the stakeholders to make proper economic decisions.},
 year = {2021}
}

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TY  - JOUR
T1  - Dynamic of the States of Three Different Stock Markets from Correlation and Partial Correlation Changes
AU  - Shafiqul Alam
AU  - Nahid Akter
AU  - Mohammad Rubel Miah
AU  - Mohammed Javed Hossain
AU  - Ashadun Nobi
Y1  - 2021/08/18
PY  - 2021
N1  - https://doi.org/10.11648/j.ijber.20211004.16
DO  - 10.11648/j.ijber.20211004.16
T2  - International Journal of Business and Economics Research
JF  - International Journal of Business and Economics Research
JO  - International Journal of Business and Economics Research
SP  - 155
EP  - 161
PB  - Science Publishing Group
SN  - 2328-756X
UR  - https://doi.org/10.11648/j.ijber.20211004.16
AB  - The core focus of the study is to examine financial states using index effect on stock to stock correlations of developed, developing and emerging market. The three markets such as S&P 500, KOSPI 200 and DSE are declared as developed, developing and emerging market respectively. To study the similarity between stock price changes, we calculate the time series of the daily log return. Closing stock prices of the targeted markets have been used to measure the daily return of the stocks. To analyze the market mobility, Pearson correlation coefficient, partial correlation, and index effect on stock to stock correlation techniques have been applied. The study found that the companies of developed and emerging market are more strongly correlated than those of developing market during big crash. On the other hand, developing market shows less index effect on stock correlations during crisis. Moreover, insignificant index effect has been found in emerging market during calm state. No significant effect of DSE index on stock to stock correlations in the period of global financial crisis has been observed, implying that global financial crisis did not hit to the DSE in this period. Before the market crash, the interactions between stocks became low enough which corresponds to lower value of average correlation for all types of market. Finally, the change of correlation and partial correlation can be a good indicator to identify and predict the financial states of all the markets which will further helps the stakeholders to make proper economic decisions.
VL  - 10
IS  - 4
ER  -

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Author Information

Shafiqul Alam

Department of Business Administration, Noakhali Science and Technology University, Noakhali, Bangladesh
Nahid Akter

Department of Computer Science and Telecommunication Engineering, Noakhali Science and Technology University, Noakhali, Bangladesh
Mohammad Rubel Miah

Department of Business Administration, Noakhali Science and Technology University, Noakhali, Bangladesh
Mohammed Javed Hossain

Department of Computer Science and Telecommunication Engineering, Noakhali Science and Technology University, Noakhali, Bangladesh
Ashadun Nobi

Department of Computer Science and Telecommunication Engineering, Noakhali Science and Technology University, Noakhali, Bangladesh

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APA Style

Shafiqul Alam, Nahid Akter, Mohammad Rubel Miah, Mohammed Javed Hossain, Ashadun Nobi. (2021). Dynamic of the States of Three Different Stock Markets from Correlation and Partial Correlation Changes. International Journal of Business and Economics Research, 10(4), 155-161. https://doi.org/10.11648/j.ijber.20211004.16

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ACS Style

Shafiqul Alam; Nahid Akter; Mohammad Rubel Miah; Mohammed Javed Hossain; Ashadun Nobi. Dynamic of the States of Three Different Stock Markets from Correlation and Partial Correlation Changes. Int. J. Bus. Econ. Res. 2021, 10(4), 155-161. doi: 10.11648/j.ijber.20211004.16

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AMA Style

Shafiqul Alam, Nahid Akter, Mohammad Rubel Miah, Mohammed Javed Hossain, Ashadun Nobi. Dynamic of the States of Three Different Stock Markets from Correlation and Partial Correlation Changes. Int J Bus Econ Res. 2021;10(4):155-161. doi: 10.11648/j.ijber.20211004.16

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@article{10.11648/j.ijber.20211004.16,
  author = {Shafiqul Alam and Nahid Akter and Mohammad Rubel Miah and Mohammed Javed Hossain and Ashadun Nobi},
  title = {Dynamic of the States of Three Different Stock Markets from Correlation and Partial Correlation Changes},
  journal = {International Journal of Business and Economics Research},
  volume = {10},
  number = {4},
  pages = {155-161},
  doi = {10.11648/j.ijber.20211004.16},
  url = {https://doi.org/10.11648/j.ijber.20211004.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijber.20211004.16},
  abstract = {The core focus of the study is to examine financial states using index effect on stock to stock correlations of developed, developing and emerging market. The three markets such as S&P 500, KOSPI 200 and DSE are declared as developed, developing and emerging market respectively. To study the similarity between stock price changes, we calculate the time series of the daily log return. Closing stock prices of the targeted markets have been used to measure the daily return of the stocks. To analyze the market mobility, Pearson correlation coefficient, partial correlation, and index effect on stock to stock correlation techniques have been applied. The study found that the companies of developed and emerging market are more strongly correlated than those of developing market during big crash. On the other hand, developing market shows less index effect on stock correlations during crisis. Moreover, insignificant index effect has been found in emerging market during calm state. No significant effect of DSE index on stock to stock correlations in the period of global financial crisis has been observed, implying that global financial crisis did not hit to the DSE in this period. Before the market crash, the interactions between stocks became low enough which corresponds to lower value of average correlation for all types of market. Finally, the change of correlation and partial correlation can be a good indicator to identify and predict the financial states of all the markets which will further helps the stakeholders to make proper economic decisions.},
 year = {2021}
}

Copy | Download

TY  - JOUR
T1  - Dynamic of the States of Three Different Stock Markets from Correlation and Partial Correlation Changes
AU  - Shafiqul Alam
AU  - Nahid Akter
AU  - Mohammad Rubel Miah
AU  - Mohammed Javed Hossain
AU  - Ashadun Nobi
Y1  - 2021/08/18
PY  - 2021
N1  - https://doi.org/10.11648/j.ijber.20211004.16
DO  - 10.11648/j.ijber.20211004.16
T2  - International Journal of Business and Economics Research
JF  - International Journal of Business and Economics Research
JO  - International Journal of Business and Economics Research
SP  - 155
EP  - 161
PB  - Science Publishing Group
SN  - 2328-756X
UR  - https://doi.org/10.11648/j.ijber.20211004.16
AB  - The core focus of the study is to examine financial states using index effect on stock to stock correlations of developed, developing and emerging market. The three markets such as S&P 500, KOSPI 200 and DSE are declared as developed, developing and emerging market respectively. To study the similarity between stock price changes, we calculate the time series of the daily log return. Closing stock prices of the targeted markets have been used to measure the daily return of the stocks. To analyze the market mobility, Pearson correlation coefficient, partial correlation, and index effect on stock to stock correlation techniques have been applied. The study found that the companies of developed and emerging market are more strongly correlated than those of developing market during big crash. On the other hand, developing market shows less index effect on stock correlations during crisis. Moreover, insignificant index effect has been found in emerging market during calm state. No significant effect of DSE index on stock to stock correlations in the period of global financial crisis has been observed, implying that global financial crisis did not hit to the DSE in this period. Before the market crash, the interactions between stocks became low enough which corresponds to lower value of average correlation for all types of market. Finally, the change of correlation and partial correlation can be a good indicator to identify and predict the financial states of all the markets which will further helps the stakeholders to make proper economic decisions.
VL  - 10
IS  - 4
ER  -

Copy | Download