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Difference in nature of correlation between NASDAQ and BSE indices

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  • P. Manimaran
  • Prasanta K. Panigrahi
  • Jitendra. C. Parikh

Abstract

We apply a recently developed wavelet based approach to characterize the correlation and scaling properties of non-stationary financial time series. This approach is local in nature and it makes use of wavelets from the Daubechies family for detrending purpose. The built-in variable windows in wavelet transform makes this procedure well suited for the non-stationary data. We analyze daily price of NASDAQ composite index for a period of 20 years, and BSE sensex index, over a period of 15 years. It is found that the long-range correlation, as well as fractal behavior for both the stock index values differ from each other significantly. Strong non-statistical long-range correlation is observed in BSE index, whose removal revealed a Gaussian random noise character for the corresponding fluctuation. The NASDAQ index, on the other hand, showed a multifractal behavior with long-range statistical correlation.

Suggested Citation

  • P. Manimaran & Prasanta K. Panigrahi & Jitendra. C. Parikh, 2006. "Difference in nature of correlation between NASDAQ and BSE indices," Papers nlin/0601074, arXiv.org, revised Apr 2008.
  • Handle: RePEc:arx:papers:nlin/0601074
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    Cited by:

    1. Power, Gabriel J. & Turvey, Calum G., 2010. "Long-range dependence in the volatility of commodity futures prices: Wavelet-based evidence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(1), pages 79-90.
    2. Neeraj & Prasanta K. Panigrahi, 2016. "Causality and Correlations between BSE and NYSE indexes: A Janus Faced Relationship," Papers 1608.07796, arXiv.org.
    3. Pal, Mayukha & Satish, B. & Srinivas, K. & Rao, P. Madhusudana & Manimaran, P., 2015. "Multifractal detrended cross-correlation analysis of coding and non-coding DNA sequences through chaos-game representation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 596-603.
    4. Neeraj, & Panigrahi, Prasanta K., 2017. "Causality and correlations between BSE and NYSE indexes: A Janus faced relationship," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 481(C), pages 284-313.
    5. Manimaran, P. & Narayana, A.C., 2018. "Multifractal detrended cross-correlation analysis on air pollutants of University of Hyderabad Campus, India," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 228-235.
    6. Chakrabarty, Anindya & De, Anupam & Gunasekaran, Angappa & Dubey, Rameshwar, 2015. "Investment horizon heterogeneity and wavelet: Overview and further research directions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 45-61.
    7. Wang, Yudong & Liu, Li & Gu, Rongbao, 2009. "Analysis of efficiency for Shenzhen stock market based on multifractal detrended fluctuation analysis," International Review of Financial Analysis, Elsevier, vol. 18(5), pages 271-276, December.
    8. Kim, Hongseok & Oh, Gabjin & Kim, Seunghwan, 2011. "Multifractal analysis of the Korean agricultural market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4286-4292.
    9. Sayantan Ghosh & P. Manimaran & Prasanta K. Panigrahi, 2010. "Characterizing Multi-Scale Self-Similar Behavior and Non-Statistical Properties of Financial Time Series," Papers 1003.2539, arXiv.org, revised Dec 2010.
    10. Chen, Hongtao & Wu, Chongfeng, 2011. "Forecasting volatility in Shanghai and Shenzhen markets based on multifractal analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(16), pages 2926-2935.
    11. Pal, Mayukha & Madhusudana Rao, P. & Manimaran, P., 2014. "Multifractal detrended cross-correlation analysis on gold, crude oil and foreign exchange rate time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 452-460.
    12. Ghosh, Sayantan & Manimaran, P. & Panigrahi, Prasanta K., 2011. "Characterizing multi-scale self-similar behavior and non-statistical properties of fluctuations in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4304-4316.
    13. Pal, Mayukha & Kiran, V. Satya & Rao, P. Madhusudana & Manimaran, P., 2016. "Multifractal detrended cross-correlation analysis of genome sequences using chaos-game representation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 288-293.

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