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Coupled Network Approach To Predictability Of Financial Market Returns And News Sentiments

Author

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  • CHESTER CURME

    (Center for Polymer Studies and Department of Physics, Boston University, 590 Commonwealth Avenue, Boston, MA 02215, USA)

  • H. EUGENE STANLEY

    (Center for Polymer Studies and Department of Physics, Boston University, 590 Commonwealth Avenue, Boston, MA 02215, USA)

  • IRENA VODENSKA

    (Administrative Sciences Department, Metropolitan College, Boston University, 808 Commonwealth, Avenue Boston, MA 02215, USA)

Abstract

We analyze the network structure of lagged correlations among daily financial news sentiments and returns of financial market indices of 40 countries from 2002 to 2012. Using a spectral method, we decompose the network into bipartite sub-structures, and show that these sub-structures are relevant to the performance of prediction models, bridging concepts from network theory and time series analysis. Our results suggest that, at the daily level, endogenous influences among financial markets overwhelm exogenous influences of news outlets, and that changes in financial news sentiments respond to market movements more substantially than they drive them.

Suggested Citation

  • Chester Curme & H. Eugene Stanley & Irena Vodenska, 2015. "Coupled Network Approach To Predictability Of Financial Market Returns And News Sentiments," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 18(07), pages 1-26, November.
    • Handle: RePEc:wsi:ijtafx:v:18:y:2015:i:07:n:s0219024915500430
    DOI: 10.1142/S0219024915500430
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    6. Liu, Nairong & An, Haizhong & Gao, Xiangyun & Li, Huajiao & Hao, Xiaoqing, 2016. "Breaking news dissemination in the media via propagation behavior based on complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 453(C), pages 44-54.
    7. de Resende, Charlene C. & Pereira, Adriano C.M. & Cardoso, Rodrigo T.N. & de Magalhães, A.R. Bosco, 2017. "Investigating market efficiency through a forecasting model based on differential equations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 199-212.
    8. Kiran Sharma & Anindya S. Chakrabarti & Anirban Chakraborti, 2018. "Multi-layered Network Structure: Relationship Between Financial and Macroeconomic Dynamics," Papers 1805.06829, arXiv.org, revised Mar 2019.
    9. Th'arsis T. P. Souza & Tomaso Aste, 2018. "Predicting future stock market structure by combining social and financial network information," Papers 1812.01103, arXiv.org.
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