dc.description |
1. Sornette, D.: Why Stock Markets Crash: Critical Events in Complex Systems. Princeton
University Press. (2003)
2. Zemba, W.T., Lieo, S., Zhitlukhin, M.: Stosk Market Crashes: Predictable and Unpredictable and What to Do About Them. World Scientific (2018) 3. Chen, L., Qiao, Z., Wang, M., Wang, C., Du, R., Stanley, H. E.: Which Artificial Intelligence Algorithm Better Predicts the Chinese Stock Market? IEEE Access 6, 48625-48633
(2018)
4. Chong, E., Han, C., Park, F. C.: Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies. Expert Systems With Applications 83, 187-205 (2017)
5. Li, S.I., Yoo, S.J.: Multimodal Deep Learning for Finance: Integrating and Forecasting International Stock Markets. https://arXiv:1903.06478v1 [q-fin.CP] ( 2019)
6. Wang, M., Zhao, L., Du, R., Wang, C., Chen, L., Tian, L., Stanley, H. E.: A novel hybrid
method of forecasting crude oil prices using complex network science and artificial intelligence algorithms. Applied Energy 220, 480–495 (2018)
7. Kaizoji, T., Sornette, D. Market Bubbles and Crashes. https://arXiv:0812.2449 [q-fin.RM]
(2008)
8. Filimonov, V., Demos, G., Sornette, D.: Modified Profile Likelihood Inference and Interval Forecast of the Burst of Financial Bubbles. Quantitative Finance 17(8), 1186 (2017)
https://doi.org/10.1080/14697688.2016.1276298
9. Fievet, L., Sornette, D.: Calibrating emergent phenomena in stock markets with agent
based models. PLoS ONE 13(3) : e0193290. https://doi.org/10.1371/journal.pone.0193290
10. Diaz, J.: Evidence of Noisy Chaotic Dynamics in the Returns of Four Dow Jones Stock Indices. Annual Review of Chaos Theory, Bifurcation and Dynamical System 4, 1-15 (2013)
11. Duarte, B., Machado, J., Duarte, M.: Dynamics of the Dow Jones and the NASDAQ Stock
Indexes 61(4), 691-705 (2010)
12. Newman, M. E. J.: Complex Systems: A Survey. American Journal of Physics 79, 800-810
(2011) https://doi.org/10.1119/1.3490372
13. Nikolis, G., Prigogine, I: Exploring complexity. An Introduction. W. H. Freeman and
Company, New York (1989)
14. Mantegna, N., Stanley, E.: An Introduction to Econophysics: Correlations and Complexity in Finance. Cambridge Univ. Press, Cambridge UK (2000)
15. Charles, A., Darne, O.: Large shocks in the volatility of the Dow Jones Industrial Average
index: 1928-2013. Journal of Banking & Finance 43, 188-199 (2014)
https://doi.org/10.1016/j.bankfin.2014.03.022
16. Gradojevic, N., Gencay, R.: Was it Expected? Aggregate Market Fears and Long Range
Dependence. Journal of Empirical Finance 17(2), 270-282 (2010)
http://dx.doi.org/10.2139/ssrn.959547
17. Danylchuk, H., Derbentsev, V., Soloviev, V., Sharapov, A.: Entropy analysis of dynamics
properties of regional stock market. Science and Education a New Dimension. Economics
4(2), 15-19 (2016)
18. Pele, T., Lazar, E., Dufour, A.: Information Entropy and Measures of Market Risk. Entropy 19(5), 1-19 (2017) https://doi.org/10.3390/e19050226
19. Lim, R.: Rapid Evaluation of Permutation Entropy for Financial Volatility Analysis – A
Novel Hash Function using Feature-Bias Divergence. Department of Computer Science,
Imperial College of London, London (2014)
20. Gu, R.: Multiscale Shannon Entropy and its application in the stock market. Physics A
484, 215-224 (2017)
21. Wang, G.-J., Xie, C., Han, F.: Multi-Scale Approximation Entropy Analysis of Foreign
Exchange Markets Efficiency. Systems Engineering Procedia 3, 201-208 (2012)
22. Fiedor, P.: Multiscale Analysis of the Predictability of Stock Returns. Risks 3(2), 219-233
(2015) https://doi.org/10.3390/risks3020219 23. Soloviev, V., Belinskiy, A.: Complex Systems and Crashes of Cryptocurrency Market. In:
Ermolayev, V., Suárez-Fgueroa, M., Yakovyna, V., Mayr, H., Nikitchenko, M., Spivakovsky, A. (eds.) on ITC in Education, Research, and Industrial Applications. CCIS, vol 1007,
pp 276-297. Springer, Cham (2018)
24. Bielinskyi, A., Soloviev, V.: Complex network precursors of crashes and critical events in
the cryptocurrency market. In: Kiv, A., Semerikov, S., Soloviev, V., Striuk, A. (eds) Proceedings of the 1st Student Workshop on Computer & Software Engnieering, CEUR
Workshop Proceedings (CEUR-WS.org), vol 2292, pp 37-45. Kryvyi Rig, Ukraine (2018)
25. Bandt, C., Pompe, B.: Permutation entropy: A natural complexity measure for time series.
Phys. Rev. Lett. 88(17), 2-4 (2002)
26. Shannon E.: A mathematical theory of communication. The Bell System Technical Journal
27(3), 379-423 (1948)
27. Kantz, H., Schreiber, T.: Nonlinear Time Series Analysis. 2
nd edition. Cambridge University Press, London (2003) http://doi.org/10.1017/CBO9780511755798
28. Tsallis C.: Nonextensive Statistics: Theoretical, Experimental and Computational Evidence and Connections. Brazilian Journal of Physics 29(1), 1-35 (1999)
http://doi.org/10.1590/S0130-97331999000100002
29. Costa, M., Goldberger, A., Peng, C.-K.: Multiscale Entropy Analysis of Complex Physiologic Time Series. Physical Review Letters 89(6), 068102 (2002) |
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