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Entropy analysis of dynamic properties of regional stock markets

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dc.contributor.author Danylchuk, H.
dc.contributor.author Derbentsev, V.
dc.contributor.author Соловйов, Володимир Миколайович
dc.contributor.author Sharapov, A.
dc.date.accessioned 2017-07-29T18:14:49Z
dc.date.available 2017-07-29T18:14:49Z
dc.date.issued 2016
dc.identifier.citation Danylchuk H. B. Entropy analysis of dynamic properties of regional stock markets / H. Danylchuk, V. Derbentsev, V. Soloviev, A. Sharapov // Science and Education a New Dimension. Economics. – 2016. – Vol. IV (2). – Issue: 94. – P. 15-19. uk
dc.identifier.issn 2308-5258
dc.identifier.uri http://elibrary.kdpu.edu.ua/handle/0564/1154
dc.identifier.uri https://doi.org/10.31812/0564/1154
dc.description 1. Sornette D. (2003) Why Stock Markets Crash: Critical Events in Complex Financial Systems. Princeton University Press. 2. Peters, E. E. (1994). Fractal Market Analysis: Applying Chaos Theory to Investment and Economics. John Wiley and Sons. 3. Mantegna R. N. , Stanley H. E. (2000). An Introduction to Econophysics. – Cambridge: Cambridge University Press. 4. Derbentsev V., Serdyuk O., Soloviev V., Sharapov A. Synergetics and Econophysics Research Methods of Dynamic and Structural Properties of Economic Systems. Cherkasy: Brama-Ukraine, 2010. – 300 p. 5. Chyumak O. Entropy and Fractals in Data Analysis. Moscow: Regular and Chaotic Dynamics, 2011. – 164 p. 6. Weidlich W. Socio-Dynamics: A Systematic Approach to Mathematical Modelling in the Social Science. Taylor and Francis, London, 2002. 7. Soloviev V., Danilchuk H., Serdyuk O.A. Research of the crises phenomena on time series basis with help of entropy characteristics // Information Technologies, Management and Society. Theses of the International Conference. Information Technologies and Management. 2008 April 10- 11, Information System Institute, Riga, Latvia. – P.41-42. 8. Soloviev V., Serdyuk O. Using of wavelet entropy for analysis of complex economic systems // Econophysics Colloquium and beyond, Alcona, Italy, September 27-29, 2007. 9. Joshua S., Richman J., Moorman R. Physiological timeseries analysis using approximate entropy and sample entropy // Am. J Physiol. Heart Circ. Physiol. 278: H2039- H2049, 2000. 10. Pincus S.M. (1991) Approximate entropy as a measure of system complexity. Proc. Natl. Acad. Sci. Vol.88.  P. 2297-2301. 11. Tsallis C. Nonextensive Statistics: Theoretical, Experimental and Computational Evidences and Connections / C. Tsallis // Brazilian Journal of Physics. – Vol. 29. – №. 1. – March, 1999. 12. Tsallis C. Introduction to Nonextnsive Statistical Mechanics, Approaching a Complex Word / C. Tsallis // Springer, New York, 2009. – 382 p. 13. Rosson O.A, Blanco S, Yordanova J, et al. Wavelet entropy: a new tool for analysis of short duration brain electrical signals[J]. J Neurosci Meth, vol. 105, P. 65-75, Jan. 2001. 14. Quiroga, R.Q; Rosso, O.A; Basar E.; Schürmann M. Wavelet entropy in event-related potentials: A new method shows ordering of EEG oscillations. Biol. Cybern. 2001, 84, 291–299. 15. http://finance.yahoo.com.
dc.description.abstract This paper examines entropy analysis of regional stock markets. We propose and empirically demonstrate the effectiveness of using such entropy as sample entropy, wavelet and Tsallis entropy as a measure of uncertainty and instability of such complex systems as regional stock markets. Our results show that these entropy measures can be effectively used as crisis prediction indicators. uk
dc.language.iso en_US uk
dc.publisher Society for Cultural and Scientific Progress in Central and Eastern Europe uk
dc.subject complex systems uk
dc.subject time series uk
dc.subject regional stock market crisis uk
dc.subject non-regular dynamics uk
dc.subject entropy analysis uk
dc.subject sample entropy uk
dc.subject Tsallis entropy uk
dc.subject wavelet entropy uk
dc.title Entropy analysis of dynamic properties of regional stock markets uk
dc.title.alternative Энтропийный анализ динамических свойств региональных фондовых рынков uk
dc.type Article uk


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