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Determinacy vs Randomnicity in Socio-Economic Processes: Epistemological Concept

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Smart Technologies and Innovations in Design for Control of Technological Processes and Objects: Economy and Production (FarEastСon 2018)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 138))

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Abstract

Randomnicity in socio-economic systems are investigated in the article, from a conceptual point of view. It is shown that the impact of economic agents on the system is the main generator of the emergence of randomnicity in socio-economic processes. It is proposed an epistemological concept, according to which the anthropogenic nature of economic agents’ expectations and preferences, as well as the heterogeneity and heteromorphicity of their subsequent impacts on the socio-economic processes, is the main factor of impacts to the socio-economic system. Ontological aspects of formalization of economic agents’ expectations and preferences in socio-economic processes are considered.

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References

  1. Allais, M.: The economic science of today and global disequilibrium. In: Baldassarri, M., McCallum, J., Mundell, R. (eds.) Global Disequilibrium in the World Economy, pp. 25–38. Palgrave MacMillan, Basingstoke (2014)

    Google Scholar 

  2. Allen, B.: Generic existence of completely revealing equilibria for economies with uncertainty when prices convey information. Econometrica 49(5), 1173–1199 (1981)

    Article  MathSciNet  Google Scholar 

  3. Bollerslev, T.: Generalized autoregressive conditional heteroskedasticity. J. Econom. 31, 307–327 (1986)

    Article  MathSciNet  Google Scholar 

  4. Buse, D.P., Wu, Q.H.: IP Network-based Multi-agent Systems for Industrial Automation Information Management, Condition Monitoring and Control of Power Systems. Springer, London (2007)

    Google Scholar 

  5. Caballero, R., Krishnamurthy, A.: Collective risk management in a flight to quality episode. J. Finance 63(5), 2195–2230 (2008)

    Article  Google Scholar 

  6. Casdagli, M.: Chaos and deterministic versus stochastic non-linear modeling. J. Roy. Stat. Soc. 54, 167–182 (1991)

    Google Scholar 

  7. Daniel, К., Hirshleifer, D., Subrahmanyam, A.: Investor psychology and security market under- and overreaction. J. Finance 53, 1839–1885 (1998)

    Article  Google Scholar 

  8. De Laplace, P.-S.: A Philosophical Essay on Probabilities. Chapman & Hall, London (1902). http://bayes.wustl.edu/Manual/laplace_A_philosophical_essay_on_probabilities.pdf. Accessed 15 Jan 2018

  9. Ehnts, D., Álvarez, M.C.: The Theory of Reflexivity–a Non-Stochastic Randomness Theory for Business Schools Only? (2013). http://www.ipe-berlin.org/fileadmin/downloads/working_paper/ipe_working_paper_28.pdf. Accessed 25 Feb 2018

  10. Erdös, P., Rényi, A.: On the Evolution of Random Graphs, vol. 5, pp. 17–61. Publication of the Mathematical Institute of the Hungarian Academy of Sciences (1960)

    Google Scholar 

  11. Fama, E.: Market efficiency, long-term returns, and behavioral finance. J. Financ. Econ. 49, 283–306 (1998)

    Article  Google Scholar 

  12. Fokin, N.I.: Economy: In the Beginning it was Word. Randomness. http://dictionary-economics.ru/art-9. Accessed 27 Feb 2018

  13. Fuller, R.J.: Behavioral Finance and the Sources of Alpha (2000). http://www.fullerthaler.com/downloads/bfsoa.pdf. Accessed 12 Mar 2018

  14. Hansen, L.P., Sargent, T.J.: Three types of ambiguity. J. Monetary Econ. 59(5), 422–445 (2012)

    Article  Google Scholar 

  15. Hansen, P.R., Lunde, A.: A forecast comparison of volatility models: does anything beat a GARCH(1,1)? J. Appl. Econom. 20, 873–889 (2005)

    Article  MathSciNet  Google Scholar 

  16. Himoff, J., Rzevski, G., Skobelev, P.: Magenta technology: multi-agent logistics i-scheduler for road transportation. In: Proceedings of 5-th International Conference on Autonomous Agents and Multi Agent Systems, AAMAS Japan, May 2006

    Google Scholar 

  17. Jackson, M.O., Yariv, L.: Diffusion in Social Networks. Preprint Caltech (2005). http://www.hss.caltech.edu/~jacksonm/nettipping.pdf. Accessed 22 Mar 2018

  18. Kahneman, D., Tversky, A.: Prospect theory: an analysis of decision. Econometrica 47, 263–291 (1979)

    Article  Google Scholar 

  19. Knyazeva, E.N., Kurdyumov, S.P.: Synergetic as a New Worldview: Dialogue with I. Prigogine. Issues Philos. 12, 3–20 (1992)

    Google Scholar 

  20. Kussy, M.: Current volatility as a measure of market risk. Int. J. Risk Assess. Manage. 20(4), 333–349 (2017)

    Article  Google Scholar 

  21. Kussy, M.Yu.: Reflexivity as an attribute of the system complexity of the financial market. Proc. ISA RAS 65(2), 53–65 (2015)

    Google Scholar 

  22. Kussy, M.Yu.: Current Volatility. Methodological and Applied Aspects: Monograph. DIAIPI Publ., Simferopol (2015). (in  Russian) https://elibrary.ru/item.asp?id=30787480. Accessed 22 Mar 2018

  23. Kussy, M.Yu.: About Paradigms of Modern Economic and Mathematical Modeling. A collection of materials of the International Scientific and Practical Conference “Mathematical methods and models in the study of topical problems of the Russian economy”, P. II, pp. 88–95. Aeterna Publ., Ufa (2016). https://elibrary.ru/item.asp?id=26308497. Accessed 22 Mar 2018

  24. Levin, G.D.: Necessary and random in reality and knowledge. Philos. Sci. 20, 82–106 (2015)

    Google Scholar 

  25. Mandelbrot, B.: The Fractal Geometry of Nature. W. H. Freeman and Co, New York (1982). https://ordinatous.com/pdf/The_Fractal_Geometry_of_Nature.pdf. Accessed 21 Apr 2018

  26. Mandelbrot, B., Hudson, R.L.: The (Mis)Behavior of Markets: A Fractal View of Risk, Ruin, and Reward. Basic Books, New York (2004)

    MATH  Google Scholar 

  27. Manganelli, S., Engle, R.F.: Value at Risk Models in Finance. European Central Bank Working Paper Ser. no. 75, 40 p. (2001)

    Google Scholar 

  28. Mlodinow, L.: The Drunkard’s Walk: How Randomness Rules Our Lives. Pantheon Books, New York (2008)

    MATH  Google Scholar 

  29. Pincus, S.M.: Mathematics approximate entropy as a measure of system complexity. Proc. Natl. Acad. Sci. U.S.A. 88, 2297–2301 (1991)

    Article  Google Scholar 

  30. Popov, V.V., Scheglov, B.S., Usatova, Y.: Randomness in the system of dynamic categories. Philos. Law 1, 25–29 (2015)

    Google Scholar 

  31. Prigogine, I., Stengers, I.: The End of Certainty: Time Chaos and the New Low of Nature. Simon and Schuster Corp, New York (1997)

    Google Scholar 

  32. Radner, R.: Rational expectations equilibrium: generic existence and the information revealed by prices. Econometrica 47(3), 655–678 (1979)

    Article  MathSciNet  Google Scholar 

  33. Ruelle, D.: Chance and Chaos. Princeton University Press, Princeton (1991)

    Google Scholar 

  34. Shefrin, H., Statman, M.: The disposition to sell winners too early and ride losers too long: theory of evidence. J. Finance 40, 777–790 (1985)

    Article  Google Scholar 

  35. Shródinger, E.: Indeterminism and free will. Nature July 4, 13–14 (1936)

    Google Scholar 

  36. Soros, G.: The Alchemy of Finance. Wiley, New York (2003)

    Google Scholar 

  37. Tong, H.: Non-linear Time Series: A Dynamical System Approach. Oxford University Press, Oxford (1990)

    MATH  Google Scholar 

  38. Watts, A.: A dynamic model of network formation. Games Econ. Behav. 34, 331–341 (2001)

    Article  MathSciNet  Google Scholar 

  39. Zhou, B.: High-frequency data and volatility in foreign-exchange rates. J. Bus. Econ. Stat. 14(1), 45–52 (1996)

    MathSciNet  Google Scholar 

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Authors and Affiliations

  1. V.I. Vernadsky Crimean Federal University, Simferopol, Russian Federation

    M. Y. Kussy & O. L. Korolyov

Authors
  1. M. Y. Kussy
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  2. O. L. Korolyov
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Correspondence to M. Y. Kussy .

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  1. Department of Innovatics, Engineering School, Far Eastern Federal University (FEFU) , Vladivostok, Russia

    Denis B. Solovev

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Kussy, M.Y., Korolyov, O.L. (2020). Determinacy vs Randomnicity in Socio-Economic Processes: Epistemological Concept. In: Solovev, D. (eds) Smart Technologies and Innovations in Design for Control of Technological Processes and Objects: Economy and Production. FarEastСon 2018. Smart Innovation, Systems and Technologies, vol 138. Springer, Cham. https://doi.org/10.1007/978-3-030-15577-3_81

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