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http://elibrary.kdpu.edu.ua/xmlui/handle/123456789/3151Повний запис метаданих
| Поле DC | Значення | Мова |
|---|---|---|
| dc.contributor.author | Bielinskyi, Andrii | - |
| dc.contributor.author | Семеріков, Сергій Олексійович | - |
| dc.contributor.author | Соловйова, Вікторія Володимирівна | - |
| dc.contributor.author | Соловйов, Володимир Миколайович | - |
| dc.date.accessioned | 2019-06-25T07:42:27Z | - |
| dc.date.available | 2019-06-25T07:42:27Z | - |
| dc.date.issued | 2019 | - |
| dc.identifier.citation | Bielinskyi A. Levy’s stable distribution for stock crash detecting [Electronic resource] / Andrii Bielinskyi, Serhiy Semerikov, Viktoria Solovieva and Vladimir Soloviev // The 8th International Conference on Monitoring, Modeling & Management of Emergent Economy (M3E2 2019). Odessa, Ukraine, May 22-24, 2019 / Eds. : S. Semerikov, V. Soloviev, L. Kibalnyk, O. Chernyak and H. Danylchuk // SHS Web of Conferences. – 2019. – Volume 65. – Article 06006. – Access mode : https://www.shs-conferences.org/articles/shsconf/abs/2019/06/shsconf_m3e22019_06006/shsconf_m3e22019_06006.html. – DOI : https://doi.org/10.1051/shsconf/20196506006 | uk |
| dc.identifier.issn | 2261-2424 | - |
| dc.identifier.other | DOI:10.1051/shsconf/20196506006 | - |
| dc.identifier.uri | http://elibrary.kdpu.edu.ua/xmlui/handle/123456789/3151 | - |
| dc.identifier.uri | https://doi.org/10.1051/shsconf/20196506006 | - |
| dc.description | 1. Podobnik, B., Valentinčič, A., Horvatić, D., Stanley, H.E.: Asymmetric Lévy flight in financial ratios. Proceedings of the National Academy of Sciences of the United States of America. 108(44), 17883– 17888 (2011). doi:10.1073/pnas.1113330108 2. Baruník, J., Vácha, L., Vošvrda, M.: Tail behavior of the Central European stock markets during the financial crisis. AUCO Czech Economic Review. 4(3), 281–295 (2010) 3. Bachelier, L.: Théorie de la spéculation. Annales scientifiques de l'École Normale Supérieure, Série 3. 17, 21–86 (1900). doi:10.24033/asens.476 4. Gopikrishnan, P., Plerou, V., Amaral, L.A.N., Meyer, M., Stanley, H.E.: Scaling of the distribution of fluctuations of financial market indices. Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics. 60(3), 5305–5316 (1999). doi:10.1103/PhysRevE.60.5305 5. Gabaix, X., Gopikrishnan, P., Plerou, V., Stanley, H.E.: A Theory of Power Law Distributions in Financial Market Fluctuations. Nature. 423(6937), 267–270 (2003) 6. Gabaix, X., Gopikrishnan, P., Plerou, V., Stanley, H.E.: Institutional Investors and Stock Market Volatility. Quarterly Journal of Economics. 121(2), 461–504 (2006). doi:10.3386/w11722 7. Mandelbrot, B.: The variation of certain speculative prices. The Journal of Business. 36(4), 394–419 (1963). doi:10.1086/294632 8. Levy, P.: Théorie des erreurs. La loi de Gauss et les lois exceptionnelles. Bulletin de la Société Mathématique de France. 52, 49–85 (1924) 9. Gnedenko, B.V., Kolmogorov, A.N.: Limit Distributions for Sums of Independent Random Variables. Addison-Wesley, Cambridge (1954) 10. Fama, E.F.: The Behavior of Stock-Market Prices. The Journal of Business. 38(1), 34–105 (1965). 11. Mantegna, R.N., Stanley, H.E.: Scaling behaviour in the dynamics of an economic index. Nature. 376, 46–49 (1995). 12. Weron, R.: Levy-stable distributions revisited: tail index > 2 does not exclude the Levy-stable regime. International Journal of Modern Physics C. 12(2), 209–223 (2001). 13. Koutrouvelis, I.A.: Regression-Type Estimation of the Parameters of Stable Laws. Journal of the American Statistical Association. 75(372), 918–928 (1980) 14. Brorsen, B.W., Yang, S.R.: Maximum Likelihood Estimates of Symmetric Stable Distribution Parameters. Communications in Statistics - Simulation and Computation. 19(4), 1459–1464 (1990). doi:10.1080/03610919008812928 15. Nolan, J.P.: Maximum likelihood estimation of stable parameters. In: Barndorff-Nielsen, O.E., Mikosch, T., Resnick, S.I. (eds.) Lévy Processes: Theory and Applications, pp. 379–400. Springer Science+Business Media, Boston (2001) 16. Fama, E.F., Roll, R.: Parameter estimates for symmetric stable distributions. Journal of the American Statistical Association. 66(334), 331–338 (1971). doi:10.2307/2283932 17. McCulloch, J.H.: Simple consistent estimators of stable distribution parameters. Communications in Statistics - Simulation and Computation. 15(4), 1109–1136 (1986) 18. Shao, M., Nikias, C. L.: Signal processing with fractional lower order moments: stable processes and their application. Proceedings of the IEEE. 81(7), 986–1010 (1993). doi: 10.1109/5.231338 19. Ma, X., Nikias, C.L.: Joint estimation of time delay and frequency delay in impulsive noise using fractional lower order statistics. IEEE Transactions on Signal Processing. 43(11), 2669–2687 (1996). doi:10.1109/78.542175 20. Nicolas, J.-M., Anfinsen, S. N.: Introduction to second kind statistics: Application of log-moments and log-cumulants to the analysis of radar image distributions. Traitement du Signal. 19(3), 139–167 (2002) 21. Kuruoğlu, E.E.: Density parameter estimation of skewed α-stable distributions. IEEE Transactions on Signal Processing. 49(10), 2192–2201 (2001). doi:10.1109/78.950775 22. DuMouchel, W.H.: On the Asymptotic Normality of the Maximum Likelihood Estimate When Sampling from a Stable Distribution. The Annals of Statistics 1(5), 948–957 (1973) 23. Zolotarev, V.M.: One-dimensional Stable Distributions. American Mathematical Society, Providence (1986) 24. Chambers, J.M., Mallows, C.L., Stuck, B.W.: A Method for Simulating Stable Random Variables: Journal of the American Statistical Association. 71(354), 340–344 (1976). 25. Koutrouvelis, I.A.: An iterative procedure for the estimation of the parameters of stable laws: An iterative procedure for the estimation. Communications in Statistics - Simulation and Computation. 10(1), 17–28 (1981). doi:10.1080/03610918108812189 26. Arnold, V.I., Avez, A.: Ergodic problems of classical mechanics. Benjamin, New York (1968). doi:zamm.19700500721 27. Umeno, K.: Ergodic transformations on R preserving Cauchy laws. Nonlinear Theory and Its Applications. 7(1), 14–20 (2016). doi:10.1587/nolta.7.14 28. Charles, A., Darné, O.: Large shocks in the volatility of the Dow Jones Industrial Average index: 1928– 2013. Journal of Banking & Finance. 43(C), 188– 199 (2014). doi:10.1016/j.jbankfin.2014.03.022 29. Duarte, F.B., Tenreiro Machado, J.A., Monteiro Duarte, G.: Dynamics of the Dow Jones and the NASDAQ stock indexes. Nonlinear Dynamics. 61(4), 691–705 (2010). doi:10.1007/s11071-010- 9680-z 30. Soloviev, V.M., Chabanenko, D.M.: Dynamika parametriv modeli Levi dlia rozpodilu prybutkovostei chasovykh riadiv svitovykh fondovykh indeksiv (Dynamics of parameters of the Levy model for distribution of profitability of time series of world stock indexes). In: Pankratova, E.D. (ed.) Proceedings of 16-th International Conference on System Analysis and Information Technologies (SAIT 2014), Kyiv, Ukraine, May 26-30, 2014. ESC “IASA” NTUU “KPI”, Kyiv (2014) 31. Soloviev, V., Solovieva, V., Chabanenko, D.: Dynamics of α-stable Levi process parameters for returns distribution of the financial time series. In: Chernyak, O.I., Zakharchenko, P.V. (eds.) Contemporary concepts of forecasting the development of complex socio-economic systems, pp. 257–264. FO-P Tkachuk O.V, Berdyansk (2014) 32. Fukunaga, T., Umeno, K.: Universal Lévy's stable law of stock market and its characterization. https://arxiv.org/pdf/1709.06279 (2018). Accessed 21 Mar 2019 | - |
| dc.description.abstract | In this paper we study the possibility of construction indicators-precursors relying on one of the most power-law tailed distributions – Levy’s stable distribution. Here, we apply Levy’s parameters for 29 stock indices for the period from 1 March 2000 to 28 March 2019 daily values and show their effectiveness as indicators of crisis states on the example of Dow Jones Industrial Average index for the period from 2 January 1920 to 2019. In spite of popularity of the Gaussian distribution in financial modeling, we demonstrated that Levy’s stable distribution is more suitable due to its theoretical reasons and analysis results. And finally, we conclude that stability α and skewness β parameters of Levy’s stable distribution which demonstrate characteristic behavior for crash and critical states, can serve as an indicator-precursors of unstable states. | uk |
| dc.language.iso | en | uk |
| dc.publisher | EDP Sciences | uk |
| dc.title | Levy’s stable distribution for stock crash detecting | uk |
| dc.type | Article | uk |
| Розташовується у зібраннях: | Кафедра інформатики та прикладної математики | |
Файли цього матеріалу:
| Файл | Опис | Розмір | Формат | |
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| shsconf_m3e22019_06006.pdf | Article | 409.84 kB | Adobe PDF | Переглянути/Відкрити |
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