Open Access
SHS Web Conf.
Volume 65, 2019
The 8th International Conference on Monitoring, Modeling & Management of Emergent Economy (M3E2 2019)
Article Number 06006
Number of page(s) 7
Section Monitoring, Modeling, Forecasting and Preemption of Crisis in Socio-Economic Systems
Published online 29 May 2019
  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 [CrossRef] [Google Scholar]
  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) [Google Scholar]
  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 [Google Scholar]
  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 [Google Scholar]
  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) [CrossRef] [PubMed] [Google Scholar]
  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 [CrossRef] [Google Scholar]
  7. Mandelbrot, B.: The variation of certain speculative prices. The Journal of Business. 36(4), 394-419 (1963). doi:10.1086/294632 [CrossRef] [Google Scholar]
  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) [Google Scholar]
  9. Gnedenko, B.V., Kolmogorov, A.N.: Limit Distributions for Sums of Independent Random Variables. Addison-Wesley, Cambridge (1954) [Google Scholar]
  10. Fama, E.F.: The Behavior of Stock-Market Prices. The Journal of Business. 38(1), 34-105 (1965). [CrossRef] [Google Scholar]
  11. Mantegna, R.N., Stanley, H.E.: Scaling behaviour in the dynamics of an economic index. Nature. 376, 46-49 (1995). [NASA ADS] [CrossRef] [Google Scholar]
  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). [CrossRef] [Google Scholar]
  13. Koutrouvelis, I.A.: Regression-Type Estimation of the Parameters of Stable Laws. Journal of the American Statistical Association. 75(372), 918-928 (1980) [CrossRef] [Google Scholar]
  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 [Google Scholar]
  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) [Google Scholar]
  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 [CrossRef] [Google Scholar]
  17. McCulloch, J.H.: Simple consistent estimators of stable distribution parameters. Communications in Statistics - Simulation and Computation. 15(4), 1109-1136 (1986) [Google Scholar]
  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 [CrossRef] [Google Scholar]
  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 [Google Scholar]
  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) [Google Scholar]
  21. Kuruoǧlu, 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 [NASA ADS] [CrossRef] [Google Scholar]
  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) [CrossRef] [Google Scholar]
  23. Zolotarev, V.M.: One-dimensional Stable Distributions. American Mathematical Society, Providence (1986) [Google Scholar]
  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). [CrossRef] [MathSciNet] [Google Scholar]
  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 [Google Scholar]
  26. Arnold, V.I., Avez, A.: Ergodic problems of classical mechanics. Benjamin, New York (1968). doi:zamm.19700500721 [Google Scholar]
  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 [Google Scholar]
  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 [CrossRef] [Google Scholar]
  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 [CrossRef] [Google Scholar]
  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) [Google Scholar]
  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) [Google Scholar]
  32. Fukunaga, T., Umeno, K.: Universal Lévy’s stable law of stock market and its characterization. (2018). Accessed 21 Mar 2019 [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.