An exactly solvable correlated stochastic process in finite time

作者: Jongwook Kim , Junghyo Jo

DOI: 10.1016/J.PHYSA.2014.03.055

关键词:

摘要: Abstract We propose a correlated stochastic process of which the novel non-Gaussian probability mass function is constructed by exactly solving moment generating function. The calculation cumulants and auto-correlation shows that convergent scale invariant in large but finite time limit. demonstrate model infers correlation strength discrete time-series data, predicts data distribution with high precision regime.

参考文章(15)
Stefan Mittnik, Svetlozar T. Rachev, Stable Paretian Models in Finance ,(2000)
Didier Sornette, Critical Phenomena in Natural Sciences Springer Series in Synergetics. ,(2000) , 10.1007/978-3-662-04174-1
Albert-László Barabási, Réka Albert, Emergence of Scaling in Random Networks Science. ,vol. 286, pp. 509- 512 ,(1999) , 10.1126/SCIENCE.286.5439.509
Klaus Lehnertz, Christian E. Elger, Can Epileptic Seizures be Predicted? Evidence from Nonlinear Time Series Analysis of Brain Electrical Activity Physical Review Letters. ,vol. 80, pp. 5019- 5022 ,(1998) , 10.1103/PHYSREVLETT.80.5019
Benoit B. Mandelbrot, John W. Van Ness, Fractional Brownian Motions, Fractional Noises and Applications Siam Review. ,vol. 10, pp. 422- 437 ,(1968) , 10.1137/1010093
Jean-Michel Courtault, Yuri Kabanov, Bernard Bru, Pierre Crepel, Isabelle Lebon, Arnaud Le Marchand, Louis Bachelier on the Centenary of Théorie de la Spéculation Mathematical Finance. ,vol. 10, pp. 339- 353 ,(2000) , 10.1111/1467-9965.00098
Bernard Friedman, A simple urn model Communications on Pure and Applied Mathematics. ,vol. 2, pp. 59- 70 ,(1949) , 10.1002/CPA.3160020103
Pierre-Gilles de Gennes, Introduction to polymer dynamics ,(1990)