Application of Chaos Theory in Incomplete Randomized Financial Analysis
International Journal of Economics, Finance and Management Sciences
Volume 6, Issue 6, December 2018, Pages: 306-310
Received: Jan. 4, 2019; Published: Jan. 5, 2019
Views 19      Downloads 26
Xuelin Xian, Department of Management, Shenzhen Institute of Information Technology, Shenzhen, China
Jiande Liu, Right Way Venture Capital, Shenzhen, China
Article Tools
Follow on us
In the new economy, some tech companies have rapidly built market power and modernization led to the unpredictable bank-to-client relationship. Moreover, financial markets are confronted with big data and as a result, digitization and further introduction of mathematical techniques and new models were brought into the financial industry. Uncertainty has increased markedly in the macroeconomic risk, payment systems, capital accumulation and investment. But so far, timid attempts are made to elucidate the possibilities of the chaos theory application in finance. To verify a theoretical model whether or not is an accurate representation of an empirically observed phenomenon is one of the most challenging investigations in the scientific field. The following study explores the problem related to incomplete randomized financial analysis. The behavior of financial market relates to the circumstances that are both internal and external. Chaos mathematics is an acute methodology to be applied in the analysis of the randomness in financial markets instead of completely randomized design. The completely randomized design places the emphasis on which the factor effects are constant and assumes the observation from experiments to be statistically independent. However, this hypothesis is often not realistic and practical. The correlated impact should not be ignored. This article attempts to clarify some points related to the possibility of using chaos theory in finance.
Incompletely Random, Chaos Theory, Human Social Activities, Modeling of Random Variables
To cite this article
Xuelin Xian, Jiande Liu, Application of Chaos Theory in Incomplete Randomized Financial Analysis, International Journal of Economics, Finance and Management Sciences. Vol. 6, No. 6, 2018, pp. 306-310. doi: 10.11648/j.ijefm.20180606.19
Dariusz J. Ropiak, “The Chaos Theory, Approach, Methods.”2018, pp. 1-4.
Tang Rui, Nilanjan Dey, Simon Fong, “Metaheuristics and Chaos Theory.”2018, pp. 1-18.
Igor Klioutchnikov, Mariia Sigova, Nikita Beizerov, “Chaos Theory in Finance.” Procedia Computer Science, 2017, pp. 368-375.
Vieira, Ernesto Jose, Martins, Henrique Cordeiro, Goncalves, Carlos Alberto, “Applicability of Chaos theory in organizations.” 2014, pp. 1-16.
Sai Venkatesh Balasubramanian, “Chaos Theory and Nonlinear Analysis for the Business Strategist.”, 2014.
K. Falconer, Fractal Geometry, Wiley, 2013.
P. Abry, P. Gonvalves and L. Vehel, Scaling, Fractals and Wavelets, Wiley, 2013.
K. Falconer, Fractal Geometry, Wiley, 2013.
A. Adekola & B. S. Sergi, Global Business Management, Ashgate, 2012.
FD Mcclure, JK Lee, “Uncertainties of method performance statistics based on a balanced completely randomized model inter laboratory study.” Journal of Aoac International, 2008.
Claire G. Gilmore, “Detecting Linear and Nonlinear Dependence in Stock Returns: New methods Derived from Chaos Theory.” Journal of Business Finance & Accounting 23 (9-10), 2008.
Antonio Politi, Annette Witt, “Fractal dimension of space-time chaos”, 2008.
Claire G. Gilmore, “An examination of nonlinear dependence in exchange rates, using recent methods from chaos theory.” Global Finance Journal 12(2001), pp. 139-151.
Max V. Moldovan, “Stochastic Modeling of Random Variables with an Application in Financial Risk Management.” 2003, pp. 1–116.
Mason, Robert L, Gunst, Richard F and Hess, James L “Statistical Design and Analysis of Experiments-Analysis of Completely Randomized Designs.”
C. Tricot, Curves and Fractal Dimension, Springer, 1995.
Science Publishing Group
NEW YORK, NY 10018
Tel: (001)347-688-8931