A Comprehensive Framework for Uncovering Non-Linearity and Chaos in Financial Markets: Empirical Evidence for Four Major Stock Market Indices

被引:13
|
作者
Inglada-Perez, Lucia [1 ]
机构
[1] Univ Complutense Madrid, Dept Stat & Operat Res, Plaza Ramon y Cajal S-N Ciudad Univ, Madrid 28040, Spain
关键词
nonlinear dynamics; chaos; time series analysis; stock exchange market; Lyapunov; recurrence plots; BDS; correlation dimension; GARCH model; TIME-SERIES; UNIT-ROOT; CONDITIONAL HETEROSKEDASTICITY; LYAPUNOV EXPONENTS; STRANGE ATTRACTORS; DYNAMICS; RETURNS; DETERMINISM; DIMENSION; EXCHANGE;
D O I
10.3390/e22121435
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The presence of chaos in the financial markets has been the subject of a great number of studies, but the results have been contradictory and inconclusive. This research tests for the existence of nonlinear patterns and chaotic nature in four major stock market indices: namely Dow Jones Industrial Average, Ibex 35, Nasdaq-100 and Nikkei 225. To this end, a comprehensive framework has been adopted encompassing a wide range of techniques and the most suitable methods for the analysis of noisy time series. By using daily closing values from January 1992 to July 2013, this study employs twelve techniques and tools of which five are specific to detecting chaos. The findings show no clear evidence of chaos, suggesting that the behavior of financial markets is nonlinear and stochastic.
引用
收藏
页码:1 / 26
页数:26
相关论文
共 2 条