Recurrence Quantification Analysis of Wavelet Pre-Filtered Index Returns
Recurrence Quantification Analysis of Wavelet Pre-Filtered Index Returns
复制标题
DOI：
10.2139/ssrn.415361
复制
发表时间：
2003-06
期刊：
影响因子：
--
通讯作者：
Antonios Antoniou;Costas E. Vorlow
中科院分区：
文献类型：
--
作者：
Antonios Antoniou;Costas E. Vorlow
本文研究了金融时间序列中非随机的，可能是非线性的确定性动力周期的存在性。通过结合递归量化分析(RQA：参见Zbilut和Webber(J.Appl.太棒了。76(2)(1994)965))和小波滤波。定量和定性结果表明，通过小波预滤波，我们可以更清楚地了解收益率生成过程的潜在动力结构。我们的结果还表明高维确定性动力学、不稳定周期轨道和混沌的存在。
In this paper we investigate for the presence of non-stochastic, possibly nonlinear deterministic dynamical cycles in financial time series. Evidence of nonlinear dynamics is revealed in denoised daily stock market index returns for six countries by combining Recurrence Quantification Analysis (RQA: see Zbilut and Webber (J. Appl. Phys. 76(2) (1994) 965)) and wavelet filtering. Quantitative and qualitative results indicate that through wavelet pre-filtering we can obtain a clearer view of the underlying dynamical structure of returns generating processes. Our results also suggest the existence of high dimensional deterministic dynamics, unstable periodic orbits and chaos.