Nonlinear and Chaotic Time Series Analysis

Baki Ünal and Çağdaş Hakan Aladağ

Chapter 4 in Modeling and Advanced Techniques in Modern Economics, 2022, pp 67-104 from World Scientific Publishing Co. Pte. Ltd.

Abstract: This study introduces the techniques used in the analysis of nonlinear and deterministic time series. Since chaotic time series are nonlinear and deterministic, the techniques introduced here can be successfully applied to the analysis of chaotic time series. Chaotic time series differ from stochastic time series. Therefore, the analysis of both types of time series shows differences. In this work, for analyzing nonlinear deterministic time series, we present how the phase space is reconstructed, how chaos is detected, how noise is cleaned from the data and how the deterministic time series are estimated.

Keywords: Harmonic Regression; Periodograms; Consumer Price Index; Food Inflation; Turkey; Gaussian Distribution; Europe Union; GDP; Panel Data; Spatial Regression; Measurement Errors; Nonlinear Time Series; Chaotic Time Series; Weibull Distribution; Location Parameters; Fiducial Approach; Hypothesis Testing; Green Swan; Financial Stability; Annex II Countries; Financial Time Series; Kernels; Stock Index; Machine Learning; Statistical Learning; Optimization; WSAR Algorithm; Deep Neural Networks; Phyton; Parameter Estimation; COVID-19; Clustering Analyses; Artificial Neural Networks; Performance Criteria; Time Series Forecasting; Statistical Inference (search for similar items in EconPapers)
JEL-codes: C1 C4 C5 C6 C63 (search for similar items in EconPapers)
Date: 2022
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