Deterministic chaos and forecasting in Amazon’s share prices
Deterministic chaos and forecasting in Amazon’s share prices
Author(s): Michael Hanias, Stefanos Tsakonas, Lykourgos Magafas, Eleftherios I. Thalassinos , Loukas ZachilasSubject(s): Policy, planning, forecast and speculation, Financial Markets, ICT Information and Communications Technologies
Published by: Instytut Badań Gospodarczych
Keywords: time series; chaos theory; econophysics; forecasting;
Summary/Abstract: Research background: The application of non-linear analysis and chaos theory modelling on financial time series in the discipline of Econophysics. Purpose of the article: The main aim of the article is to identify the deterministic chaotic behavior of stock prices with reference to Amazon using daily data from Nasdaq-100. Methods: The paper uses nonlinear methods, in particular chaos theory modelling, in a case study exploring and forecasting the daily Amazon stock price. Findings & Value added: The results suggest that the Amazon stock price time series is a deterministic chaotic series with a lot of noise. We calculated the invariant parameters such as the maxi-mum Lyapunov exponent as well as the correlation dimension, managed a two-days-ahead forecast through phase space reconstruction and a grouped data handling method.
Journal: Equilibrium. Quarterly Journal of Economics and Economic Policy
- Issue Year: 15/2020
- Issue No: 2
- Page Range: 253-273
- Page Count: 21
- Language: English
