| dc.creator | Hanias M., Tsakonas S., Magafas L., Thalassinos E.I., Zachilas L. | en |
| dc.date.accessioned | 2023-01-31T08:27:47Z | |
| dc.date.available | 2023-01-31T08:27:47Z | |
| dc.date.issued | 2020 | |
| dc.identifier | 10.24136/eq.2020.012 | |
| dc.identifier.issn | 1689765X | |
| dc.identifier.uri | http://hdl.handle.net/11615/73883 | |
| dc.description.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. © 2020, Institute of Economic Research. All rights reserved. | en |
| dc.language.iso | en | en |
| dc.source | Equilibrium. Quarterly Journal of Economics and Economic Policy | en |
| dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107152913&doi=10.24136%2feq.2020.012&partnerID=40&md5=7bece2bd918009315efbabafb09d1300 | |
| dc.subject | Institute of Economic Research | en |
| dc.title | Deterministic chaos and forecasting in amazon’s share prices | en |
| dc.type | journalArticle | en |