Deterministic Chaos and Forecasting in Amazon's Share Prices

• Autorzy: Michael Hanias , Stefanos Tsakonas , Lykourgos Magafas , Eleftherios I. Thalassinos , Loukas Zachilas
• Języki publikacji: EN

Abstrakty

EN

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 behaviour 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. (original abstract)

Słowa kluczowe

EN

Chaos theory; Forecasting; Time-series; Share price

PL

Teoria chaosu; Prognozowanie; Szeregi czasowe; Kurs akcji

• Czasopismo: Equilibrium
• Rocznik: 2020
• Tom: 15
• Numer: nr 2
• Strony: 253--273

Twórcy

autor

Michael Hanias

• International Hellenic University, Greece

autor

Stefanos Tsakonas

• University of Thessaly, Greece

autor

Lykourgos Magafas

• International Hellenic University, Greece

autor

Eleftherios I. Thalassinos

• University of Piraeus, Greece; University of Malta, Malta

autor

Loukas Zachilas

• University of Thessaly, Greece

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Identyfikatory

DOI

10.24136/eq.2020.012