Deterministic chaos and forecasting in Amazon?s share prices
DOI:
https://doi.org/10.24136/eq.2020.012Keywords:
time series, chaos theory, econophysics, forecastingAbstract
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.
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