 Modeling the financial market with labyrinth chaosWiston Adrián Risso ()
Algorithmic Finance, 2019, vol. 8, issue 1-2, 57-75 Abstract: In the present study, a deterministic model is introduced to explain the stylized facts of financial data. The adaptation introduced by the labyrinth chaos model can reproduce phenomena such as heavy tails observed in financial returns, volatility clustering and jumps. The model is based on the assumption that many unstable stationary states arise from the interaction or feedback between financial prices. Model tests are performed, and the results show that the model generates series that reject a normal distribution of the returns and which can be represented by the GARCH model. An analysis applying symbolic dynamics shows similar behaviors in a system with three stock indices, three currency relations and three prices generated by the introduced model. We observe sequences that have not been produced by any of the three systems, suggesting that in a three-dimensional space, the paths traveled by the real series and those of the model may not be completely random. Keywords: Financial markets; stylized facts; volatility clustering; chaos; financial time series; brownian motion (search for similar items in EconPapers) There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ris:iosalg:0076 Access Statistics for this article Algorithmic Finance is currently edited by Phil Maymin More articles in Algorithmic Finance from IOS Press |
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