Abstract
Abstract The methodology for detecting chaos from a time series is able if stock market indexes or oil prices are the observables. The analysis of volatilities and returns require only a series of historical prices. Routines run in the Maple environment. The conveniences of the symbolic computation are decisive for studies in this line of research. This work extends the domain of application in Econophysics if the observables are prices of cryptocurrencies. The methods include the detection of chaos and randomness. Application of the computational routines provides conclusive results on the underlying dynamics of the Bitcoin market since 18 Jul. 2010 to 06 May 2019. These results include a direct comparison between the Dow Jones stock market and Bitcoin prices.
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