Abstract
The main purpose of this paper is to suggest daily bitcoin return model using a genetic algorithm and NARX neural network. We found that the genetic algorithm is effective to decide the architecture of the NARX neural network than information criteria-Akaike information criterion and the Schwarz information criterion using a Monte Carlo simulation and a hypothesis test. Finally, we forecasted daily bitcoin geometric return using this hybrid model of the genetic algorithm and NARX neural network and compare it with a feed-forward neural network forecasting model through a hypothesis test.
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