# Determining the number of factors in a forecast model by a random matrix test: cryptocurrencies

@article{Medina2019DeterminingTN, title={Determining the number of factors in a forecast model by a random matrix test: cryptocurrencies}, author={A. Medina and Graciela Gonz'alez-Far'ias}, journal={arXiv: Statistical Finance}, year={2019} }

We determine the number of statistically significant factors in a forecast model using a random matrices test. The applied forecast model is of the type of Reduced Rank Regression (RRR), in particular, we chose a flavor which can be seen as the Canonical Correlation Analysis (CCA). As empirical data, we use cryptocurrencies at hour frequency, where the variable selection was made by a criterion from information theory. The results are consistent with the usual visual inspection, with the… Expand

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