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- W4288362138 abstract "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 advantage that the subjective element is avoided. Furthermore, the computational cost is minimal compared to the cross-validation approach." @default.
- W4288362138 created "2022-07-29" @default.
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- W4288362138 date "2019-05-01" @default.
- W4288362138 modified "2023-10-17" @default.
- W4288362138 title "Determining the number of factors in a forecast model by a random matrix test: cryptocurrencies" @default.
- W4288362138 doi "https://doi.org/10.48550/arxiv.1905.00545" @default.
- W4288362138 hasPublicationYear "2019" @default.
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