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We apply the statistical sparse jump model, a recently devel-oped, interpretable and robust regime switching model, to infer key featuresthat drive the return dynamics of the largest cryptocurrencies. The algorithmjointly performs feature selection, parameter estimation, and state classifica-tion. Our large set of candidate features are partly based on cryptocurrency,sentiment and financial market We apply the statistical sparse jump model, a recently devel-oped, interpretable and robust regime switching model, to infer key featuresthat drive the return dynamics of the largest cryptocurrencies. The algorithmjointly performs feature selection, parameter estimation, and state classifica-tion. Our large set of candidate features are partly based on cryptocurrency,sentiment and financial marke
