Consensus clustering of price correlation networks with ARIMA forecasts produces cryptocurrency portfolios that deliver stable positive returns and tighter tail-risk control up to 14-day holding periods.
Akaike, A new look at the statistical model identification, IEEE transactions on automatic control 19 (6) (1974) 716–723
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Tuning and robustness check of model selection for binary latent block models on placement test data.
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Optimising cryptocurrency portfolios through stable clustering of price correlation networks
Consensus clustering of price correlation networks with ARIMA forecasts produces cryptocurrency portfolios that deliver stable positive returns and tighter tail-risk control up to 14-day holding periods.
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Examining the robustness of a model selection procedure in the binary latent block model through a language placement test data set
Tuning and robustness check of model selection for binary latent block models on placement test data.