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Table 5 Sets of variables used in the models

From: Forecasting and trading cryptocurrencies with machine learning under changing market conditions

Variables Returns Volatility Other trading variables Network Daily dummies # variables
Bitcoin
Linear BTC[− 1, − 2] RR[− 1] No No Yes 14
ETH[− 1] \(\sigma\)[− 1, − 2]
LTC[− 1]
Linear-binary BTC[− 1, …, − 7] RR[− 1] Yes Yes Yes 48
ETH[− 1, …, − 7] \(\sigma\)[− 1, …, − 7]
LTC[− 1, …, − 7]
RF BTC[− 1, − 2] RR[− 1] No No Yes 16
ETH[− 1, − 2] \(\sigma\)[− 1, − 2]
LTC[− 1, − 2]
RF-binary BTC[− 1, − 2] RR[− 1] No No Yes 14
ETH[− 1] \(\sigma\)[− 1, − 2]
LTC[− 1]
SVM BTC[− 1, − 2] RR[− 1] No No Yes 16
ETH[− 1, − 2] \(\sigma\)[− 1, − 2]
LTC[− 1, − 2]
SVM-binary BTC[− 1, − 2] RR[− 1] Yes Yes Yes 26
ETH[− 1] \(\sigma\)[− 1, − 2]
LTC[− 1]
Ethereum
Linear ETH[− 1, − 2] RR[− 1] No No Yes 14
BTC[− 1] \(\sigma\)[− 1, − 2]
LTC[− 1]
Linear-binary ETH[− 1, − 2, − 3] RR[− 1] Yes Yes Yes 32
BTC[− 1, − 2, − 3] \(\sigma\)[− 1, − 2, − 3]
LTC[− 1, − 2, − 3]
RF ETH[− 1, − 2] RR[− 1] No No Yes 16
BTC[− 1, − 2] \(\sigma\)[− 1, − 2]
LTC[− 1, − 2]
RF-binary ETH[− 1, − 2] RR[− 1] No No Yes 16
BTC[− 1, − 2] \(\sigma\)[− 1, − 2]
LTC[− 1, − 2]
SVM ETH[− 1, …, − 4] RR[− 1] No No Yes 24
BTC[− 1, …,-4] \(\sigma\)[− 1, …, − 4]
LTC[− 1, …,-4]
SVM-binary ETH[− 1, …, − 5] RR[− 1] No No Yes 28
BTC[− 1, …, − 5] \(\sigma\)[− 1, …, − 5]
LTC[− 1, …, − 5]
Litecoin
Linear LTC[− 1, …, − 6] RR[− 1] No No Yes 32
BTC[− 1, …, − 6] \(\sigma\)[− 1, …, − 6]
ETH[− 1, …, − 6]
Linear-binary LTC[− 1, …, − 6] RR[− 1] Yes Yes Yes 44
BTC[− 1, …, − 6] \(\sigma\)[− 1, …, − 6]
ETH[− 1, …, − 6]
RF LTC [− 1, − 2] RR[− 1] No No Yes 16
BTC[− 1, − 2] \(\sigma\)[− 1, − 2]
ETH[− 1, − 2]
RF-binary LTC [− 1] RR[− 1] No No Yes 12
BTC[− 1] \(\sigma\)[− 1]
RTH [− 1]
SVM LTC [− 1, …, − 5] RR[− 1] Yes Yes Yes 40
BTC[− 1, …, − 5] \(\sigma\)[− 1, …, − 5]
ETH[− 1, …, − 5]
SVM-binary LTC [− 1, − 2,-3] RR[− 1] No No Yes 20
BTC[− 1, − 2,-3] \(\sigma\)[− 1, − 2, − 3]
ETH[− 1, − 2,-3]
  1. This table shows the best input sets obtained in the validation sample, i.e. those variables that maximize the 1-step out-of-sample average return, based on a rolling window with a length of 648 days. These sets of variables are then used in the test sample. The second column refers to the lagged returns of the three cryptocurrencies, which could go up to lag 7. The third column refers to two volatility estimators of the dependent cryptocurrency, namely the relative price range, \(RR_{t}\), and the range estimator of Parkinson (1980), \(\sigma_{t}\). For the first estimator only the first lag is used, while for \(\sigma_{t}\) it was considered a maximum lag structure up to lag 7. The number of lags used in these variables are in squared brackets. The fourth column refers to other trading variables, namely the daily trading volume and market capitalization. The fifth column refers to network variables. All the models that include these variables, consider a subset of the initial network variables, however all these subsets do not include the median transaction value and the number of transactions on the public blockchain. The sixth column refers to dummies corresponding to the day-of-the-week.