Here, we show model performance in predicting the bitcoin price and their hyper-parameters.
DATE | CLOSE |
---|---|
2024-12-04 | 94,619.12 |
2024-12-11 | 95,997.80 |
2024-12-18 | 97,408.36 |
2024-12-25 | 98,839.70 |
For scoring, Root Mean Squared Error was used.
D+7 | D+14 | D+21 | D+28 |
---|---|---|---|
1,013.33 | 859.43 | 2,116.25 | 85.89 |
D+7 | D+14 | D+21 | D+28 |
---|---|---|---|
2,501.42 | 16,099.47 | 19,147.52 | 17,070.09 |
Below are choices made for the model setup.
(Determined by Forward Selection and heuristically based on the model's assumptions)
param | description | value |
---|---|---|
include_indices | Whether to include market indices. | True |
include_commodities | Whether to include commodities. | False |
include_currencies | Whether to include currencies. | False |
(Determined by Grid Search)
param | description | value |
---|---|---|
ohlc_ratio | Whether to add OHLC ratios of bitcoin price to the data. | True |
lags | List of lags to use. None, if no lags are used. | None |
(Determined by heuristically, considering the model's assumptions)
param | description | value |
---|---|---|
log | Whether to take the log of the data. | False |
diff | Whether to difference the data. | True |
normalize | Whether to normalize the data. | True |
(Determined by Grid Search)
param | description | value |
---|---|---|
num_leaves | The number of leaves in the tree. A smaller number of leaves may reduce overfitting. | 10 |
max_depth | The maximum depth of the tree. A negative value means no limit. | -1 |
min_data_in_leaf | The minimum number of data points required in a leaf. This is a regularization parameter. | 5 |
num_boost_round | The number of boosting rounds, or the number of trees in the ensemble. | 1 |