Here, we show model performance in predicting the bitcoin price and their hyper-parameters.
| DATE | CLOSE |
|---|---|
| 2024-12-04 | 94,837.67 |
| 2024-12-11 | 87,917.41 |
| 2024-12-18 | 96,537.70 |
| 2024-12-25 | 98,313.26 |
For scoring, Root Mean Squared Error was used.
| D+7 | D+14 | D+21 | D+28 |
|---|---|---|---|
| 305.96 | 1,806.76 | 414.08 | 3,702.32 |
| D+7 | D+14 | D+21 | D+28 |
|---|---|---|---|
| 3,231.14 | 18,001.30 | 19,412.95 | 22,653.99 |
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. | False |
| 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. | False |
| lags | List of lags to use. None, if no lags are used. | [7] |
(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 |
|---|---|---|
| criterion | Function for splitting the tree. | squared_error |
| max_depth | The maximum depth of the tree. | 5 |
| max_features | The number of features to consider when looking for the best split. Either int, or log2 (=log2(num features)) or sqrt (= sqrt(num features)). | log2 |
| min_samples_split | The minimum number of samples required to split an internal node. | 5 |
| min_samples_leaf | The minimum number of samples required to be at a leaf node. | 3 |