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# High-Frequency Dataset
# Introduction
This folder contains 2 examples
- A high-frequency dataset example
- An example of predicting the price trend in high-frequency data
## High-Frequency Dataset
This dataset is an example for RL high frequency trading.
## Get High-Frequency Data
### Get High-Frequency Data
Get high-frequency data by running the following command:
```bash
python workflow.py get_data
```
## Dump & Reload & Reinitialize the Dataset
### Dump & Reload & Reinitialize the Dataset
The High-Frequency Dataset is implemented as `qlib.data.dataset.DatasetH` in the `workflow.py`. `DatatsetH` is the subclass of [`qlib.utils.serial.Serializable`](https://qlib.readthedocs.io/en/latest/advanced/serial.html), whose state can be dumped in or loaded from disk in `pickle` format.
@@ -27,9 +32,9 @@ Run the example by running the following command:
python workflow.py dump_and_load_dataset
```
## Benchmarks Performance
### Signal Test
Here are the results of signal test for benchmark models. We will keep updating benchmark models in future.
## Benchmarks Performance (predicting the price trend in high-frequency data)
Here are the results of models for predicting the price trend in high-frequency data. We will keep updating benchmark models in future.
| Model Name | Dataset | IC | ICIR | Rank IC | Rank ICIR | Long precision| Short Precision | Long-Short Average Return | Long-Short Average Sharpe |
|---|---|---|---|---|---|---|---|---|---|