# Synthetic Asset Usage Analytics

**Implementation Details**

**Class Names**

| Model Name                   | Parameters Class          | Data Class              |
| ---------------------------- | ------------------------- | ----------------------- |
| SyntheticAssetUsageAnalytics | SyntheticAssetQueryParams | SyntheticAssetUsageData |

**Import Statement**

```python
pythonCopyEditfrom satoshi_terminal.models.synthetic_asset_usage_analytics import (
    SyntheticAssetUsageAnalytics,
    SyntheticAssetQueryParams,
    SyntheticAssetUsageData,
)
```

***

**Parameters**

| Name          | Type                    | Description                                                                | Default              | Optional |
| ------------- | ----------------------- | -------------------------------------------------------------------------- | -------------------- | -------- |
| asset\_symbol | Union\[str, List\[str]] | Synthetic asset(s) to monitor (e.g., sETH, sUSD).                          | None                 | False    |
| usage\_metric | str                     | Specific metrics to track (e.g., "Transaction Volume," "Liquidity Depth"). | "Transaction Volume" | True     |
| time\_window  | int                     | Time window (in days) for tracking synthetic asset usage.                  | 7                    | True     |

***

**Data**

| Name             | Type         | Description                                               |
| ---------------- | ------------ | --------------------------------------------------------- |
| asset\_symbol    | str          | Symbol of the synthetic asset being analyzed.             |
| total\_volume    | float        | Total transaction volume of the synthetic asset (in USD). |
| liquidity\_depth | float        | Total liquidity available for the asset.                  |
| usage\_trends    | List\[float] | Historical usage trends over the specified time period.   |
| timestamp        | datetime     | Timestamp of the analysis.                                |

***

**Key Features**

* **Volume Analysis:** Tracks transaction volume for synthetic assets across platforms.
* **Liquidity Insights:** Highlights the availability of liquidity for synthetic asset trading.
* **Trend Monitoring:** Visualizes usage patterns over time to detect adoption trends.


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