> ## Documentation Index
> Fetch the complete documentation index at: https://systematica.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Frontiers

> systematica.portfolio.frontiers

## `FrontierAssetStats`

```python theme={null}
FrontierAssetStats(
    alpha: float = 0.05,
    a_sim: int = 100,
    beta: float = None,
    b_sim: int = None,
    kappa: float = 0.3,
    model: str = 'Classic',
    rm: str = 'MV',
    kelly: str = None,
    rf: float = 0.0,
    hist: bool = True,
    solver: str = 'CLARABEL',
    constraints: List[Dict[str, str]] = None,
    asset_classes: dict = _Nothing.NOTHING,
    config: Dict[str, Any] = _Nothing.NOTHING,
)
```

Class that creates a portfolio object with all properties needed to
calculate optimal portfolios.

Method generated by attrs for class BaseFrontier.

### Ancestors

* `systematica.portfolio.base.BaseFrontier`
* `abc.ABC`
* `riskfolio.src.Portfolio.Portfolio`

### Methods

#### `fit`

```python theme={null}
fit(
    self,
    market_returns: pandas.core.frame.DataFrame,
) ‑> systematica.portfolio.base.BaseFrontier
```

Calculate the inputs that will be used by the optimization method when
we select the input model `Classic`.

More information in the [Riskfolio Documentation](https://riskfolio-lib.readthedocs.io/en/latest/portfolio.html#Portfolio.Portfolio.assets_stats).

**Parameters**:

| Name             | Type           | Default | Description          |
| ---------------- | -------------- | ------- | -------------------- |
| `market_returns` | `pd.DataFrame` | `--`    | Market returns data. |

**Returns**:

| Type           | Description              |
| -------------- | ------------------------ |
| `BaseFrontier` | `BaseFrontier` instance. |