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omega_ratio

Calculate the Omega Ratio.

The Omega Ratio is a sophisticated metric that goes beyond traditional performance measures by considering the probability of achieving returns above a given threshold. It offers a more nuanced view of risk and reward, focusing on the likelihood of success rather than just average outcomes.

Examples

from openbb import obb
# Get Omega Ratio.
stock_data = obb.equity.price.historical(symbol="TSLA", start_date="2023-01-01", provider="fmp").to_df()
returns = stock_data["close"].pct_change().dropna()
obb.quantitative.performance.omega_ratio(data=returns, target="close")
obb.quantitative.performance.omega_ratio(target='close', data='[{'date': '2023-01-02', 'close': 0.05}, {'date': '2023-01-03', 'close': 0.08}, {'date': '2023-01-04', 'close': 0.07}, {'date': '2023-01-05', 'close': 0.06}, {'date': '2023-01-06', 'close': 0.06}]')

Parameters

data: list[openbb_core.provider.abstract.data.Data]

Time series data.

Optional: False


target: str

Target column name.

Optional: False


threshold_start: float

Start threshold, by default 0.0

Optional: True


threshold_end: float

End threshold, by default 1.5

Default: 1.5

Optional: True


Returns

results: list[OmegaModel]

Serializable results.


provider: None

Provider name.


warnings: Optional[list[Warning_]]

list of warnings.


chart: Optional[Chart]

Chart object.


extra: dict[str, Any]

Extra info.


Data

threshold: float

omega: float