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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.

target: str
Target column name.

threshold_start: float
Start threshold, by default 0.0

threshold_end: float
Default: 1.5
End threshold, by default 1.5

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

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