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
- standard
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
- OmegaModel
threshold
: float
omega
: float