Calculate the Omega Ratio of an investment portfolio or asset’s returns.

The Omega Ratio is a risk-return measure that divides the sum of gains above a minimum acceptable return (MAR) by the sum of losses below it, capturing the full shape of the return distribution rather than only its first two moments (unlike the Sharpe Ratio).

The formula is as follows:

\[\text{Omega Ratio} = \operatorname{SUM}(\text{Gains above MAR}) / \operatorname{SUM}(\text{Losses below MAR})\]

See definition: https://en.wikipedia.org/wiki/Omega_ratio

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Calculate the Omega Ratio in Python

The Omega Ratio is available in the Performance module of the open-source Finance Toolkit. Install it with:

pip install financetoolkit -U

Then call get_omega_ratio as shown below.

from financetoolkit import Toolkit

toolkit = Toolkit(["AAPL", "TSLA"], api_key="FINANCIAL_MODELING_PREP_KEY")

toolkit.performance.get_omega_ratio()

Which returns:

  AAPL TSLA
2021 1.2354 1.1945
2022 0.892 0.8129
2023 1.4034 1.3043
2024 1.2462 1.2098
2025 1.0873 1.0871
2026 1.2062 0.9358

Parameters

get_omega_ratio accepts the following parameters:

  • period (str, optional): The period to use for the calculation. Defaults to “quarterly” if the Toolkit is initialised with quarterly=True, otherwise “yearly”.
  • within_period (bool, optional): Whether to calculate the Omega Ratio within the specified period or for the entire period. Thus whether to look at the Omega Ratio within a specific year (if period = ‘yearly’) or look at the entirety of all years. Defaults to True.
  • rolling (int, optional): The rolling window size to use for the calculation. If set, the Omega Ratio is calculated over a rolling window of this many periods across the full return history instead of per period. Defaults to None.
  • minimum_acceptable_return (float, optional): The minimum acceptable return (MAR) used as the threshold between gains and losses. Defaults to 0.0.
  • rounding (int, optional): The number of decimals to round the results to. Defaults to 4.
  • growth (bool, optional): Whether to calculate the growth of the ratios. Defaults to False.
  • lag (int | str, optional): The lag to use for the growth calculation. Defaults to 1.
  • standardize (bool, optional): Whether to standardize (Z-Score) the result. When combined with growth=True, standardizes the growth values instead of the raw values. Defaults to False.
Tracking Error Information Ratio Upside Capture Ratio Downside Capture Ratio Win Rate Kappa Ratio Gain-to-Pain Ratio Compound Growth Rate Returns Excess Return Correlation Matrix Covariance Matrix

The Performance module page introduces the module, and the sidebar lists all of its functions.

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