Beta
Calculate the Beta, a measurement that assess the systematic risk of a stock or investment.
Beta is a financial metric used to assess the systematic risk of a stock or investment in relation to the overall market. It provides valuable insights into how a particular asset’s returns tend to move in response to fluctuations in the broader market. A stock’s Beta is calculated by analyzing its historical price movements and their correlation with the movements of a market index, typically the benchmark index like the S&P 500.
The formula is as follows:
\[\text{Beta} = \text{Covariance of Asset Returns and Benchmark Returns} / \text{Variance of Benchmark Returns}\]For a given period, for example monthly, this translates into the following:
\[\text{Beta} = \text{Monthly Covariance of Asset Returns and Benchmark Returns} / \text{Monthly Variance of Benchmark Returns}\]See definition: https://en.wikipedia.org/wiki/Beta_(finance)
Also known as: market sensitivity, systematic risk.
Beta in Python
Install the Finance Toolkit with:
pip install financetoolkit -U
Then call get_beta as shown below.
from financetoolkit import Toolkit
toolkit = Toolkit(["AAPL", "AMZN"], api_key="FINANCIAL_MODELING_PREP_KEY")
toolkit.performance.get_beta()
Which returns:
| Date | AAPL | AMZN |
|---|---|---|
| 2021 | 1.3093 | 1.0276 |
| 2022 | 1.2989 | 1.6292 |
| 2023 | 1.1 | 1.5133 |
| 2024 | 0.9656 | 1.5442 |
| 2025 | 1.2485 | 1.3264 |
| 2026 | 0.7887 | 1.281 |
Parameters
The function accepts the following parameters:
- period (str, optional): The period to use for the calculation. Defaults to “quarterly” if the Toolkit is initialized with quarterly=True, otherwise “yearly”.
- rolling (int, optional): The rolling period to use for the calculation. If you select period = ‘monthly’ and set rolling to 12 you obtain the rolling 12-month Sharpe Ratio.
- 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.