GJR-GARCH Volatility Model
Calculates volatility forecasts based on the GJR-GARCH model.
GJR-GARCH extends GARCH with a leverage term that lets negative shocks (bad news) raise volatility by more than positive shocks of the same size, a well documented asymmetry in equity returns that symmetric GARCH cannot capture.
For more information about the method, see the following paper:
- Glosten, L.R., Jagannathan, R., and Runkle, D.E. (1993). “On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks.” The Journal of Finance, 48(5), 1779-1801.
Also known as: GJR-GARCH, threshold GARCH, TGARCH.
GJR-GARCH Volatility Model in Python
Install the Finance Toolkit with:
pip install financetoolkit -U
Then call get_gjr_garch as shown below.
from financetoolkit import Toolkit
toolkit = Toolkit(["AMZN", "TSLA"], api_key="FINANCIAL_MODELING_PREP_KEY")
toolkit.risk.get_gjr_garch(period="quarterly")
Which returns:
| Date | AMZN | TSLA | Benchmark |
|---|---|---|---|
| 2024Q2 | 0.027 | 0.1542 | 0.0053 |
| 2024Q3 | 0.0267 | 0.1513 | 0.0047 |
| 2024Q4 | 0.0266 | 0.1642 | 0.0048 |
| 2025Q1 | 0.0264 | 0.1937 | 0.0046 |
| 2025Q2 | 0.027 | 0.1603 | 0.0065 |
| 2025Q3 | 0.0267 | 0.157 | 0.0053 |
| 2025Q4 | 0.0265 | 0.173 | 0.005 |
| 2026Q1 | 0.0264 | 0.1503 | 0.0046 |
| 2026Q2 | 0.0267 | 0.1506 | 0.0066 |
| 2026Q3 | 0.0265 | 0.1513 | 0.0061 |
Parameters
The function accepts the following parameters:
- period (str, optional): The data frequency for returns (daily, weekly, monthly, quarterly, or yearly). Defaults to “quarterly” if the Toolkit is initialized with quarterly=True, otherwise “yearly”.
- time_steps (int, optional): Time steps to calculate GJR-GARCH for.
- optimization_t (int, optional): Time steps to optimize GJR-GARCH for. It is only used if no weights are given.
- within_period (bool, optional): Whether to calculate GJR-GARCH within the specified period or for the entire period. Defaults to False.
- rounding (int | None, optional): The number of decimals to round the results to. Defaults to 4.
- growth (bool, optional): Whether to calculate the growth of the GJR-GARCH values over time. Defaults to False.
- lag (int | list[int], 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.