Veta
Calculate the veta of an option based on the Black Scholes Model. The Black Scholes Model is a mathematical model used to estimate the price of European-style options. The veta is the rate of change of the vega with respect to the time to expiration.
The veta calculation is the theoretical value of the veta. The actual veta can differ from this value due to several factors such as the volatility of the underlying asset, the time to expiration, the risk free rate and more.
The formula is as follows:
\[d_{1} = (\ln(S / K) + (r - q + (\sigma ^{2}) / 2) \cdot t) / (\sigma \cdot \sqrt{t})\] \[d_{2} = d_{1} - \sigma \cdot \sqrt{t}\] \[\text{Veta} = S \cdot e ^{- q \cdot t} \cdot N'(d_{1}) \cdot \sqrt{t} \cdot (q + ((r - q) \cdot d_{1}) / (\sigma \cdot \sqrt{t}) - (1 + d_{1} \cdot d_{2}) / (2 \cdot t)) / (100 \cdot 365)\]Where S is the stock price, K is the strike price, r is the risk free rate, q is the dividend yield, σ is the volatility, t is the time to expiration, N’(d1) is the standard normal probability density at d1 and N(d2) is the cumulative normal distribution of d2.
This expression equals dVega/dt, the change in Vega as calendar time passes (the negative of the derivative with respect to the remaining time to maturity t), and is used as is, without a change of sign. Veta thus, like Theta, Charm and Color, measures the change per unit of time that passes: an option close to the money loses Vega as expiry approaches, so its Veta is typically negative.
It is common practice to divide the mathematical result of veta by 100 times the number of days per year to express it as the change in Vega (per percentage point of volatility) per calendar day. This is also done here.
The Veta can be interpreted as follows:
- If Veta is positive, it indicates that the option’s Vega is becoming more positive over time. In other words, the option is gaining sensitivity to changes in implied volatility as time passes.
- If Veta is negative, it suggests that the option’s Vega is becoming more negative over time. The option is losing sensitivity to changes in implied volatility as time passes.
Also known as: vega time decay.
Veta in Python or via the MCP
Install the Finance Toolkit with:
pip install financetoolkit -U
Then call get_veta as shown below.
from financetoolkit import Toolkit
toolkit = Toolkit(
["AZO"],
api_key="FINANCIAL_MODELING_PREP_KEY",
start_date="2025-01-01",
end_date="2025-12-31",
)
toolkit.options.get_veta(
strike_price_range=0.1, strike_step_size=50
).loc["AZO", ["2026-01-07", "2026-01-14", "2026-01-28"]]
Or, after setting up the Finance Toolkit MCP, ask:
What was the veta of AutoZone's call options at the end of 2025 for the expiries of 7, 14 and 28 January 2026, for strikes within 10% of the share price in $50 steps?
Which returns:
| Strike Price | 2026-01-07 | 2026-01-14 | 2026-01-28 |
|---|---|---|---|
| 3050 | -0.0051 | -0.0325 | -0.0541 |
| 3100 | -0.0189 | -0.0561 | -0.0651 |
| 3150 | -0.051 | -0.0816 | -0.0722 |
| 3200 | -0.1 | -0.1011 | -0.0746 |
| 3250 | -0.1436 | -0.1082 | -0.0728 |
| 3300 | -0.1551 | -0.1037 | -0.0692 |
| 3350 | -0.1403 | -0.096 | -0.0664 |
| 3400 | -0.1344 | -0.0946 | -0.0665 |
| 3450 | -0.1525 | -0.1026 | -0.0701 |
| 3500 | -0.1688 | -0.1146 | -0.0762 |
| 3550 | -0.154 | -0.1213 | -0.0826 |
| 3600 | -0.1108 | -0.1163 | -0.0869 |
| 3650 | -0.063 | -0.0994 | -0.0875 |
| 3700 | -0.0288 | -0.0759 | -0.0835 |
Parameters
get_veta accepts the following parameters.
| Parameter | Type | Description | Example |
|---|---|---|---|
start_date | str | None | The date whose price, volatility and rates the values start from; a date without prices (a weekend or a holiday) uses the last trading day before it, and a ticker without a price on that day is left out with a warning. Defaults to None, which uses the last date of the historical data. | "2021-01-01" |
strike_price_range | float | The percentage range to use for the strike prices. Defaults to 0.25 which equals 25% and thus results in strike prices from 75 to 125 if the current stock price is 100. | 0.1 |
strike_step_size | int | The step size to use for the strike prices. Defaults to 5 which means that the strike prices will be 75, 80, 85, 90, 95, 100, 105, 110, 115 and 120 if the current stock price is 100. | 1 |
expiration_time_range | int | The number of days to use for the time to expiration: the columns are the expirations 1 up to expiration_time_range - 1 days after the start date. Defaults to 30, which gives expirations of 1 to 29 days. | 90 |
risk_free_rate | float | The risk free rate to use for the calculation. Defaults to None, which uses the Toolkit’s risk-free rate on the pricing date: the 10-year Treasury yield unless the Toolkit’s risk_free_rate parameter selects ‘13w’, ‘5y’ or ‘30y’, converted from its semi-annual bond-equivalent quote to continuous compounding. A rate passed here is used as given, as a continuously compounded rate. | 0.04 |
dividend_yield | float | The dividend yield to use for the calculation. Defaults to None which means it will use the current dividend yield. | 0.02 |
show_input_info | bool | Whether to show the input information. Defaults to False. | True |
rounding | int | None | The number of decimals to round the results to. Defaults to None, which uses the rounding of the Toolkit (4 unless set otherwise). | 2 |
standardize | bool | Whether to standardize (Z-Score) the result across the time to expiration columns for each ticker and strike price. Defaults to False. | True |