Veta —
How Vega changes with the passage of time (Vega decay).
Quick Answer
Veta measures how an option's Vega decays as one day passes, holding all else constant. It explains why a long-dated Nifty option carries volatility exposure that a weekly simply does not: as expiry nears, Vega bleeds away, so the same implied-volatility move affects the position less each day.
Veta — definition
Veta is the second-order option Greek measuring how Vega changes for the passage of one day, quoted per calendar day — the time decay of Vega.
Veta — key takeaways
Veta is the decay of Vega over time — the reason your volatility exposure fades daily and the reason volatility bets belong in longer-dated options. It powers calendar spreads, explains why weeklies ignore India VIX, and warns that a correct volatility call still loses if the move arrives too late.
Veta at a glance
| Measures | How Vega changes with the passage of time (Vega decay) |
|---|---|
| Sign | Vega decays over time; long-Vega positions lose Vega as expiry nears |
| Typical range | Largest ATM with time remaining; collapses toward zero at expiry |
| Order | Second-order |
Veta in simple words
Vega tells you how sensitive an option is to implied volatility; Veta tells you how fast that sensitivity shrinks as time passes. Just as Theta decays value and Charm decays Delta, Veta decays Vega. A monthly option is very Vega-sensitive today but far less so a week before expiry — Veta is that daily bleed. It explains why volatility bets belong in longer-dated options and why weeklies barely respond to India VIX.
How Veta behaves — visual
Veta — detailed explanation
Vega decay, defined
Veta is the rate of change of Vega with respect to time, ∂Vega/∂t. Vega itself is proportional to the square root of time remaining, so as expiry approaches, Vega shrinks — an option simply has less runway over which volatility can matter. Veta is the daily size of that shrinkage. Where Theta is the decay of price and Charm is the decay of Delta, Veta is the decay of your volatility exposure, completing the family of time-decay Greeks.
Why weeklies barely feel India VIX
A near-expiry weekly option has very little Vega left, because there is almost no time for volatility to influence the outcome. Veta has already done its work — the Vega has bled away. This is the mathematical reason a spike in India VIX barely moves a Tuesday-expiry weekly but meaningfully re-prices a monthly or quarterly option. If you want to trade volatility, Veta tells you to go further out in time, where Vega is large and decays slowly.
Veta and calendar spreads
Calendar and diagonal spreads live and die by Veta. A calendar is long a far-dated option and short a near-dated one; the near leg's Vega decays fast (high Veta) while the far leg's decays slowly. That differential is the engine of the trade — the position is net long Vega and benefits if IV rises, while the front leg's quicker Vega decay and Theta work in its favour. Understanding Veta is understanding why the two legs of a calendar behave so differently as time passes.
Managing volatility exposure over time
A trader holding a long-Vega position for a volatility view must respect Veta: even if IV never falls, the position's sensitivity to IV erodes daily, so the volatility move must arrive in time to be captured. Desks running long-dated Vega books watch Veta the way they watch Theta on short-dated books — it is the clock ticking on their volatility thesis, and it runs faster as expiry nears and for at-the-money strikes.
Veta formula
Veta = ∂ν/∂t = −S·n(d₁)·√T · ( r·d₁/(σ√T) − (1+d₁·d₂)/(2T) )
The sensitivity of Vega to the passage of time (Vega decay). Usually quoted per calendar day. Largest for at-the-money options with meaningful time to expiry.
Veta — practical example (Nifty)
Illustrative — Nifty spot 24500, lot size 65
Nifty at 24,500. You buy a monthly 24,500 straddle for a volatility view, combined Vega 40, thirty days to expiry. India VIX stays flat, but ten days pass with no move. Because of Veta, the straddle's Vega has decayed from 40 toward roughly 30 — even though your IV forecast has not changed, your exposure to it has shrunk by a quarter. Had you instead bought a weekly straddle, its Vega would have been small to begin with and nearly gone in the same span, which is precisely why a volatility bet belongs in the monthly, not the weekly. Multiply the fading Vega by lot size (65) to see how much less a late VIX spike would now pay you.
Why Veta matters in practice
- Veta is Vega decay — it tells you how fast your volatility exposure erodes as time passes, even if IV is unchanged.
- Weekly options have little Vega and high relative Veta, so they barely respond to India VIX; monthlies retain volatility exposure far longer.
- Calendar and diagonal spreads are built on the Veta differential between a fast-decaying near leg and a slow-decaying far leg.
- A volatility view needs the IV move to arrive before Veta erodes the Vega that would have paid for it.
Common misconceptions about Veta
- Misconception: An option's Vega is constant until expiry.
Reality: Veta is the daily decay of Vega. As expiry nears, an option's Vega bleeds toward zero, which is why a Nifty weekly barely reacts to India VIX while a longer-dated option still carries real volatility exposure.
Common mistakes with Veta
- Buying weekly options to trade a volatility spike, when their Vega is tiny and Veta has nearly finished decaying it.
- Holding a long-Vega position too long and watching Veta shrink the exposure before the expected IV move arrives.
- Ignoring the Veta differential in calendar spreads and being surprised when the two legs' volatility sensitivities diverge.
- Confusing Veta (Vega vs time) with Theta (value vs time) or Vomma (Vega vs volatility) — all touch Vega or time but measure different things.
How professionals use Veta
Volatility desks treat Veta as the clock on their Vega book, exactly as they treat Theta on directional premium: it dictates how long a volatility thesis can be held before its exposure erodes. They express volatility views in longer-dated options where Vega is large and Veta is gentle, and they build calendars and diagonals that deliberately harvest the Veta gap between near and far expiries. For serious Indian volatility traders, Veta is why 'right on volatility, wrong on timing' is a real and expensive way to lose.
Veta — frequently asked questions
What is Veta in options trading?
Veta measures how much an option's Vega decays as time passes, usually per day. It is Vega decay — the volatility-exposure cousin of Theta's value decay and Charm's Delta decay.
Why do weekly options barely react to India VIX?
Because near-expiry options have very little Vega left — there is almost no time for volatility to matter. Veta has already decayed most of the Vega, so even a VIX spike moves them little.
Why should volatility trades use longer-dated options?
Because longer-dated options have large Vega that decays slowly (low Veta), giving your volatility view time to play out. Weeklies have small, fast-fading Vega, so a late IV move pays little.
How does Veta affect calendar spreads?
Calendars exploit the Veta differential: the short near-dated leg loses Vega fast while the long far-dated leg keeps its Vega, leaving the position net long volatility with favourable time decay on the front leg.
Is Veta a first- or second-order Greek?
Second-order. It is the cross-derivative of the option price with respect to both volatility and time.
Can I be right on volatility and still lose because of Veta?
Yes. If IV rises but only after Veta has eroded your Vega, the payoff is smaller than expected — 'right on volatility, wrong on timing' is a real loss driven by Veta.
People also ask about Veta
These questions are answered in detail on their own pages:
Sources & references
- Black, F. & Scholes, M. (1973). “The Pricing of Options and Corporate Liabilities.” Journal of Political Economy, 81(3), 637–654.
- Hull, J. C. Options, Futures, and Other Derivatives (10th ed.). Pearson, 2017.
- Natenberg, S. Option Volatility and Pricing (2nd ed.). McGraw-Hill, 2015.
- NSE India — India VIX (volatility index) methodology and derivatives data.
Published 22 April 2026. Educational content only — not investment advice.