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Vega requires a volatility-unit convention

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Start with the idea

An option’s response to an implied-volatility change is often quoted per one volatility point, although mathematical derivatives usually use a full decimal unit.

Symbols, units & horizon
  • ν: option-price sensitivity per 1.0 decimal annualized volatility change
  • Δσ: annualized volatility change as decimal fraction
  • ν_point: price sensitivity per one percentage-point volatility change
  • ΔV: local per-unit option price change with other inputs fixed

When and why to use this

Reconcile option-risk reports, hedge quantities and surface scenarios.

An option’s response to an implied-volatility change is often quoted per one volatility point, although mathematical derivatives usually use a full decimal unit.

A rise from 20% to 21% is .01 in decimal volatility and one volatility point. Mixing those conventions can exaggerate sensitivity by a factor of 100. State whether Greeks cover one underlying unit or one exchange contract.

Vega is a local partial derivative that holds spot and other inputs fixed. A market smile may move differently at each strike and maturity, so a single parallel shock is only one scenario.

ΔV≈νΔσ,νpoint=0.01ν
Local partial-derivative approximation and unit conversion

Vega requires a volatility-unit convention

  1. Convert the volatility change to decimal fraction.
  2. Multiply by vega quoted per full decimal unit.
  3. If using per-point vega instead, multiply the derivative by .01 once and express the move in volatility points.
Work it by hand

Vega 40 per decimal unit and volatility rise from .20 to .23 give 40×.03=1.2 price units. Per-point vega is .4, and .4×3 gives the same answer.

Apply it in a strategy

  • Freeze inputs at the stated decision time and record their units.
  • Reconcile option-risk reports, hedge quantities and surface scenarios.
  • Recompute the example, then change the material assumption and explain the difference.

Research deliverable

Vega requires a volatility-unit convention: produce the worked calculation, a timestamped input record and a written decision addressing this limitation: Parallel, small volatility moves are an approximation; large skew or spot changes require full repricing.

These are synthetic mechanics examples, not historical performance or paper replications. Module evidence and research boundaries record the 12 September 2026 review.

Python implementation

Self-contained teaching example. Python 3.10+; dependencies and input conventions are shown in the code and notation. Run in your own Python environment.

# Python 3.10+; standard library and NumPy only.
# Synthetic teaching inputs; conventions and units are defined in the notation above.
def vega_change(vega_per_decimal,vol_before,vol_after):
    if min(vol_before,vol_after)<0: raise ValueError('Nonnegative volatilities required')
    return vega_per_decimal*(vol_after-vol_before),.01*vega_per_decimal

change,per_point=vega_change(40,.2,.23)
assert abs(change-1.2)<1e-12 and per_point==.4
print(change,per_point)

Continue learning

Volatility: Measurement, Surfaces & Variance Risk — all lessons
  1. Realized variance starts with squared returns
  2. EWMA as a causal variance baseline
  3. A multi-horizon realized-variance forecast
  4. Implied volatility is a model inversion
  5. Term structure through total and forward variance
  6. Strike convexity and a butterfly consistency check
  7. Vega requires a volatility-unit convention
  8. Variance exposure and the difference from arbitrage

Quantitative finance and development glossary · Python resources and libraries · Research sources and limitations