Gamma Hedging P&L: Realized Versus Implied Volatility and Market Marks
Summary
The discussion examines the source and interpretation of gamma-hedging P&L when a trader uses an option valued at implied volatility. Under the simplified setup, the hedge’s accumulated P&L is related to the difference between realized variance and the implied variance used to price the option, multiplied by gamma and the squared underlying price. One answer treats the implied volatility chosen at entry as fixed and attributes interim hedge gains to realized underlying moves.
The replies distinguish this model-based calculation from marking the option to its changing market value before expiration. A market mark can include changes in implied volatility and other inputs, so comparing the hedge account with the current option price introduces additional P&L terms. The discussion also says the variance formula can accommodate deterministic time-varying volatilities, while stochastic volatility requires a broader treatment, such as applying Itô’s formula with volatility as another state variable. These conclusions depend on the chosen valuation and marking convention; the thread does not provide a complete general market P&L decomposition.
Key ideas
- The simplified gamma hedge P&L depends on the gap between realized and implied variance.
- An implied volatility fixed at trade entry differs from a changing market implied volatility mark.
- Marking an option before expiry can add P&L from changes in implied volatility and other inputs.
- Deterministic time-varying volatility can be incorporated into the variance-based hedge expression.
- Stochastic volatility requires a broader model and the cited extension is presented with practical caveats.
Tags
Full text
# Gamma PnL when hedging with implied volatility - where is the mark to market PnL?
# Gamma PnL when hedging with implied volatility - where is the mark to market PnL?
It is well known that hedging with implied volatility involves a PnL:
$0.5*(σ^{2}_r−σ^{2}_i)S^{2}*Γ_{i}dt$
In the Wilmott paper (http://web.math.ku.dk/~rolf/Wilmott_WhichFreeLunch.pdf), they imply that the collective PnL from such a strategy is the integral of above expression across time.
However, this seems to assume that the market implied volatility stays constant at $σ_i$. Otherwise, one would also encounter the mark-to-market PnL governed by the sensitivity of the option to implied volatility among other terms:
$C_{σ}* (dσ)+.....$
Why is the mark to market PnL not accounted for in the above analysis?
## Answer by user34971 (score 1)
https://quant.stackexchange.com/a/69210
Consider any function $f(S(t),K,t,T,\{x_i(t)\})$ with payoff $(S(T) - K)_+$ when $t=T$, where $\{x_i(t)\}$ are other variables/parameters so that at $t=0$ you are able to choose (i.e. calibrated) these so that your function matches the market price of the option: $f(S(0),K,0,T,\{x_i(0)\}) = C^{market}(t=0)$.
As the payoff of the option does not depend on $\{x_i(T)\}$, if you decide to look only at the option value at maturity, then you are free to keep these other variables fixed and only hedge changes in $S_t$. In this case, according to your chosen `reality' (this is 'marking to model' as opposed to 'marking to market') the change in option value is $$ df = \theta dt + \Delta dS + \frac{1}{2} \Gamma (dS)^2 $$ since you have chosen all the others variables/parameters to be constant. $dS$ is whatever change in stock price is observed.
However, if you decide to / or are forced to 'look' at the option value in the market before expiration, then your delta-hedge P/L will equal: $$ P\&L = C^{market}(t=0) + \int_0^u \left( \theta_t dt + \frac{1}{2} \Gamma_t (dS_t)^2 \right) - C^{market}(t=u) $$
## Answer by Kurt G. (score 0)
https://quant.stackexchange.com/a/69207
If you assume that the vols $\sigma_r,\sigma_i$ are deterministic functions of time their formula (1) still holds $$\tag{1} dV(t)=\frac{1}{2}(\sigma^2_r(t)-\sigma_i^2(t))\,\Gamma^i(t)\,dt. $$ Integrating gives the accumulated hedge PnL $$ V(t)=\frac{1}{2}\int_0^t(\sigma^2_r(s)-\sigma_i^2(s))\,\Gamma^i(s)\,ds. $$ One could extend the derivation to the case of stochastic vol $\sigma_r(t)$ by applying Ito's formula to the call price with two state variables $C(t,S(t),\sigma_r(t))\,.$ I am however not sure how useful such a general result will be in practice. Formula (1) holds approximately for small time intervals when $\sigma_r(t)$ can be assumed to be nearly deterministic.
## Answer by Arbitrage Technologies (score 0)
https://quant.stackexchange.com/a/74294
The sigma i is the implied volatility you locked when u bought the call! It never moves. The only thing that move is sigma realised that you build during rebalancing… understood?Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.