# 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?

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: $$P\&L = C^{market}(t=0) + \int_0^u \left( \theta_t dt + \frac{1}{2} \Gamma_t (dS_t)^2 \right) - C^{market}(t=u)$$
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.
• If volatility is stochastic, how can you write the true dynamics of $C$ in 2 state variables? Dec 22, 2021 at 12:17