How Delta-Hedging Frequency Affects Gamma P&L
Summary
The document examines the expected value and variance of gamma P&L under different delta-hedging intervals. The question assumes normally distributed underlying returns, constant implied volatility, no transaction costs, and a constant dollar gamma exposure. Its initial calculation treats one day as a fixed horizon but rescales each interval’s gamma P&L by the number of intervals, leading to a claimed lack of dependence on hedge frequency.
The answers clarify that comparisons must hold the time unit fixed: changing the interval while keeping the same total horizon changes the distribution of the accumulated P&L. One response connects delta hedging to a stochastic integral and notes that more frequent hedging reduces hedging error in the idealized framework. Another suggests using log returns to compare frequencies. In practice, transaction costs, mean reversion, volatility changes, and risk limits can affect hedge choices. The discussion does not work through a full derivation of the corrected expectation and variance, and its idealized assumptions omit these real-world effects.
Key ideas
- Compare hedge intervals over a fixed total horizon to assess frequency effects on gamma P&L.
- Delta-hedging P&L is related to a stochastic integral, with finer hedging reducing discretization error in an idealized setting.
- The initial calculation's scaling obscures how the accumulated P&L distribution changes with hedge frequency.
- Transaction costs, volatility behavior, mean reversion, and risk limits influence practical rebalancing choices.
- The answers suggest comparing log returns but do not provide a complete derivation of the revised moments.
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Full text
# Delta hedging frequency, Gamma PnL
# Delta hedging frequency, Gamma PnL
I want to know the expectation and the variance of the Gamma PnL for different hedging frequencies.
Let's say the return of the underlying follow a normal process: $dr= \sigma*dW$, the market trades 24hours and there is no transaction cost. I consider I have a constant dollar $\Gamma$ position (-r% or +r%, r $\in$ $\mathbb{R}$), provide the same $\Gamma$) with a stripe of options. I also assume, there is no change in implied vol during the day, therefore the vega PnL is zero.
The daily volatility is $s = \frac{\sigma}{\sqrt{365}}$ therefore $dr \sim \mathcal{N}(0,s^2)$.
What is the Gamma PnL if we hedge every seconds, hours ... every time period $t$?
If we hedge every time $t$ (to simplify I normalize $t$ to a day, for instance every hour would be $t$ = 1/24), using the properties of Brownian motions, I can consider I have $1/t$ independent return processes $dr_{t} \sim \mathcal{N}(0, s^2*t)$, the Gamma PnL process is then for a day:
$PnL_{\Gamma}= \frac{1}{t}*\Gamma*\frac{dr_{t}^2}{2}$
and then follows $PnL_{\Gamma}\sim \chi^2_{1}$, with mean $E =\Gamma*s^2*t/t = \Gamma*s^2$ and variance $V = \Gamma^2*s^4*t^2/t^2 = \Gamma^2*s^4$
What I do not understand is that there is no dependency of the Gamma PnL to the hedging frequency. As we increase the hedging frequency we should have less variance and less return on the gamma and the reciprocal should be true? Where is my math failing? I do not see it.
## Answer by Nivel Egres (score 2)
https://quant.stackexchange.com/a/32510
From a quant perspective (I am sure more quants will chime in), delta hedging is a physical representation of a stochastic integral, which is inherently independent of the step size (in both time and price dimension). All you can really say there is that the closer to continuous hedging you get, the lower your hedging error will be.
From a traders perspective re-balancing frequency will indeed come into play if you leave the perfect BS world. For example, in real life, you are usually trying to optimize your hedging for a balance of (a) smoothness of P&L, (b) transaction costs, (c) vol dampening or amplifying (d) mean reversion found in the asset you're trading and (e) your risk limits.
## Answer by user26616 (score 2)
https://quant.stackexchange.com/a/32517
The problem with what I do above is that I change the unit of time, as opposed to keeping the same unit of time and comparing the different frequencies.
We want to compare the returns over different hedging frequencies, the easy way is to use log return over different frequencies:
$dr_{t}=-\frac{s^2*t}{2} + s*\sqrt{t}*\epsilon∼N(-\frac{s^2∗t}{2},s^2∗t)$
If you do the rest of the math you will get the effect of the expected Gamma PnL and its variance.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.