Estimating Swap DV01 Changes with Gamma
Summary
The document explains how a swap’s DV01 changes when interest rates move, focusing on gamma as the rate sensitivity of delta. One answer derives a rough approximation in a simplified single-curve setting: swap delta is about the negative of maturity, while gamma is about maturity squared. This offers intuition for how DV01 can change with a rate shift.
A second answer applies a gamma-based estimate to a receiver swap, comparing the adjusted DV01 with a pricing result and finding them fairly close in that example. The approximation is explicitly limited: the maturity-based shortcut works best in a low-rate environment and can deteriorate at higher rates. The numerical example is specific to the stated instrument and curve shift; the document gives no general calibration rule beyond using gamma to estimate the change.
Key ideas
- Gamma measures how swap delta, and therefore DV01, changes as rates move.
- A simplified model approximates swap delta by negative maturity and gamma by maturity squared.
- A first-order gamma adjustment can estimate a new DV01 after a rate shift.
- The maturity-based approximation can become less reliable when rates are high.
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# ATM interest rate swap dv01 vs off-market swap dv01
# ATM interest rate swap dv01 vs off-market swap dv01
How significant is impact on dv01 of an at-the-money swap if rates move significantly?
For example: lets say a 5Y USD at the money swap has 4.6 duration. now, if the rate curve move by 150-200bps, what will be the new dv01? Is there a heuristic rule to estimate this?
thanks
## Answer by Kermittfrog (score 1, accepted)
https://quant.stackexchange.com/a/71332
To a very (!) first approximation, the delta of a swap equals the negative of its time to maturity ($\Delta \approx -T$), the gamma equals that squared ($\Gamma \approx T^2$): Starting from a generic swap valuation formula $$ \begin{align} PV&=s\sum_i\delta_{t_i}^{fix}D(t_i)-\sum_i\delta_{t_i}^{float}F(t_{i-1}\to t_i)D(t_i) \end{align} $$ with swap rate $s$, discount factor $D$, forward rate $F$, and year fraction factors $\delta$. Let's simplify and assume a single curve world ($F$ derived from $D$), annual payment frequencies ($\delta_i=1$) and payment dates $t_1=1,t_2=2,\ldots,t_n=T$
$$ \begin{align} PV&=s\sum_ie^{-r(t_i)t_i}-(1-e^{-r(t_n)t_n})\\ \Rightarrow \Delta \equiv \frac{\partial PV}{\partial r}&=-s\sum_i t_ie^{-r(t_i)t_i}-t_ne^{-r(t_n)t_n}\\ &\approx-t_n\\ &=-T \end{align} $$
Likewise, the second order derivative, $\Gamma$, is approximated as
$$ \begin{align} \Gamma \equiv \frac{\partial^2 PV}{\partial r^2}=\frac{\partial \Delta}{\partial r}&=s\sum_i t_i^2e^{-r(t_i)t_i}+t_n^2e^{-r(t_n)t_n}\\ &\approx t_n^2\\ &=T^2 \end{align} $$
Then,
$$ d\Delta=\Gamma dr\approx T^2dr $$
Do note, however, that this approximation only holds in a low-interest-rate environment. As soon as $r,c\gg0$, the approximation deteriorates.
HTH?
## Answer by oronimbus (score 3)
https://quant.stackexchange.com/a/71323
You need Gamma to answer this question really. Gamma tells you how much your delta moves for a change in rates. Taking a 5y \$ receiver swap with a DV01 of \$4333.60 on 10MM notional we get a Gamma per 1bp of \$2.41. If we now shift all curves (3m\$L and SOFR) by -150bp this swap becomes more ITM and hence the DV01 should increase. Approximately the new DV01 is now 4333.60 + 150 * 2.41 which gives us \$4695.1.
This is not too far off from the actual new DV01 of \$4715.72 when looking at the pricer. I'm not aware of any heuristics without Gamma.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.