Deriving the Zero-Coupon Bond PIDE with Short-Rate Jumps
Summary
The document derives the pricing equation for a zero-coupon bond when the short rate follows a Vasicek-style jump diffusion. The rate combines mean reversion, square-root diffusion volatility, and independent Poisson jumps with exponentially distributed positive sizes. Applying Itô’s formula for jump processes separates the continuous diffusion terms from the discrete jump changes; compensating the jump measure produces a martingale term and an expected jump contribution.
Discounting the bond price at the short rate and requiring the discounted value to be a martingale gives a partial integro-differential equation with a terminal payoff of one. The jump term averages the change in bond value over the jump-size distribution. The derivation assumes the stated model dynamics and pricing measure, along with conditions sufficient for the martingale arguments. The original question’s integral omits the jump density, while the response’s final form makes the density explicit and includes the jump intensity contribution.
Key ideas
- Apply Itô’s formula with jumps to separate diffusion and jump contributions to bond-price changes.
- The jump measure’s compensator yields the expected jump term in the pricing equation.
- Discounting by the short-rate accumulation leads to a martingale condition for an arbitrage-free bond price.
- The jump integral must be weighted by the jump-size density and intensity.
- The bond’s terminal condition is a value of one at maturity.
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Full text
# Bond PDE under an Affine Jump Diffusion model
# Bond PDE under an Affine Jump Diffusion model
Under the Jump extended Vasicek model, the dynamics of the short rate are as follow : $$dr_t=\kappa(\theta-r_t)dt+\sigma\sqrt{r_t}\,dW_t+d\left(\sum\limits_{i=1}^{N_t}\,J_i\right)$$ where $N_t$ represents a Poisson process with constant intensity rate $\lambda>0$ and $\{J_i\}_{i=1}^{\infty}$ denotes the magnitudes of jump, which are assumed to be i.i.d. random variables with distribution $f_J$ independent of $W_t$ and $N_t$. Moreover,$W_t$ is assumed to be independent of $N_t$. In addition the jump sizes $\,J_i$ has an exponential distribution with density: $${{f}_{J}}(\chi )=\left\{ \begin{matrix} \eta {{e}^{-\eta\,\chi}}\,,\,\,\chi >0\, \\ 0\,\,\,\,\,\,\,\,,\,\,\,\,o.w. \\ \end{matrix} \right.$$ where $\eta > 0 $ is an constant. Can some one explain how to find the following parabolic partial integro differential equation for an arbitrage-free price at time $t$ of of a ZC bond of maturity $T$ ? : $$\frac{\partial P}{\partial t}+\frac{1}{2}{{\sigma }^{2}}r\frac{{{\partial }^{2}}P}{\partial {{r}^{2}}}+\kappa (\theta -r)\frac{\partial P}{\partial r}-rP+\lambda \int_{-\infty }^{\infty }{(P(t,r+\chi ,T)-P(t,r,T)d\chi =0}$$ with boundary condition $P(T,r,T)=1$.
Thank you
## Answer by Gordon (score 2, accepted)
https://quant.stackexchange.com/a/42398
Let $P(t, r_t, T)$ be the bond price at time $t$, where $0 \leq t \leq T$. Then, by Ito's formula, \begin{align*} &\ P(t, r_t, T) \\ =& P(0, r_0, T) + \int_0^t\partial_s P(s, r_s, T) ds + \int_0^t\partial_r P(s, r_{s-}, T) dr_s + \frac{1}{2}\sigma^2 \int_0^t r_s\partial_{rr} P(s, r_s, T)ds\\ & \quad +\sum_{s \leq t}\big[P(s, r_s, T) - P(s, r_{s-}, T) - \partial_r P(s, r_{s-}, T)\Delta r_s\big] \quad (\mbox{where } \Delta r_s=r_s - r_{s-})\\ =& P(0, r_0, T) + \int_0^t\partial_s P(s, r_s, T) ds + \int_0^t\partial_r P(s, r_s, T) dr_s^c + \frac{1}{2}\sigma^2 \int_0^t r_s\partial_{rr} P(s, r_s, T)ds\\ & \quad +\sum_{s \leq t}\big[P(s, r_s, T) - P(s, r_{s-}, T) \big] \quad (\mbox{where } dr_t^c = \kappa(\theta - r_t)dt + \sigma \sqrt{r_t} d W_t)\\ =& P(0, r_0, T) + \int_0^t\partial_s P(s, r_s, T) ds + \int_0^t\partial_r P(s, r_s, T) dr_s^c + \frac{1}{2}\sigma^2 \int_0^t r_s\partial_{rr} P(s, r_s, T)ds\\ & \quad +\int_0^t \int_{\mathbb{R}}\big[ P(s, r_{s-}+y, T) - P(s, r_{s-}, T)\big]\mu(ds, dy) \quad (\mbox{where } \mu = \sum_{i=1}^{\infty} \delta_{\tau_i, J_i})\\ =& P(0, r_0, T) + \int_0^t\partial_s P(s, r_s, T) ds + \int_0^t\partial_r P(s, r_s, T) dr_s^c + \frac{1}{2}\sigma^2 \int_0^t r_s\partial_{rr} P(s, r_s, T)ds\\ &\quad +\int_0^t \int_{\mathbb{R}}\big[P(s, r_{s-}+y, T) - P(s, r_{s-}, T)\big](\mu(ds, dy) - ds v(dy)) \\ &\quad +\int_0^t ds\int_{\mathbb{R}}\big[ P(s, r_s+y, T) - P(s, r_s, T)\big]\lambda f_J(y)dy, \end{align*} where $v(dy) = \lambda f_J(y)dy$. Here \begin{align*} M_t = \int_0^t \int_{\mathbb{R}}\big[ u(X_{s-} + y, s) - u(X_{s-}, s))\big](\mu(ds, dy) - ds v(dy)) \end{align*} is a martingale. Since $P(t, r_t, T) e^{-\int_0^t r_s ds}$ is a martingale, and \begin{align*} d\Big(P(t, r_t, T) e^{-\int_0^t r_s ds}\Big) &= e^{-\int_0^t r_s ds}\big[-r_t P(t, r_t, T) dt + dP(t, r_t, T)\big], \end{align*} we obtain that \begin{align*} &-r_t P(t, r_t, T) + \partial_t P(t, r_t, T) + \kappa(\theta-r_t)\partial_r P(t, r_t, T) + \frac{1}{2}\sigma^2 r_t\partial_{rr} P(t, r_t, T) \\ & \qquad\qquad + \int_{\mathbb{R}}\big[ P(t, r_t+y, T) - P(t, r_t, T\big]\lambda f_J(y)dy = 0. \end{align*} That is, \begin{align*} & \partial_t P(t, r_t, T) + \kappa(\theta-r_t)\partial_r P(t, r_t, T) + \frac{1}{2}\sigma^2 r_t\partial_{rr} P(t, r_t, T) -(r_t+\lambda)P(t, r_t, T)\\ & \qquad\qquad + \lambda \int_{\mathbb{R}} P(t, r_t+y, T) f_J(y)dy = 0. \end{align*}Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)
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