Deriving the Pricing Kernel Drift with Itô’s Product Rule
Summary
The discussion derives the drift of a pricing kernel formed by multiplying a state-dependent discount factor by a function of state variables that follow Itô processes. The key point is that the accumulated integral of the discount rate has finite variation: its differential is the current rate times time, so it contributes no diffusion term and creates no cross-variation term with the state-dependent function.
Applying Itô’s product rule therefore gives the kernel’s drift as the negative current discount rate plus the infinitesimal generator applied to the state function, divided by that function. The answer also offers a less formal explanation based on the latest increment of the time integral, and another response emphasizes differentiating that integral correctly. The source contains inconsistent signs between its initial setup and its displayed answer, so the convention for the exponential discount factor must be checked before applying the formula.
Key ideas
- The time integral of a state-dependent discount rate has differential equal to the current rate times time.
- That integral has finite variation, so its product with the state function creates no diffusion cross term.
- Itô’s product rule combines the discount-rate contribution with the state function’s generator drift.
- The sign of the drift depends on the sign convention in the exponential kernel definition.
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# Markov Pricing kernel
# Markov Pricing kernel
I'm reading about Markov pricing kernels in the lecture notes of a course I'm following, but I have a big doubt on an application of Ito's lemma. The setting is the following:
We define the pricing kernel as $$ \xi_t = \xi(D_t,y_t,t) = e^{\int_0^t \delta(D_s,y_s)ds} T(D_t,y_t), \qquad \xi_0=1 $$ where $D$ and $y$ are Ito processes following the dynamics $$ dD_t = m(D_t,y_t)dt + \sigma(D_t,y_t) dW_{1t} $$ and $$ dy_t = \varphi(y_t)dt + v_1(y_t) dW_{1t} + v_2(y_t) dW_{2t} $$ Moreover, we assume the pricing kernel follows the dynamics $$ \frac{d\xi_t}{\xi_t} = -R_t dt -\lambda_{1t} dW_{1t}-\lambda_{2t} dW_{2t} $$
Now, the claim in the lecture notes is that by applying the Ito's lemma to $\xi_t$, one finds $$ R(D,y) = \delta(D,y) - \frac{\mathscr{L} T(D,y)}{T(D,y)}, $$ where $\mathscr{L}$ is the infinitesimal generator.
Now, I can see that this result can be obtained - rather trivially - in the case where the function $\delta$ in the integral is not dependent on $D$ and $y$. But in the case the dependence is there (as stated in the lecture notes), the drift obtained with Ito takes a much more complex form, and I really don't see any cancelling of the terms.
Do you agree with me - and thus there's a typo in my lecture notes - or am I applying Ito in the wrong way?
## Answer by Abramo (score 1)
https://quant.stackexchange.com/a/17055
To shorten the notation, let's write $T_t = T(D_t,y_t)$ and $\delta_t = \delta(D_t,y_t)$.
There are two ways to show that, in fact, the dynamics of $$ \xi_t = \xi(D_t, y_t,t) = e^{-\int_0^t \delta_s ds}\, T_t $$ is given by $$ \frac{d\xi_t}{\xi_t} = \left( -\delta_t + \frac{\mathscr{L} T_t}{T_t} \right)dt \quad+\quad \text{diffusion terms}. $$
### First way (more formal)
Write $\xi_t = g_t T_t$, where $g_t = e^{-\int_0^t \delta_s ds}$. It is easy to show that the dynamics of $g_t$ is given by $$ \frac{dg_t}{g_t} = -\delta_t \, dt $$ therefore, by applying Ito's product rule we have $$ d\xi_t = d(g_t T_t) = T_t dg_t + g_t dT + dg_t dT_t = -\delta_t \xi_t dt + g_t dT_t $$ because the product term vanishes since $dg_t$ has no diffusion. Hence it follows
$$ \frac{d\xi_t}{\xi_t} = \frac{d\xi_t}{g_tT_t} = -\delta_t dt + \frac{dT_t}{T_t} = \left( -\delta_t + \frac{\mathscr{L} T_t}{T_t} \right)dt \quad+\quad \text{diffusion terms} $$
### Second way (less formal)
The function $g_t = -\int_0^t \delta(D_s,y_s) ds$ is constant w.r.t. both $D_t$ and $y_t$, in the sense that the contribution of the very last realisation at time $t$ of the processes to the integral over $[0,t]$ is almost surely equal to $0$. In other words,
$$ \frac{\partial g_t}{\partial D_t} = \frac{\partial g_t}{\partial y_t} = 0 \, .$$ Therefore the result follows by noticing that $$ \mathscr{L} \xi_t = g_t \mathscr{L} T_t \implies \frac{\mathscr{L} \xi_t}{\xi_t} = \frac{\mathscr{L} T_t}{T_t} $$
## Answer by AFK (score 0)
https://quant.stackexchange.com/a/17048
I think you are having trouble differentiating the integral of $\delta$.
You should remember the differential notation is just notation for an integral: $A_td B_t = A'_t dB'_t$ just means $\int_0^T A_td B_t = \int_0^T A'_t dB'_t$.
In particular, $d\int_0^t A'_s dB'_s = A'_t dB'_t$ is a tautology. So $$ d ( e^{\int_0^t \delta(s,X_s) ds} )= e^{\int_0^t \delta(s,X_s) ds} d (\int_0^t \delta(s,X_s) ds ) = e^{\int_0^t \delta(s,X_s) ds}\delta(t,X_t)dt $$
Applying Ito formula to the product with $T$ gives the result.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.