Let consider a real-valued stochastic process described by the stochastic differential equation (SDE) in the Ito formulation: \begin{align} dx= x \mu dt + x \sigma dW \tag{1} \label{1} \end{align} where $\mu$ and $\sigma$ are real-valued constants and $W$ is a Wiener process. The corresponding Fokker Plank equation (FPE) reads (https://en.wikipedia.org/wiki/Fokker%E2%80%93Planck_equation): \begin{align} \frac{\partial P}{\partial t}=-\frac{\partial }{\partial x}(x \mu P)+ \frac{1}{2} \frac{\partial^2 }{\partial x^2} (x^2 \sigma^2 P) \tag{2} \label{2} \end{align} Eq. \ref{2} can be rewritten as: \begin{align} \frac{\partial P}{\partial t}=(\sigma^2-\mu)P+(2 \sigma^2-\mu)x \frac{\partial P }{\partial x} + \frac{x^2 \sigma^2}{2} \frac{\partial^2 P}{\partial x^2} \tag{3} \label{3} \end{align} If we perform a change of variables in eq. \ref{1}, $y=\log x$, applying Ito change of variables formula (https://en.wikipedia.org/wiki/It%C3%B4%27s_lemma) we get: \begin{align} dy= \biggl(\mu- \frac{\sigma^2}{2}\biggr) dt + \sigma dW \tag{4} \label{4} \end{align} which corresponds to the FPE: \begin{align} \frac{\partial P}{\partial t}=\biggl(\frac{\sigma^2}{2} -\mu \biggr)\frac{\partial P }{\partial y}+ \frac{\sigma^2}{2}\frac{\partial^2 P}{\partial y^2} \tag{5} \label{5} \end{align} If we now take eq. \ref{3} and perform the same change of variables of eq. \ref{4}, we get: \begin{align} \frac{\partial P}{\partial t}=(\sigma^2-\mu)P+\biggl(\frac{3}{2} \sigma^2-\mu \biggr) \frac{\partial P }{\partial y} + \frac{ \sigma^2}{2} \frac{\partial^2 P}{\partial y^2} \tag{6} \label{6} \end{align} I expect eq. \ref{5} and \ref{6} to coincide, but they do not. Can someone please explain me the reason? Where am I wrong? Thanks in advance
2026-04-24 08:19:35.1777018775
Different Fokker-Plank Equations after change of variables
385 Views Asked by Bumbble Comm https://math.techqa.club/user/bumbble-comm/detail At
1
There are 1 best solutions below
Related Questions in PROBABILITY
- How to prove $\lim_{n \rightarrow\infty} e^{-n}\sum_{k=0}^{n}\frac{n^k}{k!} = \frac{1}{2}$?
- Is this a commonly known paradox?
- What's $P(A_1\cap A_2\cap A_3\cap A_4) $?
- Prove or disprove the following inequality
- Another application of the Central Limit Theorem
- Given is $2$ dimensional random variable $(X,Y)$ with table. Determine the correlation between $X$ and $Y$
- A random point $(a,b)$ is uniformly distributed in a unit square $K=[(u,v):0<u<1,0<v<1]$
- proving Kochen-Stone lemma...
- Solution Check. (Probability)
- Interpreting stationary distribution $P_{\infty}(X,V)$ of a random process
Related Questions in STATISTICS
- Given is $2$ dimensional random variable $(X,Y)$ with table. Determine the correlation between $X$ and $Y$
- Statistics based on empirical distribution
- Given $U,V \sim R(0,1)$. Determine covariance between $X = UV$ and $V$
- Fisher information of sufficient statistic
- Solving Equation with Euler's Number
- derive the expectation of exponential function $e^{-\left\Vert \mathbf{x} - V\mathbf{x}+\mathbf{a}\right\Vert^2}$ or its upper bound
- Determine the marginal distributions of $(T_1, T_2)$
- KL divergence between two multivariate Bernoulli distribution
- Given random variables $(T_1,T_2)$. Show that $T_1$ and $T_2$ are independent and exponentially distributed if..
- Probability of tossing marbles,covariance
Related Questions in PARTIAL-DIFFERENTIAL-EQUATIONS
- PDE Separation of Variables Generality
- Partial Derivative vs Total Derivative: Function depending Implicitly and Explicitly on Variable
- Transition from theory of PDEs to applied analysis and industrial problems and models with PDEs
- Harmonic Functions are Analytic Evan’s Proof
- If $A$ generates the $C_0$-semigroup $\{T_t;t\ge0\}$, then $Au=f \Rightarrow u=-\int_0^\infty T_t f dt$?
- Regular surfaces with boundary and $C^1$ domains
- How might we express a second order PDE as a system of first order PDE's?
- Inhomogeneous biharmonic equation on $\mathbb{R}^d$
- PDE: Determine the region above the $x$-axis for which there is a classical solution.
- Division in differential equations when the dividing function is equal to $0$
Related Questions in STOCHASTIC-PROCESSES
- Interpreting stationary distribution $P_{\infty}(X,V)$ of a random process
- Probability being in the same state
- Random variables coincide
- Reference request for a lemma on the expected value of Hermitian polynomials of Gaussian random variables.
- Why does there exists a random variable $x^n(t,\omega')$ such that $x_{k_r}^n$ converges to it
- Compute the covariance of $W_t$ and $B_t=\int_0^t\mathrm{sgn}(W)dW$, for a Brownian motion $W$
- Why has $\sup_{s \in (0,t)} B_s$ the same distribution as $\sup_{s \in (0,t)} B_s-B_t$ for a Brownian motion $(B_t)_{t \geq 0}$?
- What is the name of the operation where a sequence of RV's form the parameters for the subsequent one?
- Markov property vs. transition function
- Variance of the integral of a stochastic process multiplied by a weighting function
Related Questions in STOCHASTIC-CALCULUS
- Interpreting stationary distribution $P_{\infty}(X,V)$ of a random process
- Reference request for a lemma on the expected value of Hermitian polynomials of Gaussian random variables.
- Why does there exists a random variable $x^n(t,\omega')$ such that $x_{k_r}^n$ converges to it
- Compute the covariance of $W_t$ and $B_t=\int_0^t\mathrm{sgn}(W)dW$, for a Brownian motion $W$
- Mean and variance of $X:=(k-3)^2$ for $k\in\{1,\ldots,6\}$.
- 4th moment of a Wiener stochastic integral?
- Unsure how to calculate $dY_{t}$
- What techniques for proving that a stopping time is finite almost surely?
- Optional Stopping Theorem for martingales
- $dX_t=\alpha X_t \,dt + \sqrt{X_t} \,dW_t, $ with $X_0=x_0,\,\alpha,\sigma>0.$ Compute $E[X_t] $ and $E[Y]$ for $Y=\lim_{t\to\infty}e^{-\alpha t}X_t$
Trending Questions
- Induction on the number of equations
- How to convince a math teacher of this simple and obvious fact?
- Find $E[XY|Y+Z=1 ]$
- Refuting the Anti-Cantor Cranks
- What are imaginary numbers?
- Determine the adjoint of $\tilde Q(x)$ for $\tilde Q(x)u:=(Qu)(x)$ where $Q:U→L^2(Ω,ℝ^d$ is a Hilbert-Schmidt operator and $U$ is a Hilbert space
- Why does this innovative method of subtraction from a third grader always work?
- How do we know that the number $1$ is not equal to the number $-1$?
- What are the Implications of having VΩ as a model for a theory?
- Defining a Galois Field based on primitive element versus polynomial?
- Can't find the relationship between two columns of numbers. Please Help
- Is computer science a branch of mathematics?
- Is there a bijection of $\mathbb{R}^n$ with itself such that the forward map is connected but the inverse is not?
- Identification of a quadrilateral as a trapezoid, rectangle, or square
- Generator of inertia group in function field extension
Popular # Hahtags
second-order-logic
numerical-methods
puzzle
logic
probability
number-theory
winding-number
real-analysis
integration
calculus
complex-analysis
sequences-and-series
proof-writing
set-theory
functions
homotopy-theory
elementary-number-theory
ordinary-differential-equations
circles
derivatives
game-theory
definite-integrals
elementary-set-theory
limits
multivariable-calculus
geometry
algebraic-number-theory
proof-verification
partial-derivative
algebra-precalculus
Popular Questions
- What is the integral of 1/x?
- How many squares actually ARE in this picture? Is this a trick question with no right answer?
- Is a matrix multiplied with its transpose something special?
- What is the difference between independent and mutually exclusive events?
- Visually stunning math concepts which are easy to explain
- taylor series of $\ln(1+x)$?
- How to tell if a set of vectors spans a space?
- Calculus question taking derivative to find horizontal tangent line
- How to determine if a function is one-to-one?
- Determine if vectors are linearly independent
- What does it mean to have a determinant equal to zero?
- Is this Batman equation for real?
- How to find perpendicular vector to another vector?
- How to find mean and median from histogram
- How many sides does a circle have?
Let $ P (x) $ and $ Q (y) $ be the densities with respect to the two different parametrizations.
They are related by $ P (x)=Q (y)\frac{dy}{dx} $.
This means that your second approach is the wrong one. Instead of deriving a PDE for $ Q(y)=P(x(y))\frac{dx}{dy}(y)$ you derived a PDE for $ \tilde{Q}(y):=P(x(y)) $, which is not a probability density.
PS: that your second approach is the wrong one can of course also be seen by the fact that it doesn't preserve the mass of $ P $ over time