I'm having a little trouble understanding the setup for Ito's chain rule, and how to expand it to finding SDE's. In class, I was taught that an example of Ito's chain rule was the following: $$ df = (f_t+1/2f_{BB})\,dt + f_B\,dB $$ where $f$ is a function of $t$ and the random variable $B$, typically governed by a Brownian Motion. Now, I have this problem, where I'm asked to solve the SDE for $Z = e^{B(t)^2}$ where the hint to the question is to let a random variable $X = (B(t))^2$ and apply the Ito chain rule to $f(x) = e^x$. I interpreted this as asking to substitute in this equation to let $Z = e^X$, where $(B(t))^2$ is written as the random variable $X$ in the original equation. But now, I'm confused on how to take the SDE. I'm unclear how to separate $Z$ into having a drift and diffusion term, but more importantly I'm unclear on how to use Ito's chain rule in this situation, as I don't see a function f which doesn't have the parameters of $t$(time) and $B$(random variable), I only see $Z$ as having these traits, and so I'm not sure how the chain rule would apply. I'm not looking for an answer, I just want to understand how to set up my problem, so I can understand how to solve it. Thanks.
2026-03-27 16:21:44.1774628504
Question About Ito's Chain Rule and SDE's
139 Views Asked by Bumbble Comm https://math.techqa.club/user/bumbble-comm/detail At
1
There are 1 best solutions below
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 $Y=\lim_{t\to\infty}e^{-\alpha t}X_t$
Related Questions in STOCHASTIC-INTEGRALS
- Meaning of a double integral
- 4th moment of a Wiener stochastic integral?
- Cross Variation of stochatic integrals
- Stochastic proof variance
- Solving of enhanced Hull-White $dX_t = \frac{e^t-X_t}{t-2}dt + tdW_t$
- Calculating $E[exp(\int_0^T W_s dW_s)]$?
- Applying Ito's formula on a $C^1$ only differentiable function yielding a martingale
- what does it mean by those equations of random process?
- Why aren't the sample paths of this stochastic process defined?
- Is the solution to this (simple) Stochastic Differential Equation unique?
Related Questions in STOCHASTIC-DIFFERENTIAL-EQUATIONS
- Polar Brownian motion not recovering polar Laplacian?
- Uniqueness of the parameters of an Ito process, given initial and terminal conditions
- $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 $Y=\lim_{t\to\infty}e^{-\alpha t}X_t$
- Initial Distribution of Stochastic Differential Equations
- (In)dependence of solutions to certain SDEs
- Expectation, supremum and convergence.
- Integral of a sum dependent on the variable of integration
- Solving of enhanced Hull-White $dX_t = \frac{e^t-X_t}{t-2}dt + tdW_t$
- Closed form of a SDE
- Matricial form of multidimensional GBM
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?
Ito's formula is valid for semi-martingales. In this case we have $X_t = B_t^2$, which is a semi-martingale as may be observed by applying Ito's formula,
$$ dX_t = 2B_t dB_t + 2 dt $$
So since $Z_t = \exp(X_t)$ we should have
$$ Z_t = Z_t dX_t + 1/2 Z_t d[X]_t $$
where $[.]$ stands for the quadratic variation. Now the quadratic variation of $X_t$ can be read directly off of the differential form. It is just the square of the $2B_t dB_t$ bit where we use the algebraic rule that $dB_tdB_t = dt$. (The justification for this is that the quadratic variation of the Ito integral is known to be $[\mathcal{I}_{B_t}(\Phi)] = \int \Phi_t^2d t$ when the latter is finite). That is, $d[X]_t = 4B_t^2 dt$.
So we have
$$ Z_t = Z_t dX_t + 2 B_t^2 Z_t dt = 2Z_t B_t dB_t + 2(1+B_t^2)Z_t dt $$
As Lutz mentioned, you can also just apply Ito's formula directly without any substitutions,
$$ dZ_t = 2B_t Z_t dB_t + 1/2(2Z_t + 4B_t^2 Z_t)dt $$
It clearly comes to the same thing and in this case is probably simpler. Still, convincing yourself of each step in the other approach is a valuable exercise.