List questions from stochastic-calculus

Published on 28 Mar 2026 - 15:56

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Ito integrals as limit in probability in the case of continuous integrands

Published on 23 Jan 2020 - 1:22

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Calculation of the quadratic variation of an Itô process.

Published on 23 Feb 2026 - 4:56

102

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What is a Markov kernel of a Euler-Maruyama discretization?

Published on 26 Mar 2026 - 6:05

30

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show that $\mathbb{E}[f(\max(a, x + S_u))] \sim \sqrt{\frac{2}{\pi u}}\left((a-x) f(a)+\int_{a}^{\infty} f(y) d y\right)$

Published on 27 Jan 2020 - 21:29

23

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Notation used in integration in stochastic processes

Published on 28 Mar 2026 - 3:32

745

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Discrete Ito Lemma

Published on 31 Mar 2026 - 11:29

32

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Step verification in derivation of Ito formula.

Published on 28 Jan 2020 - 18:24

61

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Simple question regarding Ito integral

Published on 28 Mar 2026 - 3:25

359

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How to show this is not a martingale.

Published on 01 Apr 2026 - 7:19

38

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If $(M_t)$ is a Martingale, why considering $\int_0^t X_s^2d\left<M\right>_s$ instead of $\int_0^t X_s^2ds$?

Published on 31 Mar 2026 - 4:51

540

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Solve the SDE $dX_t=dB_t+\frac{c-X_t}{T-t}dt$

Published on 26 Mar 2026 - 6:06

51

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If $Y_t$ is an itô process, why $(dY_t)^2$ denote the Quadratic variation of $Y_t$?

Published on 23 Feb 2026 - 4:59

56

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Prove that $(Y_{t})_{t\in[0,\epsilon]}$ is a martingale.

Published on 23 Feb 2026 - 6:24

113

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Expectation of integral of Brownian motion, using Ito formula

Published on 28 Mar 2026 - 3:30

List Question

What is the meaning of $\mathbb{E}^x$?

Ito integrals as limit in probability in the case of continuous integrands

Calculation of the quadratic variation of an Itô process.

What is a Markov kernel of a Euler-Maruyama discretization?

show that $\mathbb{E}[f(\max(a, x + S_u))] \sim \sqrt{\frac{2}{\pi u}}\left((a-x) f(a)+\int_{a}^{\infty} f(y) d y\right)$

Notation used in integration in stochastic processes

Discrete Ito Lemma

Step verification in derivation of Ito formula.

Simple question regarding Ito integral

How to show this is not a martingale.

If $(M_t)$ is a Martingale, why considering $\int_0^t X_s^2d\left<M\right>_s$ instead of $\int_0^t X_s^2ds$?

Solve the SDE $dX_t=dB_t+\frac{c-X_t}{T-t}dt$

If $Y_t$ is an itô process, why $(dY_t)^2$ denote the Quadratic variation of $Y_t$?

Prove that $(Y_{t})_{t\in[0,\epsilon]}$ is a martingale.

Expectation of integral of Brownian motion, using Ito formula

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