Questions tagged [stochastic-ode]

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Solving SDEs in R until a prespecified value is reached

I am trying to solve a system of SDEs in R using the Diffeqr package. A simplified version of the system: ...
4
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0answers
63 views

Probability approximation: monte carlo VS sde

I have a probability measure $\mu$ (say, in $\mathbb{R}^{d}$, with density) and I want to approximate it numerically. Today I noticed that my measure is ergotic for a certain Stochastic Differential ...
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1answer
106 views

Solving an SDE with time-dependent parameter in R

I am trying to solve a system of SDEs in R using the Diffeqr package. Let's reduce the system to a simple ODE: ...
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0answers
40 views

How to determine the order of convergence of the Euler-Maruyama method?

This question is originally posted in Quant.StackExchange but has been unanswered for some time so I ask in here. To make this simple let us consider the Geometric Brownian Motions (GBM). My ...
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0answers
129 views

SDE solver in python: manual determination of integrator step size (dt)

Aim: I am trying to solve a system of SDEs, while using the SDEint package in python 3.x. It is a system of SDEs adapted from and inspired by the Zombie Apocalypse ...
2
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1answer
80 views

Jump-Diffusion process: practical solver beyond Euler method?

A jump-diffusion process is a stochastic process where both continuous noise (in my case complex Wiener noise $dZ,dZ^*$ such that $dZ^2=dZ^{*2}=0,|dZ|^2=dt$) and discrete Jumps (in my case Poissonian $...
3
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1answer
48 views

Testing Wiener process splitting in adaptive-step SDE integrators

I am investigating various methods for adaptive-step integration of stochastic differential equations and trying to implement them. All of the papers that I've seen (e.g. H. Lamba, J. Comp. App. Math. ...
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1answer
34 views

Open source solver for continuous-time stochastic non-linear DAEs (SDAEs)

I am trying to solve a system of non-linear index-1 DAEs in which the derivatives of the state variables, $x(t)$ are corrupted by additive noise, $w(t)$ (whose co-variance matrix is known). $\dot x(t)...
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1answer
253 views

Easily understandable argument that normal Runge–Kutta methods cannot be generalised to SDEs?

A naïve approach to solving stochastic differential equations (SDEs) would be: take a regular multi-step Runge–Kutta method, use a sufficiently fine discretisation of the underlying Wiener process, ...
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2answers
184 views

What’s so great about derivative-free solvers for SDEs?

I am trying to familiarise myself with SDEs and have been reading a few review papers on the topic. They leave the impression that a great deal of work has been put into solvers that are derivative-...