Simulation from a process given by "complicated" SDE

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SUMMARY

This discussion focuses on simulating paths from the stochastic differential equation (SDE) defined as $$ dX_t = -a(X_t-1)dt+b\sqrt{X_t}dB_t $$, which is identified as the Cox-Ingersoll-Ross model, commonly used for modeling interest rates. The user seeks assistance in determining the distribution of the process and constructing a Log Euler scheme for simulation. The proposed method involves generating a sequence of independent standard normal pseudo-random numbers and applying the SDE iteratively to simulate projected values of ##X_t## over a specified time interval.

PREREQUISITES
  • Understanding of stochastic differential equations (SDEs)
  • Familiarity with the Cox-Ingersoll-Ross model
  • Knowledge of Brownian motion and Wiener processes
  • Proficiency in numerical methods for simulation, particularly Log Euler schemes
NEXT STEPS
  • Research the distribution properties of the Cox-Ingersoll-Ross model
  • Study the implementation of Log Euler schemes in stochastic simulations
  • Explore methods for generating independent standard normal pseudo-random numbers
  • Investigate advanced techniques for simulating stochastic processes in financial modeling
USEFUL FOR

Quantitative analysts, financial engineers, and researchers in stochastic calculus who are involved in modeling and simulating financial processes, particularly those related to interest rates.

econmajor
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Actually this is more of a simulation question but since PF doesn't have Simulation category I ask here.
I need to simulate a path from a proces given by this Stochastic DE:
$$ dX_t = -a(X_t-1)dt+b\sqrt{X_t}dB_t $$ where ##B_t## is wiener process/brownian motion and a and b are just some constants. In order to design a simulation scheme to this process I need to find it's distribution. Please help me find the distribution. I don't know whether this is advanced or Intermediate?
 
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The SDE is that of the Cox-Ingersoll-Ross model that is used for processes like interest rates. If you look up the wiki page on that model you'll find information about the distribution of a future value ##X_t##.
 
How will a Log Euler scheme for this process look like? I still haven't a proper way to construct a simulation.
 
To simulate a random sequence of projected values of ##X_t## over a period ##[0,T]## with time steps of length ##dt\triangleq T/n##, you just start with the initial value ##X_0##, generate a set of ##n## independent standard normal pseudo-random numbers ##Z_1,...,Z_n## then apply the above equation ##n## times for ##j=1## to ##n##, with ##t=t_j## taking the value ##(j-1)dt## and ##dW_{t_j} = Z_j \sqrt{dt}##.

Repeat ##m## times, where ##m## is the number of simulated paths you want, using a different random sequence of ##Z_j## each time.
 
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