PyProcess 0.2
PyProcess is a Python class library used to exactly simulate stochastic processes, and their properties.
Using this library, you can simulate the following random processes:
Continuous Diffusions
- Brownian Motion
- Geometric Brownian Motion
- CEV
- CIR
- Square Bessel Process
- Ornstein Uhlenbeck process
- Time-integrated Ornstein Uhlenbeck process
- Levy Processes
- Bessel Process (coming soon)
- Fractional Brownian Motion (coming soon)
Jump Diffusions
- Gamma process
- Variance-gamma process
- Geometric Gamma process
- Inverse Gaussian process NEW
- Normal Inverse Gaussian process NEW
Step Processes
- Renewal process
- Poisson process
- Compound poisson process
- marked-poisson process
- Fractional poisson process (coming soon)
See fun examples of the processes you can simulate [here] (http://pyprocess.70percentfatfree.com)
Simulation Algorithms + PyProcess 0.2
See the report for PyProcess 0.2's background.