6.11.2.3.7. statsmodels.sandbox.tsa.diffusion.GeometricBrownian

class statsmodels.sandbox.tsa.diffusion.GeometricBrownian(xzero, mu, sigma)[source]

Geometric Brownian Motion

:math:: dx_t &= mu x_t dt + sigma x_t dW_t

$x_t $ stochastic process of Geometric Brownian motion, $mu $ is the drift, $sigma $ is the Volatility, $W$ is the Wiener process (Brownian motion).

__init__(xzero, mu, sigma)[source]

6.11.2.3.7.1. Methods

__init__(xzero, mu, sigma)
expectedsim(func[, nobs, T, dt, nrepl]) get expectation of a function of a Wiener Process by simulation
sim([nobs, T, dt, nrepl])
simEM([xzero, nobs, T, dt, nrepl, Tratio]) from Higham 2001
simulateW([nobs, T, dt, nrepl]) generate sample of Wiener Process