class_docstr: 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).
class_docstr_tok: ["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",")","."]
code: def _sig(self, *args, **kwds):
      x = kwds["x"]
      return self.sigma * x
  
imports: import numpy
  from scipy import stats, signal
  import matplotlib.pyplot
label_desc: Use image node_id 3 for calling the GeometricBrownian obj's underlying member method code with example usage: obj._sig() and returns: unknown