performOptimization
Last updated
Last updated
Function retrieving a martingale distribution Q and a physical distribution P s.t.
Q prices financial instrument correctly
The second moment of the pricing kernel by the bound
The risk-neutral variance is higher than the physical expected variance
Parameters:
n
(int): The number of states considered
alpha
(float): A parameter limiting the second moment of the pricing kernel
lambda
(float): A parameter for the Tikhonov-type regularization
omega_l
(numpy.ndarray): A 1D numpy array of integers representing the disjunct state space partitions of interest
sp
(numpy.ndarray): A 1D numpy array of floats representing the spot prices in different states of the world
strike
(numpy.ndarray): A 1D numpy array of floats representing the strike prices of different options
bid
(numpy.ndarray): A 1D numpy array of floats representing the bid prices of different options
ask
(numpy.ndarray): A 1D numpy array of floats representing the ask prices of different options
pflag
(numpy.ndarray): A 1D numpy array of booleans indicating whether an option is a call (True
) or a put (False
) option
Output:
(tuple): includes two elements:
P distribution: The recovered P distribution
Q distribution: The recovered Q distribution