performOptimization
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 consideredalpha
(float): A parameter limiting the second moment of the pricing kernellambda
(float): A parameter for the Tikhonov-type regularizationomega_l
(numpy.ndarray): A 1D numpy array of integers representing the disjunct state space partitions of interestsp
(numpy.ndarray): A 1D numpy array of floats representing the spot prices in different states of the worldstrike
(numpy.ndarray): A 1D numpy array of floats representing the strike prices of different optionsbid
(numpy.ndarray): A 1D numpy array of floats representing the bid prices of different optionsask
(numpy.ndarray): A 1D numpy array of floats representing the ask prices of different optionspflag
(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
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