qiskit.finance.applications.ising.portfolio

Convert portfolio optimization instances into Pauli list

Functions

get_operator(mu, sigma, q, budget, penalty)	get qubit op
portfolio_expected_value(x, mu)	returns portfolio expected value
portfolio_value(x, mu, sigma, q, budget, penalty)	returns portfolio value
portfolio_variance(x, sigma)	returns portfolio variance
random_model(n[, seed])	Generate random model (mu, sigma) for portfolio optimization problem.

get_operator(mu, sigma, q, budget, penalty)

get qubit op

portfolio_expected_value(x, mu)

returns portfolio expected value

portfolio_value(x, mu, sigma, q, budget, penalty)

returns portfolio value

portfolio_variance(x, sigma)

returns portfolio variance

random_model(n, seed=None)

Generate random model (mu, sigma) for portfolio optimization problem.

Parameters

• n (int) – number of assets.

• seed (int or None) – random seed - if None, will not initialize.

Returns

expected return vector numpy.ndarray: covariance matrix

Return type

numpy.narray