qiskit.finance.applications.ising.portfolio

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