QAOA portfolio rebalancing implementation

Quantum Cost Operator

portfolio_cost_operator(problem)

Quantum cost operator for the discrete portfolio rebalancing problem, as described in https://arxiv.org/pdf/1911.05296.pdf.

It is depended on the problem instance, including the old portfolio positions, the normalized covariance matrix, the normalized asset returns and trading costs. See example implementation for formatting.

Parameters:

problemList

A list containing a the relevant data for the problem instance.

Returns:

portfolio_cost_op: function

A callable function to be applied to a QuantumArray for solving the problem instance.

Classical cost function

portfolio_cl_cost_function(problem)

Classical cost function for the discrete portfolio rebalancing problem, as described in https://arxiv.org/pdf/1911.05296.pdf.

|It is depended on the problem instance, including the old portfolio positions, the normalized covariance matrix, the normalized asset returns and trading costs. See example implementation for formatting.

Parameters:

problemList

A list containing a the relevant data for the problem instance.

Returns:

cl_cost_function: function

A callable function to calculate the cost value of the problem solution.

State initialization

portfolio_init(lots)

Initial state for the discrete portfolio rebalancing problem, as described in https://arxiv.org/abs/1904.07358.

Depending on the number of lots a QuantumArray is prepared, where the first index describes the short positions held and the second index describes the long postions held.

Parameters:

lotsInt

The number of lots in the initial portfolio position

Returns:

state_prep: function

A callable function to be applied to a QuantumArray to receive the initial state for the problem.