Source code for qiskit_finance.circuit.library.payoff_functions.european_call_pricing_objective

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"""The European Call Option Expected Value."""

from typing import Tuple
from qiskit.circuit import QuantumCircuit
from qiskit.circuit.library import LinearAmplitudeFunction


[docs]class EuropeanCallPricingObjective(QuantumCircuit): """The European Call Option Expected Value. Evaluates the expected payoff for a European call option given an uncertainty model. The payoff function is f(S, K) = max(0, S - K) for a spot price S and strike price K. """ def __init__( self, num_state_qubits: int, strike_price: float, rescaling_factor: float, bounds: Tuple[float, float], ) -> None: """ Args: num_state_qubits: The number of qubits used to represent the random variable. strike_price: strike price of the European option rescaling_factor: approximation factor for linear payoff bounds: The tuple of the bounds, (min, max), of the discretized random variable. """ # create piecewise linear amplitude function breakpoints = [bounds[0], strike_price] slopes = [0, 1] offsets = [0, 0] f_min = 0 f_max = bounds[1] - strike_price european_call = LinearAmplitudeFunction( num_state_qubits, slopes, offsets, domain=bounds, image=(f_min, f_max), breakpoints=breakpoints, rescaling_factor=rescaling_factor, ) super().__init__(*european_call.qregs, name="ECEV") self.data = european_call.data self._european_call = european_call
[docs] def post_processing(self, scaled_value: float) -> float: """Map the scaled value back to the original domain. Args: scaled_value: The scaled value. Returns: The scaled value mapped back to the original domain. """ return self._european_call.post_processing(scaled_value)