Quantum unary approach to option pricing

We present a quantum algorithm for European option pricing in finance, where the key idea is to work in the unary representation of the asset value. The algorithm needs novel circuitry and is divided in three parts: first, the amplitude distribution corresponding to the asset value at maturity is generated using a low-depth circuit; second, the computation of the expected return is computed with simple controlled gates; and third, standard amplitude estimation is used to gain quantum advantage. On the positive side, unary representation remarkably simplifies the structure and depth of the quantum circuit. Amplitude distributions use quantum superposition to bypass the role of classical Monte Carlo simulation. The unary representation also provides a postselection consistency check that allows for a substantial mitigation in the error of the computation. On the negative side, unary representation requires linearly many qubits to represent a target probability distribution, as compared to the logarithmic scaling of binary algorithms. We compare the performance of both unary vs binary option pricing algorithms using error maps, and find that unary representation may bring a relevant advantage in practice for near-term devices.

Automated summary

This study introduces a quantum algorithm for European option pricing in finance, utilizing unary representation of asset value for calculation. The algorithm is divided into three parts, which simplifies the quantum circuit structure and improves calculation accuracy using quantum advantage, but requires more qubits to represent target probability distribution.