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Autocallable Options Pricing with Integration-Based Exponential Amplitude Loading

Published: July 25, 2025 | arXiv ID: 2507.19039v1

By: Francesca Cibrario , Ron Cohen , Emanuele Dri and more

Potential Business Impact:

Makes financial calculations much faster using quantum computers.

Business Areas:

Quantum Computing Science and Engineering

We present a comprehensive quantum algorithm tailored for pricing autocallable options, offering a full implementation and experimental validation. Our experiments include simulations conducted on high-performance computing (HPC) hardware, along with an empirical analysis of convergence to the classically estimated value. Our key innovation is an improved integration-based exponential amplitude loading technique that reduces circuit depth compared to state-of-the-art approaches. A detailed complexity analysis in a relevant setting shows an approximately 50x reduction in T-depth for the payoff component relative to previous methods. These contributions represent a step toward more efficient quantum approaches to pricing complex financial derivatives.