A non-interactive time-delayed publicly verifiable scheme for quantum computation compiled from private 2-round protocols via time-lock puzzles and commitments, proven secure in the quantum random oracle model with CRS.
Quantum computational finance: Monte Carlo pricing of financial derivatives
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abstract
Financial derivatives are contracts that can have a complex payoff dependent upon underlying benchmark assets. In this work, we present a quantum algorithm for the Monte Carlo pricing of financial derivatives. We show how the relevant probability distributions can be prepared in quantum superposition, the payoff functions can be implemented via quantum circuits, and the price of financial derivatives can be extracted via quantum measurements. We show how the amplitude estimation algorithm can be applied to achieve a quadratic quantum speedup in the number of steps required to obtain an estimate for the price with high confidence. This work provides a starting point for further research at the interface of quantum computing and finance.
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Quantum-accelerated MLMC methods for BDSDE-based SPDE derivative pricing and Greeks achieve sampling complexity improvement from O(ε^{-2}) to O(ε^{-1}).
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Time-Delayed Publicly Verifiable Quantum Computation for Classical Verifiers
A non-interactive time-delayed publicly verifiable scheme for quantum computation compiled from private 2-round protocols via time-lock puzzles and commitments, proven secure in the quantum random oracle model with CRS.
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Quantum Derivative Pricing for SPDEs via BDSDE Representation
Quantum-accelerated MLMC methods for BDSDE-based SPDE derivative pricing and Greeks achieve sampling complexity improvement from O(ε^{-2}) to O(ε^{-1}).