Paper: arXiv 2303.06089
Authors: Alberto Manzano, Gonzalo Ferro, Álvaro Leitao, Carlos Vázquez, Andrés Gómez
Abstract
In this work we present an alternative methodology to the standard Quantum Accelerated Monte Carlo (QAMC) applied to derivatives pricing. Our pipeline benefits from the combination of a new encoding protocol, referred to as the direct encoding, and a amplitude estimation algorithm, the modified Real Quantum Amplitude Estimation (mRQAE) algorithm. On the one hand, the direct encoding prepares a quantum state which contains the information about the sign of the expected payoff. On the other hand, the mRQAE is able to read all the information contained in the quantum state. Although the procedure we describe is different from the standard one, the main building blocks are almost the same. Thus, all the extensive research that has been performed is still applicable. Moreover, we experimentally compare the performance of the proposed methodology against the standard QAMC employing a quantum emulator and show that we retain the speedups.
Complexity vs Empirical Score
- Math Complexity: 7.5/10
- Empirical Rigor: 5.0/10
- Quadrant: Holy Grail — high math complexity, high empirical rigor
Why this score: The paper introduces a novel encoding protocol (direct encoding) combined with a modified Quantum Amplitude Estimation algorithm for real option pricing. While mathematically sophisticated and validated via a quantum emulator, empirical rigor is limited by the absence of real hardware execution and extensive backtesting on real-world market datasets.
Research Flowchart
flowchart TD
A[Research Goal: Efficient Real Option Pricing via Quantum Computing] --> B[Inputs: Option Payoff Models & Probability Distributions]
B --> C[Step 1: State Preparation via Direct Encoding]
C --> D[Step 2: Amplitude Estimation via mRQAE Algorithm]
D --> E[Step 3: Benchmark against Standard QAMC via Quantum Emulator]
E --> F[Outcome: Retained Quadratic Speedup with Simplified Quantum Circuit Pipeline]