Quantum Algorithms and Their Applications in Finance

October 15, 2024 3:30 PM Singapore (Registration starts at 3:20 PM)

Abstract

In this talk, we explore new quantum algorithms and the challenges they face in real-world applications of quantum computing. To assess the true potential of quantum computers, we need clear use cases and benchmarks. In the first part of the talk we discuss use cases, with focus on quantum algorithms for pricing financial derivatives, specifically European and American options. For American options, we present a quantum version of the well-known least-square Monte Carlo (LSMC) algorithm, which approximates the solution to the optimal stopping problem inherent in their pricing. For European options, we approach the pricing problem by solving two linear optimization problems, leveraging various quantum algorithms designed for linear programming. In the second part of the talk, we address a major challenge in making these quantum algorithms practical: implementing circuits for quantum random access memory (QRAM). We first explore QRAM from a theoretical perspective, introducing new architectures that achieve constant-depth circuit complexity (assuming unbounded Fan-Out gates). Finally, we discuss ongoing research into the energetic costs associated with different quantum architectures, which is crucial for scaling these solutions.

PAPERS:
Based on: https://arxiv.org/abs/2111.15332 and https://www.nature.com/articles/s41598-024-68838-1

About the Speaker

Alessandro Luongo is a researcher in quantum algorithms at the Centre for Quantum Technologies (CQT) of Singapore, part of the National University of Singapore (NUS). He obtained his PhD at the Institut de Recherche en Informatique Fondamentale (IRIF) of Paris. His work focuses on developing new quantum algorithms, and applying them to problems in machine learning, finance, and cybersecurity with the aim of outperforming the best classical approaches. While his primary interest lies in theoretical research, Alessandro also enjoys collaborating with industry to bridge the gap between theory and practice, ensuring that theoretical advancements have real-world impact.