June 30, 2020 · 1 min read

Dynamic Portfolio Optimization with Real Datasets Using Quantum Processors and Quantum-Inspired Tensor Networks

In this paper we tackle the problem of dynamic portfolio optimization with discrete variables.

Multiverse Computing

This problem, well-known to be NP-Hard, is central to quantitative finance. We find the optimal trading trajectory over 8 years for 52 assets using quantum and quantum-inspired algorithms. These are benchmarked against the current best available solvers.

Read the full article on arxiv.org