Rare Events in Financial Markets

Rare events, also known as “black swans”, in financial time series can be seen as sporadic and drastic jumps in financial assets returns. These can be associated with major historical episodes such as depressions and similar country-specific events, market crashes or severe industry or company down-turns. The goal of this project is to investigate the potential for quantum computing to mitigate these limitations leveraging the most recent developments in quantum-enhanced Monte-Carlo sampling, stochastic modelling and dimensional reduction to design a set of quantum algorithms for rare event estimation that:

1. Enhance the accuracy in estimating the probability of specific rare events.

2. Reduce systematic error caused by dimensional reduction.