We have collaborated with BBVA to perform an in-depth study of how much quantum computing resource it takes to obtain a practical benefit for a specific use case in finance that is one step beyond pricing complex derivatives; Credit Valuation Adjustments (CVA).
The CVA use case is both ubiquitously significant and computationally challenging. The core of the computational challenge, which is the cost of Monte Carlo simulation, is by no means unique to the use case that we are pursuing. It is a general challenge in many quantitative finance problems having to deal with risk analysis. This type of risk analysis has become increasingly important as more banks comply with the regulations such as those posed by the Basel Committee of Banking Supervision (BCBS) to minimize the systemic risk of the overall financial ecosystem.
Together with BBVA, we present a quantum algorithm and detailed resource estimation. We propose novel circuit designs that can significantly reduce the resource needed for solving the CVA problem but more importantly, we identify the remaining challenges that need to be addressed towards practical quantum advantage.
External Co-Author:
- Andrea Cadarso, Team Lead | Quantitative & Business Solutions Mexico at BBVA Corporate & Investment Banking
→ view Andrea’s Google Scholar Profile
