Adriano Baldeschi - Latest

• Liquidity Optimization in Gross Settlement Systems with Quantum Reordering: Application to TARGET2∗

  Staff working paper 2026-32 Valerio Astuti, Adriano Baldeschi, Luca Bastianelli, Giuseppe Bruno, Riccardo Russo, Ajit Desai, Danica Marsden

  Building on our earlier quantum algorithm, this paper shows that reordering queued payments can significantly reduce liquidity needs. The algorithm performs well on smaller payment batches, while traditional algorithms can process larger batches and deliver greater savings. Machine learning also helps identify which payment patterns offer the greatest potential for improvement.

  Content Type(s): Staff research, Staff working papers JEL Code(s): C, C6, C61, C63, C8, C83, E, E4, E42, E5, E58 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Money and payments, Payment and financial market infrastructures