Using the quantum Monte Carlo algorithm, we study whether quantum computing can improve the run time of economic applications and challenges in doing so. We apply the algorithm to two models: a stress testing bank model and a DSGE model solved with deep learning. We also present innovations in the algorithm and benchmark it to classical Monte Carlo.
Because of the COVID-19 pandemic, public interest in the Bank’s balance sheet and, more specifically, the size of settlement balances, has grown. This paper deconstructs the concept of settlement balances and provides some context on their history, current state and possible future evolution.