Italian Abstract: Presentiamo un modello stocastico multivariato, per sviluppare stress test finalizzati a valutare l'adeguatezza patrimoniale delle banche e il loro grado di fragilità finanziaria. L'articolo fornisce una descrizione teorica del metodo e delle caratteristiche essenziali del...

We develop a Bayesian methodology for systemic risk assessment in financial networks such as the interbank market. Nodes represent participants in the network and weighted directed edges represent liabilities. Often, for every participant, only the total liabilities and total assets within this...

We put forward a Merton-type multi-factor portfolio model for assessing banks' contributions to systemic risk. This model accounts for the major drivers of banks' systemic relevance: size, default risk and correlation of banks' assets as a proxy for interconnectedness. We measure systemic risk...

Banks must manage their trading books, not just value them. Pricing includes valuation adjustments collectively known as XVA (at least credit, funding, capital and tax), so management must also include XVA. In trading book management we focus on pricing, hedging, and allocation of prices or...

We present a stochastic simulation forecasting model to stress-test banks' capital adequacy and to estimate probability of infringement of regulatory capital ratios and default probability. The stochastic methodology proposed is based on a simplified reduced model that provides a manageable...

The largest US banks and Systemically Important Financial Institutions are required by regulatory mandate to estimate the operational risk capital they must hold using an Advanced Measurement Approach (AMA) as defined by the Basel II/III Accords. Most of these institutions use the Loss...

We develop two neo-classical methods for function approximations, the generalized stochastic sampling (gSS) and the functional tensor train (fTT) methods, that are high-performing alternatives to generic deep neural networks (DNNs) currently routinely proposed for function approximations in...

Computational methods both open the frontiers of economic analysis and serve as a bottleneck in what can be achieved. Using the quantum Monte Carlo (QMC) algorithm, we are the first to study whether quantum computing can improve the run time of economic applications and challenges in doing so....

In light of the COVID 19 crisis, the Federal Reserve has carried out stress tests to assess if major banks have sufficient capital to ensure their viability should a new and perhaps unprecedented crisis emerge. The Fed argues that the scenarios underpinning these stress tests are severe but...

The recent evolution of prudential regulation establishes a new requirement for banks and supervisors to perform reverse stress test exercises in their risk assessment processes, aimed at detecting default or near-default scenarios. We propose a reverse stress test methodology based on a...