Mathematical programming (MP) is a widespread approach to depict production and investment decisions of agents in agent-based models (ABM) related to agriculture. However, introducing dynamics and indivisibilities in MP models renders their solution computing time intensive. We present a...

A new algorithm for calibrating agent-based models is proposed, which employs a popular gradient boosting framework. Machine learning techniques are not used to develop a surrogate model, but rather assist in narrowing down the parameter space during the search for optimal parameters. Our...

In order to verify the effects of machine learning in a market structure, an evolutionary model containing firms that use a genetic algorithm to decide their investment in innovative R&D was developed. These firms share the market, with two other types of firms, those with a fixed rate of...

The "histogram method" (Young, 2010), while the standard approach for analyzing distributional dynamics in heterogeneous agent models, is linear in optimal policies. We introduce a novel method that captures nonlinearities of distributional dynamics. This method solves the distributional...

We characterize policy interventions directed to minimize the cost to the deposit guarantee scheme and the taxpayers of banks with legacy problems. Non-performing loans (NPLs) with low and risky returns create a debt overhang that induces bank owners to forego profitable lending opportunities....

This paper introduces a formulation of the optimal network compression problem for financial systems. This general formulation is presented for different levels of network compression or rerouting allowed from the initial inter-bank network. We prove that this problem is, generically, NP-hard....

We characterize policy interventions directed to minimize the cost to the deposit guarantee scheme and the taxpayers of banks with legacy problems. Non-performing loans (NPLs) with low and risky returns create a debt overhang that induces bank owners to forego profitable lending opportunities....

We present efficient partial differential equation (PDE) methods for continuous time mean-variance portfolio allocation problems when the underlying risky asset follows a jump-diffusion. The standard formulation of mean-variance optimal portfolio allocation problems, where the total wealth is...