In this paper we introduce a calibration procedure for validating of agent based models. Starting from the well-known financial model of Brock and Hommes 1998, we show how an appropriate calibration enables the model to describe price time series. We formulate the calibration problem as a...

We develop a stock-flow-consistent agent-based model that comprises a realistic mechanism of money creation and parametrize it to fit actually observed data. The model is used to make out-of-sample projections of broad money and credit developments under the commencement/termination of foreign...

We propose two novel methods to "bring ABMs to the data". First, we put forward a new Bayesian procedure to estimate the numerical values of ABM parameters that takes into account the time structure of simulated and observed time series. Second, we propose a method to forecast aggregate time...

We propose a novel approach to the statistical analysis of simulation models and, especially, agent-based models (ABMs). Our main goal is to provide a fully automated and model-independent tool-kit to inspect simulations and perform counter-factual analysis. Our approach: (i) is easy-to-use by...

The use of fundamentalist traders in the stock market models is problematic since fundamental values in the real world are unknown. Yet, in the literature to date, fundamentalists are often required to replicate key stylized facts. The authors present an agent-based model of the stock market in...

Comparison of macroeconomic simulation models, particularly agent-based models (ABMs), with more traditional approaches such as VAR and DSGE models has long been identified as an important yet problematic issue in the literature. This is due to the fact that many such simulations have been...

This paper presents a simulative model of a financial market, based on a fully operating order book with limit and market orders. The heterogeneity of traders is characterized not only with regards to their trading rules, but also by introducing a behavioral individual risk aversion and a...

We propose two novel methods to "bring ABMs to the data". First, we put forward a new Bayesian procedure to estimate the numerical values of ABM parameters that takes into account the time structure of simulated and observed time series. Second, we propose a method to forecast aggregate time...

This paper presents a simulative model of a financial market, based on a fully operating order book with limit and market orders. The heterogeneity of traders is characterized not only with regards to their trading rules, but also by introducing a behavioral individual risk aversion and a...

In this paper, we propose a new procedure for unconditional and conditional forecasting in agent-based models. The proposed algorithm is based on the application of amortized neural networks and consists of two steps. The first step simulates artificial datasets from the model. In the second...