In this study, we explore the dynamics of the stock market using an agent-based simulation platform. Our approach involves creating a multi-strategy market where each agent considers both fundamental and technical factors when determining their strategy. The agents vary in their approach to...

Drawing on the labour-augmented K+S agent-based model, this paper develops a two-country North-South ABM wherein the leader and the laggard country interact through the international trade of capital goods. The model aims to address sources of asymmetries and possible converge patterns between...

We propose a simple agent-based version of Paul de Grauwe's chaotic exchange rate model. In particular, we assume that each speculator follows his own technical and fundamental trading rule. Moreover, a speculator's choice between these two trading philosophies depends on his individual...

This paper develops a method to compute second-order perturbations of discretetime heterogeneous agent models. It addresses the three main tasks to make secondorder approximations tractable: state reduction, generating sufficient smoothness, and fast computation of the quadratic terms in the...

In this work, we ask whether tradable emissions permits, based on the cap-and-trade principle, provide better climate change and economic projections than alternative regulations for GHG emissions, such as operational permits which are commonly used to mitigate non-GHG emissions (prevention...

We develop a macroeconomic agent-based model to study the role of systemically important banks (SIBs) in financial stability and the effectiveness of capital surcharges on SIBs as a risk management tool. The model is populated by heterogeneous firms, consumers, and banks interacting locally in...

Although climate-induced liquidity risks can cause significant disruptions and instabilities in the financial sector, they are frequently overlooked in current debates and policy discussions. This paper proposes a macro-financial agent-based integrated assessment model to investigate the...

Public policies are not intrinsically positive or negative. Rather, policies provide varying levels of effects across different recipients. Methodologically, computational modeling enables the application of a combination of multiple influences on empirical data, thus allowing for heterogeneous...

We develop an agent-based model for the euro area that fulfils widely recommended requirements for nextgeneration macroeconomic models by i) incorporating financial frictions, ii) relaxing the requirement of rational expectations, and iii) including heterogeneous agents. Using macroeconomic and...

We study the distributional consequences of COVID-19 by using a stock-flow consistent agent-based model that captures some of the aspects of pandemic-related lockdowns. In particular, the model distinguishes between "essential" and "non-essential" industries, between jobs that can be done from...

We present Causal ABM, a methodology to derive causal structures describing complex underlying behavioral phenomena. Agent-based models (ABMs) have powerful advantages for causal modeling that have not been explored sufficiently. Unlike traditional causal estimation approaches which often result...

As Machine Learning (ML) systems are becoming increasingly used and more complex, different value systems are being coded into Artificial Intelligence (AI). In this paper, we delineate the value systems that many AI systems hold and suggest alternative value frameworks to combat inequities...

In this paper, we report the findings of a randomized experiment designed to test whether the order of play in two Trust Games influences the observed level of trust displayed by Trustors (as measured by the share of endowment sent to Trustees). Playing Trustor in the second game increases the...

Members of various species engage in altruism — i.e. accepting personal costs to benefit others. Here we present an incentivized experiment to test for altruistic behavior among AI agents consisting of large language models developed by the private company OpenAI. Using real incentives for AI...

The Lux--Marchesi model has been modified to include hierarchical interactions to enable the examination of the effect of hierarchies on the formation of speculative bubbles. The Lux--Marchesi model includes two types of traders:~fundamentalists and chartists, with the latter classified as...

We consider two data-driven approaches to hedging, Reinforcement Learning and Deep Trajectory-based Stochastic Optimal Control, under a stepwise mean-variance objective. We compare their performance for a European call option in the presence of transaction costs under discrete trading schedules....

We investigate whether the fee income from trades on the CFM is sufficient for the liquidity providers to hedge away the exposure to market risk. We first analyse this problem through the lens of continuous-time financial mathematics and derive an upper bound for not-arbitrage fee income that...

This paper explores the potential impacts of climate change and mitigation policies on the Euro Area, considering the uncertainty and heterogeneity in both climate and economic systems. Using the MATRIX model, a multi-sector and multi-agent macroeconomic model, we simulate various climate...

Using a refined version of the multi-country AB-SFC model of a Monetary Union already presented in Caiani et al. (2018a, 2019) the paper aims at providing a tentative assessment of the economic effects of transforming the European Monetary Union into an Intergovernmental Fiscal Transfer Union...

Improvements in energy efficiency can help facing the on-going climate and energy crises, yet the energy intensity of economic activities at the global level in recent years has decreased more slowly than it is required to achieve climate goals. Based on this premise, the paper builds a...

Drawing on the labour-augmented K+S agent-based model, this paper develops a two-country North-South ABM wherein the leader and the laggard country interact through the international trade of capital goods. The model aims to address sources of asymmetries and possible converge patterns between...

One of the most intriguing recent development is in blockchain, which has the potential to make collaborative economies safer by securing transactions and contracts. This makes it one of the most exciting recent improvements in IoT. The use of smart contracts in an Internet of Things environment...

In 2017 Robert Shiller, a Nobel Laureate, introduced Narrative Economics, an approach to explaining aspects of economies that are difficult to comprehend when analyzed using conventional methods: in light of narratives (i.e., stories) that participants in asset markets hear, believe, and tell...

This paper develops an incomplete equilibrium model with multi-agents' different risk attitudes and heterogeneous income/payout profiles. Particularly, we apply its concrete and computationally tractable model to reinsurance derivatives pricing and life-cycle investment, which are important for...

The paper presents the cutting-edge approaches to economic expectations that originate in the field of computational intelligence. Firstly, the AI-based expectation concepts are situated within the long-standing debate about expectation formation in economics. They are discussed as a middle way...

This paper develops a new multi-agent model to create a novel warning signal for equity investment, which well replicates actual stock and bond futures price dynamics through estimating fund flows of typical trading agents. Particularly, our model contains four types of agents taking equity/bond...

Linking decision systems, negotiating agents, management accounting, and computational accounting, this paper aims at exploring dynamic pricing strategies of a synthetic business-to-consumer online operation and a comparative analysis of evolving strategy-specific pricing optimization. Five...