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...

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...

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...