2 citations · 4 across the 10 of their papers we have counts for
11 papers
EconSimulacra: A Digital Twin Platform of Socio-Economic Systems Powered by LLM Agents
Ryuji Hashimoto, Masahiro Kaneko, Kentaro Ueda +2
Real-world social behavior emerges from tightly coupled domains: economic conditions shape mobility and social interactions, while online attention and offline activity feed back i…
Financial Market as a Self-Organized Ecosystem: Simulation via Learning with Heterogeneous Preferences
Ryuji Hashimoto, Ryosuke Takata, Masahiro Suzuki +2
Agent-based models provide a constructive approach to studying emergent dynamics in life-like systems composed of interacting, adaptive agents. Financial markets serve as a canonic…
From Heard to Lived Opinions: Simulating Opinion Dynamics with Grounded LLM Agents in Economic Environments
Ryuji Hashimoto, Masahiro Kaneko, Ryosuke Takata +2
Opinion dynamics (OD) studies how individual opinions evolve and generate collective patterns such as consensus and polarization. While recent work explores OD using populations of…
Emergence from Emergence: Financial Market Simulation via Learning with Heterogeneous Preferences
Ryuji Hashimoto, Ryosuke Takata, Masahiro Suzuki +2
Agent-based models help explain stock price dynamics as emergent phenomena driven by interacting investors. In this modeling tradition, investor behavior has typically been capture…
Agent-Based Simulation of a Financial Market with Large Language Models
Ryuji Hashimoto, Takehiro Takayanagi, Masahiro Suzuki +1
In real-world stock markets, certain chart patterns -- such as price declines near historical highs -- cannot be fully explained by fundamentals alone. These phenomena suggest the…
Towards Realistic and Interpretable Market Simulations: Factorizing Financial Power Law using Optimal Transport
Ryuji Hashimoto, Kiyoshi Izumi
We investigate the mechanisms behind the power-law distribution of stock returns using artificial market simulations. While traditional financial theory assumes Gaussian price fluc…
Are Generative AI Agents Effective Personalized Financial Advisors?
Takehiro Takayanagi, Kiyoshi Izumi, Javier Sanz-Cruzado +2
Large language model-based agents are becoming increasingly popular as a low-cost mechanism to provide personalized, conversational advice, and have demonstrated impressive capabil…
CoFinDiff: Controllable Financial Diffusion Model for Time Series Generation
Yuki Tanaka, Ryuji Hashimoto, Takehiro Takayanagi +3
The generation of synthetic financial data is a critical technology in the financial domain, addressing challenges posed by limited data availability. Traditionally, statistical mo…
The Impact and Feasibility of Self-Confidence Shaping for AI-Assisted Decision-Making
Takehiro Takayanagi, Ryuji Hashimoto, Chung-Chi Chen +1
In AI-assisted decision-making, it is crucial but challenging for humans to appropriately rely on AI, especially in high-stakes domains such as finance and healthcare. This paper a…
Beyond Turing Test: Can GPT-4 Sway Experts' Decisions?
Takehiro Takayanagi, Hiroya Takamura, Kiyoshi Izumi +1
In the post-Turing era, evaluating large language models (LLMs) involves assessing generated text based on readers' reactions rather than merely its indistinguishability from human…
Is ChatGPT the Future of Causal Text Mining? A Comprehensive Evaluation and Analysis
Takehiro Takayanagi, Masahiro Suzuki, Ryotaro Kobayashi +2
Causality is fundamental in human cognition and has drawn attention in diverse research fields. With growing volumes of textual data, discerning causalities within text data is cru…