activity
20232026
most citedEvaluating generation of chaotic time series by convolutional generative adversarial networks

2 citations · 2 across the 3 of their papers we have counts for

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Showing 2025Show all

2 papers · 1 filter

cs.CY2025

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…

q-fin.CP2025

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…