A seven-dimensional Hawkes process model is proposed for synthetic order flow generation, reproducing stylised facts of high-frequency markets.
We construct an agent-based model of the money market and use it to evaluate the effectiveness of central bank liquidity facilities.
A network model of interacting financial institutions is studied, with contagion propagating through balance-sheet linkages and fire-sale externalities.
Reinforcement learning agents are placed in a simulated market environment; we analyse the convergence of strategies and impact on market efficiency.
We simulate a double auction market populated by heterogeneous agents and study emergent price dynamics, fat tails, and volatility clustering.