In this paper, authors introduce a suite of advanced models for automated market makers targeting optimized trading operations. These models feature sophisticated price dynamics such as stochastic volatility and utilize Hawkes processes for microstructural modeling. Additionally, models adjust based on the variable demand from liquidity takers employing Hawkes or Markov-modulated Poisson processes.

Key Insights:

• Incorporation of advanced stochastic models to improve the quote accuracy.
• Utilization of microstructural price models for realistic market simulations.
• Addressing demand variability through adaptive processes.

This paper is crucial as it offers a practical toolset for market operators to refine their trading mechanisms in real-time markets. It opens up possibilities for further research in automated trading enhancements.