  This paper explores the utility of agent-based simulations in realistically
modelling market structures and sheds light on the nuances of optimal dealer
strategies. It underscores the contrast between conclusions drawn from
probabilistic modelling and agent-based simulations, but also highlights the
importance of employing a realistic test bed to analyse intricate dynamics.
This is achieved by extending the agent-based model for auction markets by
\cite{Chiarella.2008} to include liquidity providers. By constantly and
passively quoting, the dealers influence their own wealth but also have
ramifications on the market as a whole and the other participating agents.
Through synthetic market simulations, the optimal behaviour of different dealer
strategies and their consequences on market dynamics are examined. The analysis
reveals that dealers exhibiting greater risk aversion tend to yield better
performance outcomes. The choice of quote sizes by dealers is
strategy-dependent: one strategy demonstrates enhanced performance with larger
quote sizes, whereas the other strategy show a better results with smaller
ones. Increasing quote size shows positive influence on the market in terms of
volatility and kurtosis with both dealer strategies. However, the impact
stemming from larger risk aversion is mixed. While one of the dealer strategies
shows no discernible effect, the other strategy results in mixed outcomes,
encompassing both positive and negative effects.
