Modelling Limit Order Book Dynamics via Subordinated Processes

The thesis introduces a model for Limit Order Book dynamics where price volatility is driven by a queue process inspired by polymer physics. Order arrivals and departures are represented as an M/M/1 Birth–Death process, which acts as stochastic volatility for price returns. Since volatility distribution is not analytically tractable, parameters are estimated maximizing Simulated Maximum Likelihood via Simulated Annealing. The calibrated model successfully reproduces many of the key statistical properties of high-frequency financial returns.