Order Book Markov Chain

Algorithm

The Order Book Markov Chain models the dynamic evolution of limit order books as a stochastic process, representing state transitions based on observed order flow. This approach frames the order book not as a static snapshot, but as a system shifting between discrete states defined by price levels and order quantities, enabling probabilistic forecasting of future book configurations. Its core function lies in quantifying the likelihood of transitioning from one order book state to another, crucial for understanding short-term market impact and liquidity dynamics, particularly within cryptocurrency exchanges. Application of this model allows for the simulation of order book behavior under various trading scenarios, informing algorithmic trading strategies and risk assessment.