Modeling of financial market data for detecting important market characteristics as well as their abnormalities plays a key role in identifying their behavior. Researchers have proposed different types of techniques to model market data. One such model proposed by Sergie Maslov, models the behavior of a limit order book. Being a very simple and interesting model, it has several drawbacks and limitations.
This paper analyses the behavior of the Maslov model and proposes several variants of it to make the original Maslov model more realistic. The price signals generated from these models are analyzed by comparing with real life stock data and it was shown that the proposed variants of the Maslov model are more realistic than the original Maslov model.
