The present thesis is an exploratory data analysis of the high frequency dataset of NBBO quotes (national best bid and offer) for the NYSE market. The focus of the analysis is on the assumptions and results of the Markovian micro structure model introduced in Cont and de Larrard (2013). The model provides distributions for the durations between mid price changes, probabilities of mid price changes conditioned to the state of the order book and a formula describing price intraday volatility in terms of pure microstructure statistics. We verify model assumptions and compare the theoretical results with empirical data for the stocks from the Dow Jones Industrial Average Index, one of the most liquid markets in the world. In this thesis, we conclude that the model gives a good description of the market dynamics at the high frequency level, and produces consistent results with the data, including the aforementioned volatility relationship.