||The thesis uses a sample of (the most liquid) securities traded on the Prague Stock Exchange (BCCP), to describe and further explore the high-frequency data (incl. price durations, intensity of trading, and volatility of bid-ask quotes) under the predictive framework of the information-based models of market microstructure. A major part of the thesis is hence devoted to testing of the relevance of such models for the Czech stock market (our results tend to favor the information-based models of market microstructure in this regard). The second part of the thesis analyzes the information content of stock trades. The main goal is to examine the ultimate impact on the stock price of the component of the (stock) trade which is unexpected and describe its major properties (among others, our results show that as a function of trade innovation size, the ultimate impact of the innovation on the quote is nonlinear, positive, and concave).