The book "Mining Financial News to Forecast Intraday Stock Price Movements" by Simon Bacher offers a comprehensive analysis of the possibilities of using unstructured financial news to predict intraday stock price movements. A system is developed based on text classification to forecast trends in stock prices. The author examines various types of news that may be relevant to stock prices and selects appropriate news sources. To filter out irrelevant news, suitable approaches are presented, including the implementation of a rule-based thesaurus. The book compares different automatic and manual labeling approaches and evaluates their impact on prediction accuracy. Additionally, novel features for price forecasting are introduced, and various text mining techniques and classifiers are analyzed. Finally, the impact of trading costs on potential profits is examined, and a market simulation is conducted to assess the practical profitability of the system.