Buying commodities is a critical issue for multiple industries because the variations of stock prices are induced not only by multiple economic parameters but also by external events. Raw material buyers must keep track of information in numerous fields, which constitutes a major challenge considering the exponential growth of online data. To tackle this issue, we propose an event detection approach in order to assist them in their anticipation process. Indeed, a lot of contextual information is contained in text and exploiting it can allow one to improve its anticipation ability. Thus, we develop a framework of event detection and qualification, then we quantify the impact of these events on stock market to help buyers in their anticipation process. In this paper, we will first introduce our context, then explain the scope of our work and our goals. After detailing the related work, we will present our proposition, conclude and propose some future work possibilities. CCS CONCEPTS • Information systems → Data management systems; Information retrieval; • Computing methodologies → Natural language processing.