STOCK PRICE PREDICTIONS
STOCK PRICE PREDICTIONS

Summary/Abstract: E-learning, in most contexts, is becoming an accessible and efficient method of training through which people could acquire new knowledge. Due the difference between epochs, reading and analysing the growing flow of information has become a very challenging task for financial professionals. It is known that fake news centred on the stock price is the most pressing problem each of is facing in a radically altered media landscape. The conventional economic data news is one of the major drivers for financial markets. Moreover, news is becoming a major driver for market sentiment: there can be news related to macro finance. How can we solve some of the challenges of misinformation in the digital age? Visibly, the discontent has been fed by fears of: slowing economic progress, especially in rich societies, flattening social mobility, concerns about the future brought by shifts in technology, etc. This entire situation, fuelled by different fluctuations (e.g. stock price), is acutely expressed online (Social Media networks, journals on economical-financial issues, etc.) by means of popular anger and distrust of elites from financial economic branches. This paper will address the problem of correlating the open information provided by companies, economic publications, and social media rumours with impact on stock price. It includes a wide range of data that can be used for training, testing and evaluation of a model for Romanian. The aim of this study is to implement an innovative service able to predict potential falling or rising of stock prices for public and private companies.

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