In this project, we attempt to answer the question “Is the market aware of the situation which has taken place regarding a certain event and has it reacted to it?”. This is commonly referred to as “Priced In”, i.e. ``are all available information regarding a particular event or news, or potential outcome, already reflected in the current price of a financial asset, stock market index, or ticker symbol?''. Our approach primarily consisted of data scraping and cleaning, and training a Recurrent Neural Network. The results demonstrate that for events such as Earnings Reports, the market efficiently captures the effects through either anticipation before the event or re-adjustments after the event, and the model’s accuracy in predicting the overall effect of events (positive or negative) based on market & stock history highlights its robustness and practicality in applications.