We are using the HTTP REST API called “NEWS API”. We will perform GET request providing the query parameters such as Stock, Name and Timestamp. We will perform data cleaning and transformation on the resulting JSON response. We will analyze further on researching other data sources based on the outcome.
We are going to perform comprehensive analysis on NewsApi using Natural Language Processing (NLP). This will help us in analyzing the emotions and predicting stock movements. This will help us in mitigating the risk involved and make informed decision whether to hold or sell stocks.
Market hypothesis assumes that a stock’s performance would have its impact from historical information or current events. With the advent of Artificial Intelligence and Machine learning algorithms, we could make predictions in the closest range possible. This inspired us to pursue this analysis to learn more about market efficiency.
In order to analyze the data we will be doing a preliminary data analysis also called as Exploratory data analysis to get the overview of shape of the data and get more insights. Based on the results and further analysis we will perform data cleaning such as removing invalid or absurd values/ outliers and transform the data accordingly. For the same we will be using tools such as RStudio, RMarkdown and libraries such as keras, matplotlib, newsapi etc. using methods such as Natural Language Processing, Sentiment Analysis .
We will evaluate our results based on the sentiment and corresponding stock movement. We can showcast this by using sklearn library and matplotlib for data analysis and visualization.