Swot Analysis Of Chipotle

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FINDINGS
From our regression we have found that there is evidence that our model is valid as all the terms are statistically significant with the exception of the squared term, and the model as a whole is statistically significant. Moreover, from our aforementioned analyses, we can conclude that:  Sentiment Scores are impacted by the news (positive or negative) about the company.
 A day after the negative financial news has a greater negative impact on the closing price than a percentage point change on sentiment score. Probably because bad news spread like a virus!
 For every day after the negative financial news, the sentiment score would have lesser impact on the closing price.
 Though none of the online sources exclusively mentioned “Subway” as Chipotle’s

LIMITATIONS
While we have acquired a significant amount of data, it the form of stock data, tweets over time, and qualitative news information regarding what has been happening at Chipotle lately our ability to obtain results and meaningful predictions has been limited to a certain degree by a few factors worth mentioning.
The first limitation is we are only looking at twitter and stock data over a period of a few weeks.
With this data we were able to obtain sentiment scores, and compare them to the stock prices recently, but since we can’t observe the correlation of the sentiment scores and the stock prices from a long term perspective, there is potential that a type 1 or type 2 errors could be made. A type 1 error also called a false positive could manifest if our short term data correlates well with the movement of stock prices, during this period, but in the larger scheme of things there isn’t a meaningful correlation over time. A type 2 error could also be present, meaning that for the time period we have considered there is no correlation between the sentiment score, but if we compared the results over time we would find a relationship between the sentiment scores and stock