Correlating S&P 500 Stocks with Twitter Data
نویسندگان
چکیده
Twitter is a widely used online social media. One important characteristic of Twitter is its real-time nature. In this paper, we investigate whether the daily number of tweets that mention Standard & Poor 500 (S&P 500) stocks is correlated with S&P 500 stock indicators (stock price and traded volume) at three different levels, from the stock market to industry sector and individual company stocks. We further apply a linear regression with exogenous input model to predict stock market indicators, using Twitter data as exogenous input. Our preliminary results demonstrate that daily number of tweets is correlated with certain stock market indicators at each level. Furthermore, it appears that Twitter is helpful to predict stock market. Specifically, at the stock market level, we find that whether S&P 500 closing price will go up or down can be predicted more accurately when including Twitter data in the model.
منابع مشابه
Using Tweets to Predict the Stock Market
It is found that some “important” twitter users’ words can influence the stock prices of certain stocks. The stock price of Tesla – a famous electric automobile company – for example, recently seen a huge rise after Elon Musk, the CEO of Tesla, updated his twitter about the self-driving motors. Besides, the Dow Jones and S&P 500 indexes dropped by about one percent after the Twitter account of ...
متن کاملForecasting Stock Price Movements Based on Opinion Mining and Sentiment Analysis: An Application of Support Vector Machine and Twitter Data
Today, social networks are fast and dynamic communication intermediaries that are a vital business tool. This study aims at examining the views of those involved with Facebook stocks so that we can summarize their views to predict the general behavior of this stock and collectively consider possible Facebook stock price movements, and create a more accurate pattern compared to previous patterns...
متن کاملPredictive Analytics On Public Data - The Case Of Stock Markets
This work examines the predictive power of public data by aggregating information from multiple online sources. Our sources include microblogging sites like Twitter, online message boards like Yahoo! Finance, and traditional news articles. The subject of prediction are daily stock price movements from Standard & Poor’s 500 index (S&P 500) during a period from June 2011 to November 2011. To fore...
متن کاملTwitter volume spikes and stock options pricing
The stock market is a popular topic in Twitter. The number of tweets concerning a stock varies over days, and sometimes exhibits a significant spike. In this paper, we investigate the relationship between Twitter volume spikes and stock options pricing. We start with the underlying assumption of the Black–Scholes model, the most widely used model for stock options pricing, and investigate when ...
متن کاملTweetTrader.net: Leveraging Crowd Wisdom in a Stock Microblogging Forum
TweetTrader.net is a stock microblogging forum that leverages the wisdom of crowds to aggregate the information contained in stock-related tweets. Based on insights from academic research on stock microblogs, the application integrates inputs from text classification, user voting and a proprietary Stock Game in order to extract the sentiment (i.e., the bullishness) of online investors with resp...
متن کامل