![]() ![]() The present study was aimed to fill that gap in the literature. However, all of these studies have focused on predicting the movements of the stock market or individual stock prices, not on determining the magnitude of the stock price effect of bad news compared to good news for specific companies. Considering that this category of assets has not yet gained the trust of investors, its price is more susceptible to volatility and the correlation between news releases and price behavior is more accentuated. The sentiment analysis of social media has also been used to study the effect of news flows on the price of cryptocurrencies. Though the authors of some studies achieved a degree of prediction capability, some others concluded that social sentiment is not useful for stock price prediction. Several published studies have described new models for predicting stock prices mostly using social opinions. Social networks’ flow of opinions, in combination with the traditional prediction models, have significantly improved the success rate of prediction methodologies. With the common use of social networks, the opinion of stockholders has been more present than ever before. In contemporary markets, stockholders’ opinions are considered to be faithful indicators of the future values of their investment holdings. The researchers of numerous publications have aimed to build models to predict stock prices because traditional models are not fully successful for this task. What affected the price more was the headline “Cristiano Ronaldo removes coke bottles and Coca-Cola stock prices drop” by CNN Spain on 16 June, which impacted the price on the 18th and 23rd of the same month. Even more, the stock closed $0.30 above the $55.26 by the end of the trading day. Cristiano Ronaldo made the declaration at 9:43 EST, and the stock price had dropped to $55.26 by 9:40 EST, 3 min before Ronaldo’s declaration. Analyzing the time frame of the stock behavior showed that the declaration per se did not affect the performance of the company. ![]() A first example: on 14 June 2021, Cristiano Ronaldo stated “Agua, no Coca” in a press conference this declaration was heavily criticized because that day, Coca-Cola stock dropped by 1.06% compared to the previous closing price. Some documented cases have shown how negative false announcements regarding companies heavily affected their stock prices over a short period of time and how the stock price recovered some of its value when the news was revealed to be fake. The results support the idea of the asymmetric effect that negative sentiment has a greater effect than positive sentiment, and these results were confirmed with the EGARCH model. After comparing the social sentiment indexes’ movements with the daily closing stock price of individual companies using transfer entropy, our estimations confirmed that the intensity of the impact of negative and positive news on the daily stock prices is statistically different, as well as that the intensity with which negative news affects stock prices is greater than that of positive news. ![]() A second algorithm was then used to analyze the contents of the tweets, converting that information into social sentiment indexes and building a time series for each considered company. Methods: The first algorithm was used to web-scrape the social network Twitter to download the top tweets of the 24 largest market-capitalized publicly traded companies in the world during the last decade. The authors of the present study followed an innovative approach based on the utilization of two artificial intelligence algorithms to test that asymmetric response effect. Financial economic research has extensively documented the fact that the impact of the arrival of negative news on stock prices is more intense than that of the arrival of positive news. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |