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Sentiment Analysis, Machine Learning, Leadership Sentiment, Oil Price Plunge
The relationship between prices and leadership mood was examined using the example of crude oil prices and the sentiment of the CEOs of 5 leading oil production companies between 2014 and 2019. The crude oil market was chosen due to recent price fluctuations and upcoming challenges, and for its significant for the global economy.
This study uses an empirical approach based on a mood analysis of the CEO's natural language. 160 speech transcripts were analyzed using a leading aspect-based sentiment analysis machine learning algorithm to obtain sentiment data. The relation between sentiment and oil price was tested using linear regression. The results of this study show in detail that the sentiment correlates positively in times of low prices and negatively in times of high prices. The average threshold price calculated using this method was 63 USD per barrel of West Texas Intermediate (WTI) crude oil in the observed period. This corresponds to analysts who estimated the ideal oil price for 2018 at USD 60 to 70. Finally, the restrictions and prospects are discussed. Findings of this study could aid investors decision making and advance the use of sentiment analysis in economic sciences.