Abstract
Computational semantic analysis was applied for measurements of pessimistic sentiments from business news. Using semantic tree method, the number of pessimistic and optimistic news was estimated for the analysis of the bearish and bullish stock markets. It was found that the number of pessimistic and optimistic macroeconomic news is very sensitive to the sharp changes of the market indices at the extreme market conditions. A new sentiment indicator was constructed for quantitative measurements of the pessimistic investor sentiments. The proposed sentiment indicator is called a Panic Indicator. We found that the Panic Indicator is appropriate for the explanation of the relationship between the negative public information and stock index declines (S&P-TSX), as well as the sharp changes of VIX index. The proposed Panic Indicator would be useful for stock price modeling, the quantified description of the pessimistic opinions, and computational trading algorithms.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
