Panic Indicator for Measurements of Pessimistic Sentiments from Business News

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.

A Public Psychological Pressure Index for Social Networks

“…Millions of people express their opinions on social networks, making it a valuable data source for the analysis of public sentiment, which has led to the emerging fields of opinion mining and sentiment analysis [27]- [30].…”