How The Market Can Detect Its Own Mispricing - A Sentiment Index To Detect Irrational Exuberance

Abstract

The emergence of big data analytics enables real \ time news analysis. Such analysis offers the possibility to instantly \ extract the sentiment conveyed by any newly published, \ textual information source. This paper investigates the existence \ of a causal relationship between news sentiment and stock \ prices. As such, we apply news sentiment analysis for unstructured, \ textual data to extract sentiment scores and utilize \ the Granger-causality test to determine the causal relationship \ between daily news sentiment scores and the corresponding \ stock market returns. Upon successfully identifying such a \ causal relationship with a time lag, we develop a real-time \ news sentiment index. This news sentiment index serves as \ a decision-support system in detecting a potential over- or \ undervaluation of stock prices given the news sentiment of \ available news sources. Thus, as a novelty, the news sentiment \ index serves as an early-warning system to detect irrational \ exuberance.