Now showing 1 - 3 of 3
  • Publication
    Media-expressed negative tone and firm-level stock returns
    We build a corpus of over 5½ million news articles on 20 large US firms over the 10-year period from January 2001 to December 2010, and use it to study the time-varying nature of the relation between media-expressed firm-specific tone and firm-level returns. By estimating a series of separate rolling window vector autoregressive (VAR) models for each firm, we show how media-expressed negative tone impacts firm-level returns episodically in ways that vary across firms and over time. We find that firms experience prolonged periods during which media-expressed tone has no effect on returns, and occasional episodes when it has a significant impact. During the significant episodes, its impacts are sometimes quickly reversed and at other times they endure — implying that media comment and analysis can sometimes be sentiment (or noise), but it can also contain value-relevant information or news. Our findings are in general consistent with efficiently functioning markets in which the media assists with the processing of complex information.
      802Scopus© Citations 48
  • Publication
    The Impact of Textual Sentiment on Sovereign Bond Yield Spreads: Evidence from the Eurozone Crisis
    (Multinational Finance Society, 2014-09)
    This study examines the relation between textual sentiment (media pessimism), the concentration/volume of news, and sovereign bond yield spreads, specifically in Greece, Ireland, Italy, Portugal and Spain during the European sovereign debt crisis from 2009 to 2012. The findings suggest that higher media pessimism and greater concentration/volume of news collectively communicate additional value-relevant information that has not been quantified by traditional determinants of yield spreads. If higher media pessimism is coupled with greater concentration/volume of news and other factors remain unchanged, yield spreads would move upwards, causing prices to fall. Media pessimism and the number of news stories respectively and collectively help predict the widening of yield spreads. Higher media pessimism level is strongly associated with more news stories being reported, suggesting that “no news is good news.”
  • Publication
    Textual sentiment in finance: A survey of methods and models
    (Elsevier, 2014-05) ;
    We survey the textual sentiment literature, comparing and contrasting the various information sources, content analysis methods, and empirical models that have been used to date. We summarize the important and influential findings about how textual sentiment impacts on individual, firm-level and market-level behavior and performance, and vice versa. We point to what is agreed and what remains controversial. Promising directions for future research are emerging from the availability of more accurate and efficient sentiment measures resulting from increasingly sophisticated textual content analysis coupled with more extensive field-specific dictionaries. This is enabling more wide-ranging studies that use increasingly sophisticated models to help us better understand behavioral finance patterns across individuals, institutions and markets.
      4788Scopus© Citations 251