Media news reveals soft information about economic linkages between firms that is not immediately incorporated into stock price . In this paper, we propose a novel measure for aggregate market risk based on news network and news tones, namely media connection index (MCI) . We show that the change of MCI predicts a negative return with a higher in-sample and out-of-sample performance than average correlation index in Pollet and Wilson (2010). In addition, our findings are also statistically as well as economically significant even though we control for different economic predictorsused in Goyal and Welch (2008). We also find this measure is capable of predicting cross-sectional stock returns sorted by B/M, size, momentum, industry, investment and profitability. Further analysis shows that the predictability of our measure mainly comes from the negative tones which is consistent with Tetlock (2007) .
Investor attention has long been noticed as an important driving force of stock returns. A large number of papers have been focusing on providing direct or indirect proxies for overall investor attention. However, we believe that additional attention is a more crucial driver than overall attention in affecting stock returns . In this paper, we propose a new class of predictors, media connection indices (MCI) , using news tones of media news that mentions more than one stocks to proxy effects that induced by additional attention, i.e. sentiment spillover, sentiment co-movement and connected news coverage. In general, we show our predictors are powerful and outperform other predictors, such as sentiment indices and economic predictors, in terms of both in-sample and out-of-sample predictability. In-depth analysis show that the predictability of MCI mainly comes from negative news tones which is consistent with \mbox{%DIFAUXCMD Tetlock2008 .
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Media news reveals soft information about economic linkages between firms that is not immediately incorporated into stock price
Investor attention has long been noticed as an important driving force of stock returns. A large number of papers have been focusing on providing direct or indirect proxies for overall investor attention. However, we believe that additional attention is a more crucial driver than overall attention in affecting stock returns
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novel measure for aggregate market risk based on news network and news tones, namely media connection index
new class of predictors, media connection indices
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. We show that the change of MCI predicts a negative return with a higher in-sample and
, using news tones of media news that mentions more than one stocks to proxy effects that induced by additional attention, i.e. sentiment spillover, sentiment co-movement and connected news coverage. In general, we show our predictors are powerful and outperform other predictors, such as sentiment indices and economic predictors, in terms of both in-sample and
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performance than average correlation index in Pollet and Wilson (2010). In addition, our findings are also statistically as well as economically significant even though we control for different economic predictorsused in Goyal and Welch (2008). We also find this measure is capable of predicting cross-sectional stock returns sorted by B/M, size, momentum, industry, investment and profitability. Further analysis shows
predictability. In-depth analysis show
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our measure
MCI
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the negative
negative news
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Tetlock (2007)
\mbox{%DIFAUXCMD Tetlock2008