Browsing by Author "Chang Y"

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    Mood and analyst optimism and accuracy (Auckland, December 2016)
    (2016-12) Chang Y; Hsu W
    Does mood affect prediction performance? When analysts are in a positive (negative) mood, do they make more positively (negatively) biased and less (more) accurate forecasts? This study provides supportive evidence. Specifically, we find that analyst forecasts are more optimistic and have larger errors near holidays, but more pessimistic and have smaller errors when there is a disaster with significant fatalities. We further show that these results are neither driven by sentiment associated with contemporaneous economic or market conditions, nor by under-reaction or over-reaction to more bad news released on days immediately before weekends or holidays.
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    Mood and analyst optimism and accuracy (Bangkok, June 2016)
    Chang Y; Hsu W
    We find that analyst forecasts are more optimistic and have larger errors near holidays, but more pessimistic and have smaller errors when there is a disaster with significant fatalities. These results are neither explained by sentiment associated with contemporaneous economic conditions, nor by under-reaction or over-reaction to more bad news released on days immediately before weekends or holidays. Overall, our results are consistent with the notion that when analysts are in a positive (negative) mood, they generally make more positively (negatively) biased and less (more) accurate forecasts.
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    Mood and analyst optimism and accuracy (Sydney, July 2016)
    Chang Y; Hsu W
    We find that analyst forecasts are more optimistic and have larger errors near holidays, but more pessimistic and have smaller errors when there is a disaster with significant fatalities. These results are neither explained by sentiment associated with contemporaneous economic conditions, nor by under-reaction or over-reaction to more bad news released on days immediately before weekends or holidays. Overall, our results are consistent with the notion that when analysts are in a positive (negative) mood, they generally make more positively (negatively) biased and less (more) accurate forecasts.