Date of Award
Doctor of Philosophy (PhD)
This dissertation proposes novel direct measures for both firm-level and market-level investor attention and investor sentiment and provides new empirical evidence on the effects of investor attention and investor sentiment on earnings pricing.
The first essay proposes novel direct measures for both market-level and firm-level attention using user activity data from StockTwits.com. To the best of my knowledge, this is the first direct measure of market-level attention. By measuring market-level and firm-level attention separately, I am be able to not only distinguish between attention allocated on market level and firm level but also detach attention from equilibrium outcomes. I document that both market-level and firm-level attention is lower on non-trading days and days without macro- or micro news announcements. On earnings announcement days, investors are distracted by higher volume of concurrent competing earnings announcements or macro-news announcements. Investors pay less attention to earnings announced on Friday. Firm-level attention is negatively associated with market-level attention, suggesting that investors allocate their limited attention strategically between market-level and firm-level. I find that investors pay more attention to earnings news announced on days with important macro-news announcements, suggesting that firm-level attention is strengthened rather than weakened with concurrent market-level information shocks. I find that investors have more muted initial reactions to earnings announcements if they pay more attention to board market. On the other hand, higher firm-level investor attention and concurrent important macro-news enhances the immediate price reaction to a firm’s earnings surprise and alleviates the post-announcement drift (PEAD). I also find that drift occurs much later than documented in the prior literature.
The second essay develops direct measures for both market-level and firm-level sentiment using sentiment scores data from StockTwits.com. I examine both the impact of sentiment and the joint effect of sentiment and attention on earnings pricing. To the best of my knowledge, this is the first research about the joint effect of sentiment and attention on earnings pricing. I find that good news is actually punished when sentiment is bullish but bad news is punished significantly more when sentiment is bearish. Good news is rewarded the most when sentiment is bearish. The findings suggest that investors do not overreact to good news when sentiment is bullish but overreact to bad news when sentiment is bearish. I document that both firm-level and market-level sentiment are negatively associated with the immediate price reaction to earnings news. For the immediate response, I find that the immediate price reaction to earnings news is weaker when sentiment is bullish. For the drift, I find that the post-announcement drift is stronger following bullish sentiment. Taking into account investor attention, I find that good news is rewarded more with high attention when sentiment is either bullish or bearish, whereas the effect of attention is more pronounced when sentiment is bearish. Bad news is considerably punished with high attention when sentiment is bearish. The immediate price reaction is strengthened with high attention when sentiment is either bullish or bearish, whereas the effect of attention is more pronounced when sentiment is bearish. For the drift, I find that the post-announcement drift is weaker with high attention following bullish sentiment. It is worth noting that good news with bearish sentiment and high attention has both stronger immediate response and post-announcement drift.
"Two Essays on Investor Attention, Investor Sentiment, and Earnings Pricing"
(2019). Doctor of Philosophy (PhD), Dissertation, Finance, Old Dominion University, DOI: 10.25777/3m7s-vc52
Available for download on Wednesday, February 02, 2022