Combining daily personnel records of an unlisted manufacturer with stock market data, we find that market overnight returns negatively predicts same-day worker output. The effect is greater on Mondays and extreme overnights. Analysis suggests that the stock market attracts (discourages) public attention when the overnight returns are extremely positive (negative), consistent with humans’ natural tendency of incorporating good news while discounting bad news. As a result, employees at work are disproportionally distracted by positive overnight returns, leading to reduced output. Additional evidence suggests that our results can hardly be explained with alternative distraction events or workers’ stock wealth concerns. This study reveals a novel channel through which the financial market shapes labor supply.

We propose a behavioral signaling framework to explain the positive announcement effects of stock splits. (Retail) investors view stock splits as good news and are loss averse. Thus, a stock split can boost investors’ expectations of the firm’s growth potential and its stock price, but may also cause disproportionally larger price declines if the firm cannot meet investors’ high expectations. In equilibrium, only managers with favorable information use stock splits to signal. Empirical analyses of stock splits in China find supporting evidence for this explanation: (1) investors become more optimistic after stock splits; (2) higher split ratios are associated with stronger market reactions; (3) splitting firms have better future performance than non-splitting firms; and (4) they experience larger price declines when falling short of investors’ expectations. These findings, along with the unique institutional features of the Chinese market, help differentiate our behavioral explanation from alternative explanations within the rational framework.

We find that the asymmetric volatility phenomenon is reversed in the Shanghai Stock Exchange during bull markets. That is, volatility increases more with good news than with bad news. This evidence is inconsistent with the US markets (Wu 2001, and Bae, Kim and Nelson 2007). Further examination of this phenomenon reveals that the positive impact of good news on volatility is driven by return chasing behaviour of investors in large stocks during bull markets. We also find that volatility increases after stock price declines in bear markets especially for small stocks. This increase in volatility of small stocks after bad news in bear markets is partly driven by liquidity. After controlling for liquidity shifts, there are no significant patterns in the volatility of small stocks during bear markets. We posit that institutional and behavioural factors are the major driving forces of observed volatility patterns in Chinese stock market.

In this paper, the relationship between firm performance’s combinations and differences as well as the timeliness of actual and scheduled third-quarter report disclosures is examined by regressing on data extracted from the semi-annual and the third-quarter reports of Chinese listed companies between 2003 and 2004. After controlling for the possible impact of semi-annual report disclosures, stock exchanges, firm size, ratios of tradable A-shares and B-shares, and so on, the results indicate that managers of listed companies may have the incentive to manipulate information in the actual and scheduled third-quarter report disclosures; the rule of “releasing good news earlier than bad news” is thus not strictly complied with. This paper further indicates that a firm’s performance, its combinations and differences, have a significant impact on the timeliness of disclosures of these two reports. I therefore suggest minimising the probability of information manipulation of listed companies, boosting investor relation management to safeguard the rights of small and medium shareholders, and enhancing the timeliness of information disclosures of Chinese listed companies.