Narrow Results

This paper applies a conditional jump model that was proposed by Chan and Maheu (2002) to examine the stock market dynamics of Mexico, Indonesia, South Korea, and Turkey (MIST). We find that the conditional jump intensity parameter estimates are statistically significant and change dramatically between two sample periods. We show that a high probability of jumps today predicts a high probability of jumps in the next period. The impact of a previous shock to the next period's jump intensity is found to be higher in Turkey compared to other MIST countries. Contrary to the previous literature, we discover that after a stock market crash, it is more likely to see a negative jump (drop) again in the stock exchanges of Mexico and Indonesia. Only in Turkey, it is more likely to see a positive jump after market crashes.

This paper examines autocorrelation and cross-autocorrelation patterns for selected Asian stock returns. Special attention is given to examination of Asian stock returns and the impact on them of the past information. By employing a class of asymmetric specification of conditional mean and conditional variance models, we find the autocorrelation coefficient to be negative for the Japanese market and positive for the rest of the Asian markets studied. Our findings suggest that the Asian markets respond sensitively to the US market, especially on the down side. The asymmetric effects are found to be present in both mean and variance equations. The evidence is consistent with behavior in which investors in Asian markets tend to react more significantly to negative stock news originating from US sources than they do to positive news.

This study examines whether negative book equity (BE) firms are in financial distress by analyzing their operating performance, financial characteristics, distress risk, and survivability when they first report negative BE. Firms with small magnitude of negative BE (SNBE firms) suffer from persistent negative earnings and financial distress, while firms with large magnitude of negative BE (LNBE firms) experience a temporary non-distress related earnings shock. LNBE firms report consecutive years of negative BE, but have lower distress risk and failure rate than both SNBE and control firms. However, all negative BE stocks have abysmal returns subsequent to their first report of negative BE.

In deciding how much customer information to disclose, managers face a tradeoff between the benefits of reducing information asymmetry and the losses of revealing proprietary information. This paper investigates which factors affect the level of ambiguous customer identity disclosure and whether such ambiguous disclosure affects the cost of equity capital. The empirical evidence shows that the proprietary cost is a crucial factor in ambiguous customer identity disclosure. Firms with a higher level of ambiguous customer identity disclosure generate a higher cost of equity capital. Moreover, the higher cost of equity capital is concentrated among firms under imperfect market competition.

This paper aims at discussing the applicability of the three-factor model in China’s multiple security markets. The monthly returns of Shenzhen Main Board Market, Shanghai Stock Market, GEM Securities Market and Small and Medium Board Securities Market from January 2012 to December 2016 are selected as samples. The following conclusions are drawn: the three-factor model is applicable in Shenzhen Main Board Market, that is, the change of stock return is proportional to market factor, book-to-market ratio factor, and inversely proportional to scale factor. Moreover, in terms of the explanatory power of the change of stock return, the market factor is the highest, the scale factor is the second, and the book-to-market ratio factor is the lowest. But in the other three markets, the two-factors model that excludes the ratio of book market value can explain the change of stock return better. In addition, the explanatory power of market factor is better than scale factor.

Using an international dataset of 5,861 firm-year observations between 2009 and 2016 obtained from the Carbon Disclosure Project (CDP), we analyze the effect of firms’ Greenhouse Gas (GHG) emissions on stock price performance. To this end, we first discuss former research which finds an equity discount entailed by high levels of GHG emissions. We then focus on additional metrics of stock price performance, namely stock price return and stock price risk. Interestingly, we do not find any significant impact of GHG emissions on these metrics. A possible explanation is that investors are not yet able to quantify the GHG emission risk due to insufficient disclosure.