Global board reforms and the pricing of IPOs

We document that global board reforms are associated with a significant reduction in IPO underpricing. The effect is amplified for IPOs with greater agency problems and mitigated for IPOs certified by reputable intermediaries, IPOs with greater disclosure specificity, and IPOs in countries with better shareholder protection and stringent financial reporting regulations. Furthermore, global board reforms have led to an improvement in the long-Term market performance, proceeds, and subscription level of IPOs, and have enhanced board independence in the issuing firms. Our findings suggest that global board reforms have strengthened board oversight in the issuing firms, leading to less underpriced IPOs

Aggregate earnings and stock market returns: the good, the bad, and the state-dependent

Prior research documents a negative aggregate earnings-returns relation. In contrast, we posit that the sign of the relation varies, depending upon the macroeconomic and financial market conditions that exist in the earnings announcement quarter. We argue that the existing macroeconomic and financial market conditions influence market participants’ frame of reference, which in turn affects whether they interpret aggregate earnings surprises to be informative about the expected inflation component of the discount rate, the market risk premium component of the discount rate, or aggregate future cash flows. Consistent with this, we find that the sign of the aggregate earnings-returns relation changes numerous times across our sample period. We also find that market participants interpret aggregate earnings to be informative about changes in expected inflation (market risk premium) when the sign of the aggregate earnings-returns relation is negative (positive). Finally, we identify macroeconomic and financial market conditions under which the aggregate earnings-returns relation is more (less) likely to be negative (positive)

Media coverage and IPO pricing around the world

We study how media coverage impacts pricing of initial public offerings (IPOs) around the world. Higher media coverage in the pre-IPO period leads to lower IPO initial returns. The effect is mitigated in countries with better financial reporting quality, greater shareholder rights protection, and more stringent media censorship, and for IPOs “certified” by reputable intermediaries, while it is amplified in countries with higher levels of media penetration and media trust. Further, IPOs with higher pre-IPO media coverage have lower ex post price revision volatility. Our findings suggest that higher pre-IPO media coverage reduces information asymmetry among investors, leading to less underpriced IPOs

Terrorist attacks, investor sentiment, and the pricing of initial public offerings

Using terrorist attacks as exogenous shocks to investor sentiment, we study the impact of investor sentiment on initial public offering (IPO) pricing. IPOs listed within the 30-day period following terrorist attacks, on average, experience lower first-day returns. The documented impact of terrorist attacks is magnified when there is greater IPO valuation uncertainty and when the terrorist attacks are more salient to investors, while mitigated for IPOs “certified” by reputable intermediaries. We also show that the affected IPOs, on average, have more pessimistic media tone in the post-attack/pre-listing day period. The affected IPOs also tend to have lower levels of price revisions, subscriptions, primary share revisions, and total proceeds. Collectively, our findings underscore the salience of investor sentiment in shaping IPO outcomes

Hiding Bad News on Fridays? Not Such a Good Idea!

Previous studies reported firms management to release more bad news on Fridays compared to the rest of weekdays, potentially exploiting investors limited attention. In this study we examine whether this strategy was detected by investors. Our key findings are as follows. First, consistent with previous studies, we find that over the last two decades firms consistently reported more bad news on Friday than during the rest of trading days. Second, we report a structural shift in the earnings-return relation with stock returns becoming more sensitive to the Friday negative earnings news compared to similar announcements released during the rest of the week. Finally, we find this structural shift to be particularly pronounced for the firms with high financial visibility. Overall, our findings suggest that investors have learned about the firms management strategy to report bad news on Fridays. As a result, the benefits from following this strategy have disappeared over time

Earnings News and Market Risk: Is the Magnitude of the Post-Earnings Announcement Drift Underestimated?

The post-earnings announcement drift is the tendency of cumulative abnormal re- turns to drift in the direction of earnings surprise for several weeks after the earnings news is released. We show that a standard approach of measuring abnormal returns by using pre-announcement estimates of market risk (betas) causes the magnitude of this phenomenon to be significantly underestimated. Our key findings are as follows. First, we find that stock beta tends to rise (fall) following the release of bad ( good ) earnings news. Second, we find that by not taking into account post-announcement shifts in betas prior studies are likely to underestimate the magnitude of the drift. A 60-days cumulative abnormal returns on hedge portfolio appear to be approximately 1.4% higher when the leverage effect is incorporated in the estimates of market risk. Our results are robust with respect to different model specifications as well as different earnings surprise measures

Dispersion of Beliefs, Stock Prices and the Earnings Surprise Measures-a Generalized Approach

In this paper we address the issue of modelling the relation between the stock prices and accounting earnings in the presence of potential divergence of opinions regarding the earnings data generating process. In our model the market’s earnings expectation is de…ned as the weighted average of both the time-series and analysts’forecasts, with weights being estimated directly from stock returns. No assumptions are made on functional form of the earnings surprise-stock returns relation, which makes our model ‡exible enough to incorporate a variety of models discussed in the previous literature. The model is estimated semiparametrically following Hardle et al. [Annals of Statistics, 1993]. Our key …ndings are as follows. First, we …nd that investors use both the time-series and analysts’forecasts to predict future earnings. Second, the proportion of investors using the time-series (analysts) forecasts is signi…cantly higher (lower) for the stocks with low (high) market capitalization. Third, we …nd that accounting for the dispersion of earnings forecasts leads to a substantial increase in the magnitude of the post-earnings announcement drift.

Modeling the Dynamics of Welfare Caseload : a New Approach

What are the determinants of welfare caseload fluctuations? To address this crucial policy issue most current research uses either cross-sectional or time-series models. In this study we propose a new two-step latent factor approach. First, a latent-factor model is fitted to the data. Next, time-series techniques are applied to study the relation between the latent factor and control macroeconomic and demographic variables. As an application, we study the dynamics of welfare caseload in Israel over the period 1986- 2002. Our major findings are as follows. First, a single latent-factor model accounts for more than 80% of the variance in welfare caseload. Second we find strong evidence that the latent factor and control variables are cointegrated. Third, the cointegration relation has experienced a structural shift during 1994-1995 following new welfare legislations as well as changes in the Israeli labor market. Overall, our findings suggest that both economic and demographic conditions as well as welfare policy regulations play an important role in explaining welfare caseload trends

Trading Volume, Volatility, and the Serial Correlation of Stock Market Returns

In this paper we study the dynamic relationship between trading volume, volatility, and stock returns at international stock markets. We test a number of theoretical models which suggest that the trading volume and volatility can predict future behavior of stock returns. Our analysis uses both semi-nonparametric (Flexible Fourier Form) and parametric techniques. Our findings suggest that the main factor driving the magnitude of the return reversals is stock market volatility and not trading volume. First, apart from a direct effect on expected returns with mixed signs, we find no evidence of the trading volume affecting the serial correlation of stock market returns, as predicted by Campbell et al. (1993) and Wang (1994). Second, the stock market volatility has a negative and statistically significant impact on the serial correlation of the stock market returns, consistent with the “positive feedback” trading model of Sentana and Wadhwani (1992). Third, the lagged trading volume is positively related to the stock market volatility, supporting the “information flow” theory (Clark, 1973). Moreover, we find that taking into account both trading volume and volatility improves the accuracy of the out-of-sample forecasts of the stock market behavior