In bad times, uncertainty is high, so that investors find it more difficult to assess the prospects of the firms they invest in. Learning models suggest that in such times investors should, everything else equal, value informative signals such as analyst forecasts and recommendations more than...

The existing literature measures the contribution of analyst recommendation changes using average stock-price reactions. With such an approach, recommendation changes can have a significant impact even if no recommendation has a visible stock-price impact. Instead, we call a recommendation...

Not all stock recommendation changes are equal. In a sample constructed to minimize the impact of confounding news, relatively few analyst recommendation changes are influential in the sense that they impact investors' beliefs about a firm in a way that could be noticed in that firm's stock...

We bring together three disparate strands of literature to develop a comprehensive empirical framework to examine the efficiency of security analysts' earnings forecasts in Singapore. We focus specifically on how the increased uncertainty and the negative market sentiment during the period of...

Not all stock recommendation changes are equal. In a sample constructed to minimize the impact of confounding news, relatively few analyst recommendation changes are influential in the sense that they impact investors’ beliefs about a firm in a way that could be noticed in that firm’s stock...

"Investors' reaction to stock recommendations is often incomplete so that there is a predictable postrecommendation drift. I investigate investor inattention as a plausible explanation for this drift by using prior turnover as a proxy for attention. I find that low-attention stocks react less to...

We find that lottery tax windfalls finance higher state-government expenditures on supplemental security income that increase consumption, but only during bust periods. Wealth transfers from lottery winners to low income households enable fiscal policy to stabilize consumption during bust periods.

This paper applies the asymmetric autoregressive conditional duration (AACD) model of Bauwens and Giot (2003) to estimate the probability of informed trading (PIN) using irregularly spaced transaction data. We model trade direction (buy versus sell orders) and the duration between trades...

This paper implements the Asymmetric Autoregressive Conditional Duration (AACD) model of Bauwens and Giot (2003) to analyze irregularly spaced transaction data of trade direction, namely buy versus sell orders. We examine the influence of lagged transaction duration, lagged volume and lagged...