We examine the impact of financial analysts on the efficiency of firms' investment decisions. We use the accuracy and dispersion of financial analysts' earnings forecasts as proxies of analyst expertise and quality in making forecasts. We find that high quality forecast is associated with higher investment if the firm is more likely to under-invest and lower investment if the firm is more likely to over-invest, suggesting that forecast quality increases firm-level investment efficiency. We further show that such effects are stronger for the firms with higher information asymmetry and lower institutional stock ownership. The results are consistent with the notion that higher quality of analyst forecasts increases the information environment and external monitoring, which in turn increases investment efficiency.

Agency theory suggests that outside shareholders prefer higher dividend payouts in order to reduce the free cash flows of firms that are under the insiders’ control. Our study investigates the effects of mutual funds, typically the most important and influential type of outside shareholder, on firms’ dividend payouts in China during the period from 2003 to 2011. We find that mutual funds influence firms to pay higher cash dividends. The results are consistent with the predictions from exit theory. The effects are more pronounced in firms controlled by state and regional governments and in firms with relatively higher free cash flows. We also find evidence that the mutual funds’ effects are stronger when their investment horizon is longer and the ownership interest is larger. Other institutional investors, such as banks, insurance companies, and securities companies have a lower exit threat and do not have an influence on firms’ cash dividend payments or financial performances.

We measure the volatility information content of stock options for individual firms using option prices for 149 US firms and the S&P 100 index. We use ARCH and regression models to compare volatility forecasts defined by historical stock returns, at-the-money implied volatilities and model-free volatility expectations for every firm. For 1-day-ahead estimation, a historical ARCH model outperforms both of the volatility estimates extracted from option prices for 36% of the firms, but the option forecasts are nearly always more informative for those firms that have the more actively traded options. When the prediction horizon extends until the expiry date of the options, the option forecasts are more informative than the historical volatility for 85% of the firms. However, at-the-money implied volatilities generally outperform the model-free volatility expectations.