Knowledge that Transforms

Jimmy E. Hilliard, Jorge Reis, Valuation of Commodity Futures and Options Under Stochastic Convenience Yields, Interest Rates, and Jump Diffusions in the Spot, The Journal of Financial and Quantitative Analysis, Vol. 33, No. 1 (Mar., 1998), pp. 61-86

Moshe Arye Milevsky, Steven E. Posner, Asian Options, the Sum of Lognormals, and the Reciprocal Gamma Distribution, The Journal of Financial and Quantitative Analysis, Vol. 33, No. 3 (Sep., 1998), pp. 409-422

Alvaro Almeida, Charles Goodhart, Richard Payne, The Effects of Macroeconomic News on High Frequency Exchange Rate Behavior, The Journal of Financial and Quantitative Analysis, Vol. 33, No. 3 (Sep., 1998), pp. 383-408

Both bond rating agencies and stock analysts evaluate publicly traded companies and com? municate their opinions to investors. Comparing the timeliness of each, we find that Granger causality flows both ways. While most bond downgrades are preceded by declines in actual and forecast earnings, both actual earnings and forecasts of future earnings tend to fall following downgrades. Although part of this post-downgrade forecast revision can be attributed to negative news regarding actual earnings, most appears to be reaction to the downgrade itself. We find little change in actual earnings following upgrades. Analysts, however, tend to increase their forecasts of future earnings.

It has long been market folklore that the best time to buy stocks is when individual investors are bearish, and the best time to sell is when individual investors are bullish. We examine the forecast power of three popular measures of individual investor sentiment: the level of discounts on closed-end funds, the ratio of odd-lot sales to purchases, and net mutual fund redemptions. Using data from 1933 to 1993, we find that fund discounts and net redemptions predict the size premium, the difference between small and large firm returns, but little evidence that the odd-lot ratio predicts returns.

We model the firm's decision to invest in liquid assets when external financing is costly. The optimal amount of liquidity is determined by a tradeoff between the low return earned on liquid assets and the benefit of minimizing the need for costly external financing. The model predicts that the optimal investment in liquidity is increasing in the cost of external financing, the variance of future cash flows, and the return on future investment opportunities, while it is decreasing in the return differential between the firm's physical assets and liquid assets. Empirical tests on a large panel of U.S. industrial firms support the model's predictions.