Knowledge that Transforms

In this article, we characterize economies in which both cash flows and forward prices follow random walks. We show in the case of geometric random walks that the preferences of the representative investor are of the constant proportional risk-aversion type. We also show the conditions under which spot prices follow random walks and under which the equivalent martingale measure is non-state-dependent.

Event studies often include cross-sectional regressions of announcement effects on exogenous variables. If the event is voluntary and investors are rational, then standard OLS and GLS estimators are inconsistent. Consistent ML estimators are constructed for a cross-sectional model of horizontal mergers relating announcement effects to exogenous characteristics of firms and industries. The OLS and ML estimates differ dramatically for bidders but not for targets. The evidence suggests that managers of bidders, but not targets, have valuable private information about the potential synergies from proposed mergers.

Results of tests contrasting tax-loss selling with intertemporal information variation as explanations of the January seasonal in stock returns are reported. Closed-end fund shares display the typical size-related January seasonal while their net asset values do not. Interpreting the net asset value return as a proxy for information about underlying assets, this result indicates information variation is not a necessary condition for the January effect in stocks. The share returns at the turn of the year are negatively related to their mean preceding year returns and positively related to the standard deviations of their preceding year returns. These results are consistent with tax-loss selling.

The stock market crash of October 1987 led to a boom in conferences, commissions, and studies of the stock market. In almost each case, the participants would try to understand the events of October 1987 by a detailed analysis or description of events during the particular days of high volatility. Of course, to us economists there was nothing qualitatively unusual about October 19, 1987; the stock market moved, and we have no model that succeeds in explaining the magnitude or sources of daily stock market volatility for that day or any other day. When asked by the National Bureau of Economic Research to organize yet another conference on this subject, I decided that it was time to put these events in a historical perspective and try to understand them in the context of longer time periods and broader models. The papers collected in this symposium issue admirably succeed in broadening...

This study investigates experimental financial markets in which firms possess more information than do potential investors. Firms were given opportunities to undertake positive net present value projects which they could either forgo or finance by selling equity. Auctions were conducted among the investors for the right to finance the projects. When the theoretical equilibrium was unique, theory predicted well. When theory permitted pooling, separation, and semiseparation, only the more efficient pooling equilibrium was observed. The domination of the pooling equilibrium was robust to different experimental experiences by participants. When available, signals were used by good firms to distinguish themselves from bad.

The downside risk in a leveraged stock position can be eliminated by using stop-loss orders. The upside potential of such a position can be captured using contingent buy orders. The terminal payoff to this stop-loss start-gain strategy is identical to that of a call option, but the strategy costs less initially. This article resolves this paradox by showing that the strategy is not self-financing for continuous stock-price processes of unbounded variation. The resolution of the paradox leads to a new decomposition of an option’s price into its intrinsic and time value. When the stock price follows geometric Brownian motion, this decomposition is proven to be mathematically equivalent to the Black–Scholes (1973) formula.

Examination of 41 closed-end fund intial public offerings (IPOs) during the period from January 1986 to June 1987 reveals that the mean intial day's return is not significantly different from zero in contrast to previous findings for nonfund IPOs. New funds also show significant negative after- market returns unlike other new issues. Despite the disparity between our findings and previous results, our results are consistent with existing models. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.

This article is a reexamination of the clearing and settlement process in financial markets (particularly the futures market) and its performance during the 1987 stock market crash. It provides both some institutional background and some conceptual perspective on the problems faced by the system during the week of October 19. Much of the discussion is based on the useful analogies that can be drawn between the clearinghouse and other financial intermediaries, such as banks and insurance companies. A major conclusion is that the Federal Reserve played a vital role in protecting the integrity of the clearing and settlements system during the crash.

In a model of takeovers under asymmetric information, we identify a separating equilibrium in which the value of the bidder firm is revealed by the mix of cash and securities used as payment for the target. The model predicts that the revealed bidder value is monotonically increasing and convex in the fraction of the total offer that consists of cash. We examine the model restrictions using data from Canada, where mixed offers are both relatively frequent and free of the confounding tax-related options characterizing mixed offers in the United States. We find that the average announcement-month bidder abnormal return in mixed offers is large and significant. However, maximum likelihood estimates of parameters in both linear and nonlinear cross-sectional regressions fail to support the model predictions.