This article shows that introducing derivative assets increases incentives to collect information about asset payoffs. The increase in information collection makes the price of the underlying asset more informative and causes the expected price to increase. Extending the model to a dynamic setting with multiple risky assets, we find the introducing derivative assets for one asset increases the expected prices of positively correlated assets and reduces price reaction to future earnings announcements. These findings are consistent with the bulk of the empirical evidence on the relationship between the introduction of derivative assets and the behavior of asset prices.

Analysis of absence of arbitrage normally ignores payoffs in states to which the agent assigns zero probability. We extend the fundamental theorem of asset pricing to the case of “no empty promises” in which the agent cannot promise arbitrarily large payments in some states. There is a superpositive pricing rule that can assign positive price to claims in zero probability states important to the market as well as assigning positive prices to claims in the states of positive probability. With continuous information arrival, no empty promises can be enforced by shutting down the agent's subsequent investments once wealth hits zero.

This paper examines underwriters' pricing errors and the information content of first‐day trading activity in IPOs. We show that first‐day winners continue to be winners over the first year, and first‐day dogs continue to be relative dogs. Exceptions are “extra‐hot” IPOs, which provide the worst future performance. We also demonstrate that large, supposedly informed, traders “flip” IPOs that perform the worst in the future. IPOs with low flipping generate abnormal returns of 1.5 percentage points per month over the first six months beginning on the third day. We show that flipping is predictable and conclude that underwriters' pricing errors are intentional.

We present a consumption‐based model that explains a wide variety of dynamic asset pricing phenomena, including the procyclical variation of stock prices, the long‐horizon predictability of excess stock returns, and the countercyclical variation of stock market volatility. The model captures much of the history of stock prices from consumption data. It explains the short‐and long‐run equity premium puzzles despite a low and constant risk‐free rate. The results are essentially the same whether we model stocks as a claim to the consumption stream or as a claim to volatile dividends poorly corelated with consumption. The model is driven by an independently and identically distributed consumption growth process and adds a slow ‐moving external habit to the standard power utility function. These features generate slow countercyclical variation in risk premia. The model posits a fundamentally novel description of risk premia. Investors fear stocks primarily because they do poorly in recessions unrelated to the risks of long‐run average consumption growth.

In this comment, it is argued that a balanced-budget rule may cause underinvestment. As a consequence, such a rule is not ex ante efficient: in order to achieve the ex ante optimal outcome, it would be necessary to add an extra rule for the level of public investment. Unfortunately, however, such an investment rule is likely to be very difficult to implement in practice. When there are no rules to prevent underinvestment, it is no longer clear whether a balanced-budget rule is beneficial or not. In some cases, the cost of low levels of investment outweigh the benefits of a balanced budget.