Person:

Stein, Jeremy

We examine the business model of traditional commercial banks when they compete with shadow banks. While both types of intermediaries create safe "money-like" claims, they go about this in different ways. Traditional banks create money-like claims by holding illiquid fixed-income assets to maturity, and they rely on deposit insurance and costly equity capital to support this strategy. This strategy allows bank depositors to remain "sleepy": they do not have to pay attention to transient fluctuations in the market value of bank assets. In contrast, shadow banks create money-like claims by giving their investors an early exit option requiring the rapid liquidation of assets. Thus, traditional banks have a stable source of funding, while shadow banks are subject to runs and fire-sale losses. In equilibrium, traditional banks have a comparative advantage at holding fixed-income assets that have only modest fundamental risk but are illiquid and have substantial transitory price volatility, whereas shadow banks tend to hold relatively liquid assets.

We study optimal government debt maturity in a model where investors derive monetary services from holding riskless short-term securities. In a setting where the government is the only issuer of such riskless paper, it trades off the monetary premium associated with short-term debt against the refinancing risk implied by the need to roll over its debt more often. We then extend the model to allow private financial intermediaries to compete with the government in the provision of short-term, money-like claims. We argue that if there are negative externalities associated with private money creation, the government should tilt its issuance more towards short maturities. The idea is that the government may have a comparative advantage relative to the private sector in bearing refinancing risk and, hence, should aim to partially crowd out the private sector's use of short-term debt.

Changes in monetary policy have surprisingly strong effects on forward real rates in the distant future. A 100 basis point increase in the two-year nominal yield on a Federal Open Markets Committee announcement day is associated with a 42 basis point increase in the ten-year forward real rate. This finding is at odds with standard macro models based on sticky nominal prices, which imply that monetary policy cannot move real rates over a horizon longer than that over which all prices in the economy can readjust. Instead, the responsiveness of long-term real rates to monetary shocks appears to reflect changes in term premia. One mechanism that could generate such variation in term premia is based on demand effects due to the existence of what we call yield-oriented investors. We find some evidence supportive of this channel.

Introducing more speculators into the market for a given commodity leads to improved risk sharing but can also change the informational content of prices. This inflicts an externality on those traders already in the market, whose ability to make inferences based on current prices will be affected. In some cases, the externality is negative: the entry of new speculators lowers the informativeness of the price to existing traders. The net result can be one of price destabilization and welfare reduction. This is true even when all agents are rational, risk-averse, competitors who make the best possible use of their available information.

We develop a model in which a firm can devote effort either to increasing sales growth, or to improving per-unit profit margins. If the firm's manager cares about the current stock price, she will favor the growth strategy when the market pays more attention to growth numbers. Conversely, it can be rational for the market to weight growth measures more heavily when it is known that the firm is following a growth strategy. This two-way feedback between firms' strategies and the market's pricing rule can lead to excess volatility in real variables, even absent any external shocks.

A large catalog of variables with no apparent connection to risk has been shown to forecast stock returns, both in the time series and the cross-section. For instance, we see medium-term momentum and post-earnings drift in returns—the tendency for stocks that have had unusually high past returns or good earnings news to continue to deliver relatively strong returns over the subsequent six to twelve months (and vice-versa for stocks with low past returns or bad earnings news); we also see longer-run fundamental reversion—the tendency for “glamour” stocks with high ratios of market value to earnings, cashflows, or book value to deliver weak returns over the subsequent several years (and vice-versa for “value” stocks with low ratios of market value to fundamentals). To explain these patterns of predictability in stock returns, we advocate a particular class of heterogeneous-agent models that we call “disagreement models.” Disagreement models may incorporate work on gradual information flow, limited attention, and heterogeneous priors, but all highlight the importance of differences in the beliefs of investors. Disagreement models hold the promise of delivering a comprehensive joint account of stock prices and trading volume—and some of the most interesting empirical patterns in the stock market are linked to volume.

We develop a model that clarifies the respective advantages and disadvantages of academic and private-sector research. Rather than relying on lack of appropriability or spillovers to generate a rationale for academic research, we emphasize control-rights considerations, and argue that the fundamental tradeoff between academia and the private sector is one of creative control versus focus. By serving as a precommitment mechanism that allows scientists to freely pursue their own interests, academia can be indispensable for early-stage research. At the same time, the private sector's ability to direct scientists toward higher-payoff activities makes it more attractive for later-stage research.

This article addresses the following basic capital budgeting problem: suppose that cross-sectional differences in stock returns can be predicted based on variables other than P(e.g., book-to-market) and that this predictability reflects market irrationality rather than compensation for fundamental risk. In this setting, how should companies determine hurdle rates? I show how factors such as managerial time horizons and financial constraints affect the optimal hurdle rate. Under some circumstances, beta can be useful as a capital tool, even budgeting if it is of no use in predicting stock returns.

This paper examines the familiar argument that takeover pressure can be damaging because it leads managers to sacrifice long-term interests in order to boost current profits. If stockholders are imperfectly informed, temporarily low earnings may cause the stock to become undervalued, increasing the likelihood of a takeover at an unfavorable price; hence the managerial concern with current bottom line. The magnitude of the problem depends on a variety of factors, including the attitudes and beliefs o f shareholders, the extent to which corporate raiders have inside information, and the degree to which managers are concerned with retaining control of their firms.

The authors develop a pair of models that illustrate how imperfections in transfunctional mechanisms can lead to a market crash. Neither market orders nor limit orders allow traders to condition their demands on the full information set needed to achieve a Walrasian outcome. When volume shocks are sufficiently large, the deviations from Walrasian prices and allocations are large also. Properly designed and implemented, circuit breakers may help to overcome some of these informational problems and thereby improve the market's ability to absorb large volume shocks.