Knowledge that Transforms

This study uses the introduction of second-generation antitakeover legislation as a natural experimental setting to infer the value that managers place on the control rights conferred by stock ownership. We conjecture that managers will reduce their stockholdings in the post-legislation period because they can ensure their prior level of control while holding fewer risky shares. Using a variety of specifications, we find robust evidence consistent with this "revealed preference" hypothesis. Further demonstrating the key role played by control considerations in managers' stockholding decisions, the reductions in ownership are concentrated in management teams with higher levels of initial ownership and in firms without poison pills.

Corporations use a variety of processes to allocate capital. This article studies the benefits and costs of several common budget procedures from the perspective of a model with agency and information problems. Processes that delegate aspects of the decision to the agent result in too many projects being approved, while processes in which the principal retains the right to reject projects cause the agent to strategically distort his information about project quality. We show how the choice of a decision process depends on these two costs, and specifically on severity of the agency problem, quality of information, and project risk.

This article solves a realistically calibrated life cycle model of consumption and portfolio choice with non-tradable labor income and borrowing constraints. Since labor income substitutes for riskless asset holdings, the optimal share invested in equities is roughly decreasing over life. We compute a measure of the importance of human capital for investment behavior. We find that ignoring labor income generates large utility costs, while the cost of ignoring only its risk is an order of magnitude smaller, except when we allow for a disastrous labor income shock. Moreover, we study the implications of introducing endogenous borrowing constraints in this incomplete-markets setting.

This paper examines the optimal consumption and portfolio-choice problem of long-horizon investors who have access to a riskless asset with constant return and a risky asset ("stocks") with constant expected return and time-varying precision–the reciprocal of volatility. Markets are incomplete, and investors have recursive preferences defined over intermediate consumption. The paper obtains a solution to this problem which is exact for investors with unit elasticity of intertemporal substitution of consumption and approximate otherwise. The optimal portfolio demand for stocks includes an intertemporal hedging component that is negative when investors have coefficients of relative risk aversion larger than one, and the instantaneous correlation between volatility and stock returns is negative, as typically estimated from stock return data. Our estimates of the joint process for stock returns and precision (or volatility) using U.S. data confirm this finding. But we also find that stock return volatility does not appear to be variable and persistent enough to generate large intertemporal hedging demands.

We study how heterogeneous beliefs affect returns and examine whether they are a priced factor in traditional asset pricing models. To accomplish this task, we suggest new empirical measures based on the disagreement among analysts about expected earnings (short-term and long-term) and show they are good proxies. We first establish that the heterogeneity of beliefs matters for asset pricing and then turn our attention to estimating a structural model in which we use the forecasts of financial analysts to proxy for agents' beliefs. Finally, we investigate whether the amount of heterogeneity in analysts' forecasts can help explain asset pricing puzzles.

In theory, the sum of squares of log returns sampled at high frequency estimates their variance. When market microstructure noise is present but unaccounted for, however, we show that the optimal sampling frequency is finite and derives its closed-form expression. But even with optimal sampling, using say 5-min returns when transactions are recorded every second, a vast amount of data is discarded, in contradiction to basic statistical principles. We demonstrate that modeling the noise and using all the data is a better solution, even if one misspecifies the noise distribution. So the answer is: sample as often as possible.

We investigate whether domestic investors have an edge over foreign investors in trading domestic stocks. Using Korean data, we show that foreign money managers pay more than domestic money managers when they buy and receive less when they sell for medium and large trades. The sample average daily trade-weighted disadvantage of foreign money managers is 21 basis points for purchases and 16 basis points for sales. There is also some evidence that domestic individual investors have an edge over foreign investors. The explanation for these results is that prices move more against foreign investors than against domestic investors before trades.

I develop a model of information spillovers in initial public offerings (IPOs). The outcomes of pioneers' IPOs reflect participating investors' private information on common valuation factors. This makes the pricing of subsequent issues relatively easier and attracts more firms to the IPO market. I show that IPO market timing by the followers emerges as an equilibrium clustering pattern. High offer price realizations for pioneers' IPOs better reflect investors' private information and trigger a larger number of subsequent IPOs than low offer price realizations do. This asymmetry in the spillover effect is more pronounced early on in a hot market. The model provides an explanation for recent empirical findings that illustrate the high sensitivity of going public decision to IPO market conditions.

We examine the importance of industry to firm-level financial and real decisions. We find that in addition to standard industry fixed effects, financial structure also depends on a firm's position within its industry. In competitive industries, a firm's financial leverage depends on its natural hedge (its proximity to the median industry capital-labor ratio), the actions of other firms in the industry, and its status as entrant, incumbent, or exiting firm. Financial leverage is higher and less dispersed in concentrated industries, where strategic debt interactions are also stronger, but a firm's natural hedge is not significant. Our results show that financial structure, technology, and risk are jointly determined within industries. These findings are consistent with recent industry equilibrium models of financial structure.

This article takes a shrinkage approach to examine the empirical implications of aversion to model uncertainty. The shrinkage approach explicitly shows how predictive distributions incorporate data and prior beliefs. It enables us to solve the optimal portfolios for uncertainty-averse investors. A version to uncertainty about the capital asset pricing model leads investors to hold a portfolio that is not mean-variance efficient for any predictive distribution. However, mean-variance efficient portfolios corresponding to extremely strong beliefs in the Fama-French model are approximately optimal for uncertainty-averse investors. The empirical Bayes approach does not result in optimal portfolios for investors who are averse to model uncertainty.