This paper uses a unique dataset from Denmark to investigate the impact of family characteristics in corporate decision making and the consequences of these decisions on firm performance. We focus on the decision to appoint either a family or external chief executive officer (CEO). The paper uses variation in CEO succession decisions that result from the gender of a departing CEO's firstborn child.
This paper lays out a decomposition of book-to-price (B/P) that derives from the accounting for book value and that articulates precisely how B/P "absorbs" leverage. The B/P ratio can be decomposed into an enterprise book-to-price (that pertains to operations and potentially reflects operating risk) and a leverage component (that reflects financing risk).
This paper develops numerical approximations for pricing collateralized debt obligations (CDOs) and other portfolio credit derivatives in the multifactor Normal Copula model. A key aspect of pricing portfolio credit derivatives is capturing dependence between the defaults of the elements of the portfolio. But, compared with an independent-obligor model, pricing in a model with correlated defaults is more challenging. Our approach strikes a balance by reducing the problem of pricing in a model with correlated defaults to calculations involving only independent defaults.
The article shows that two measures of the amount of private information in stock price — price nonsynchronicity and probability of informed trading (PIN) — have a strong positive effect on the sensitivity of corporate investment to stock price. Moreover, the effect is robust to the inclusion of controls for managerial information and for other information-related variables. The results suggest that firm managers learn from the private information in stock price about their own firms’ fundamentals and incorporate this information in the corporate investment decisions.
This paper develops a pure simulation-based approach for computing maximum likelihood estimates in latent state variable models using Markov Chain Monte Carlo methods (MCMC). Our MCMC algorithm simultaneously evaluates and optimizes the likelihood function without resorting to gradient methods. The approach relies on data augmentation, with insights similar to simulated annealing and evolutionary Monte Carlo algorithms. We prove a limit theorem in the degree of data augmentation and use this to provide standard errors and convergence diagnostics.
Contrary to the common perception that operating cash flows are better than accounting earnings at explaining equity valuations, recent studies suggest that valuations derived from industry multiples based on reported earnings are closer to traded prices than those based on reported operating cash flows.
Explicit presence of reorganization in addition to liquidation leads to conflicts of interest between borrowers and lenders. In the first-best outcome, reorganization adds value to both parties via higher debt capacity, lower credit spreads, and improved overall firm value. If control of the ex ante reorganization timing and the ex post decision to liquidate is given to borrowers, most of the benefits are appropriated by borrowers ex post. Lenders can restore the first-best outcome by seizing this control or by the ex post transfer of control rights.
This study offers the first empirical microeconomic analysis of the effectiveness of dollar debt and contract redenomination policies to mitigate adverse financial and relative price consequences from a large devaluation.
While standard real options models assume that agents possess a constant rate of time preference, there is substantial evidence that agents are impatient about choices in the short term but are patient when choosing between long-term alternatives. We extend the real options framework to model the investment-timing decisions of entrepreneurs with time-inconsistent preferences.