This paper analyzes the effect of dynamic capital structure adjustments on credit risk. Firms may optimally adjust their leverage in response to stochastic changes in firm value. It is shown that capital structure dynamics lower optimal initial leverage ratios but increase both, fair credit spreads and expected default probabilities for moderate levels of transactions costs. Numerical examples demonstrate that expected default frequencies do not decrease monotonically in the traditional distance to default measure. The magnitude of the effect of capital structure dynamics depends on firm characteristics such as asset volatility, the growth rate, the effective corporate tax rate, debt call features and transactions costs. We find that the underestimation of credit spreads and expected default frequencies is exacerbated when the risk-adjusted drift of the underlying stochastic process is inferred from a model which ignores the opportunity to recapitalize. Finally it is shown that the value-at-risk of corporate bonds increases with the distance to default (DD) both for very low and for very high values of DD whereas it decreases for intermediate values.

We develop a continuous-time model in which a portfolio manager is hired by a management company. On the basis of observed portfolio returns, all agents update their beliefs about the manager’s skills. In response, investors can move capital into or out of the mutual fund, and the management company can fire the manager. Introducing firing rationalizes several empirically documented findings, such as the positive relation between manager tenure and fund size or the increase of portfolio risk before a manager replacement and the following risk decrease. The analysis predicts that the critical performance threshold that triggers firing increases significantly over a manager’s tenure and that management replacements are accompanied by capital inflows when a young manager is replaced but may be accompanied by capital outflows when a manager with a long tenure is fired. Our model yields much lower valuation levels for management companies than simple applications of discounted cash flow (DCF) methods and is thus more consistent with empirical observations.

This paper presents a framework to study how investors’ social concerns affect technology choices. Consequentialist preferences (disutility from aggregate harm) influence outcomes only if investors coordinate, unless internalized harm is independent of an investor’s mass. Non-consequentialist preferences (disutility from stockholdings) affect outcomes regardless of coordination. Both preferences have stronger impact when risk-sharing consequences of technology supply are small (e.g., highly correlated returns), and their effects cannot be inferred from cost-of-capital differences. When harm is stochastic, polluting firms may appear less risky to social investors. Depending on type and strength of social preferences, this can support or hinder the green transition.