We examine interactions between investment and financing decisions in a dynamic model where the firm can alter the mix of debt and equity financing and exercise a randomly arriving and potentially short lived growth option. The firm will typically finance the exercise of the growth option with equity and may wait years before recapitalizing to a higher debt level. The lack of coordination between the timing of investment and debt financing helps explain a number of findings in the empirical literature, including violation of the financing pecking order, debt conservatism, apparent market timing of security issues, and more pronounced underperformance following equity issues than debt issues.

ABSTRACT Staggered boards (SBs) are one of the most potent common entrenchment devices, and their value effects are considerably debated. We study SBs' effects on firm value, managerial behavior, and investor composition using a quasi‐experimental setting: a 1990 law that imposed SBs on all Massachusetts‐incorporated firms. We find that relative to a matched control group of companies, for treated companies the law led to an increase in Tobin's Q, investment in capital expenditures and R&D, patents, and higher‐quality patented innovations, resulting in higher profitability. These effects are concentrated in innovating firms, especially those facing greater Wall Street scrutiny. An increase in institutional and dedicated investors also accompanied the imposition of SBs, facilitating a longer‐term orientation. The evidence suggests that SBs can benefit early‐life‐cycle firms facing high information asymmetries by allowing their managers to focus on long‐term investments and innovations.

We examine the value and efficiency of analyst recommendations through the lens of capital market anomalies. We find that analysts do not fully use the information in anomaly signals when making recommendations. Analysts tend to give more favorable consensus recommendations to stocks classified as overvalued and, more important, these stocks subsequently tend to have particularly negative abnormal returns. Analysts whose recommendations are better aligned with anomaly signals are more skilled and elicit stronger recommendation announcement returns. Our findings suggest that analysts’ biased recommendations could be a source of market friction that impedes the efficient correction of mispricing.

Using a sample of Chinese A-share listed firms from 2007‐2017, we examine the impact of short sales on a firm's financial constraints. We develop three conceptual frameworks, the negative information effect, the undervaluation effect, and the deterrent effect, based on the prevailing theories and conduct an in-depth empirical analysis using the difference-in-differences, propensity score matching, and instrumental variable methods. Our findings suggest that: (1) Short sales generally worsen a firm's financial constraints by reducing its ability of raising cheap and overvalued external capital. (2) A shortable firm's financial constraints deteriorate more seriously in the case of higher credit risk or information asymmetry. (3) When a firm becomes shortable, its negative media coverage increases, external financing cost rises, and the amount of new external financing decreases. (4) The adverse impact of short sales on financial constraints is more pronounced for inefficient state-owned firms and mainly concentrates in the short term. Collectively, these results support the underlying logic of the negative information effect. However, further analysis shows that: (1) The deterrent effect also exists but is much weaker than the negative information effect. (2) The strength of the two effects will “wan and wax” with time or circumstances. Thus, the deterrent effect may outweigh the negative information effect by easing a firm's financial constraints in some cases, such as in the long term after short sales deregulation and when short sales magnitude is low or the managers are more sensitive to the decline of stock price. Our paper provides new insights into the impact of shorts sales on financial constraints, revealing some unique Chinese features compared to the US market and offering valuable lessons to other emerging markets.

Abstract This paper explores implications of weak identification in common ‘long memory’ and recent ‘rough’ approaches to modeling volatility dynamics of financial assets. We unveil an asymptotic near-observational equivalence between a long memory model with weak autoregressive dynamics and a rough model with a near-unit autoregressive root. Standard methods struggle to distinguish them, and conventional asymptotics are invalid. We propose an identification-robust approach to construct confidence sets that reveal the uncertainty and aid inference. Empirical studies based on realized volatility and trading volume often fail to statistically reject either model, thereby providing evidence of their potential coexistence.