We study how sophisticated investors, when faced with shocks to information environment, change their information acquisition and trading behavior, and how these changes in turn affect market efficiency. We find that, after exogenous reductions of analyst coverage due to closures and mergers of brokerage firms, hedge funds scale up information acquisition, trade more aggressively, and earn higher abnormal returns on the affected stocks. The hedge fund participation also mitigates the impairment of market efficiency caused by coverage reductions. Overall, in a causal framework, our findings suggest a substitution effect between sophisticated investors and public information providers in facilitating market efficiency.

Insurance companies often follow highly correlated investment strategies. As major investors in corporate bonds, their investment commonalities subject investors to fire sale risk when regulatory restrictions prompt widespread divestment of a bond following a rating downgrade. Reflective of fire sale risk, the clustering of insurance companies in a bond has significant explanatory power for yield spreads, controlling for liquidity, credit risk, and other factors. The effect of insurer clustering on bond yield spreads is more evident for bonds held to a greater extent by capital-constrained insurance companies, those with ratings closer to National Association of Insurance Commissioners risk categories with larger capital requirements, and during the financial crisis.

We build an asset-pricing model with dynamic strategic competition to explain the strong joint fluctuations in aggregate discount rates, competition intensity, profitability, and asset prices. Product market competition endogenously intensifies as discount rates rise, because firms compete more aggressively for current cash flows by undercutting each other as the value of future cooperation decreases. In industries with a lower turnover rate of market leaders, firms’ profit margins tend to be higher yet more exposed to discount-rate fluctuations, thereby generating the gross profitability premium. We exploit large tariff cuts to identify exogenous variation in market structure to test the core mechanism directly.

This paper proposes a novel quantitative framework with endogenous strategic competition in heterogeneous concentrated industries. Oligopolies compete strategically for profit margins in repeated games, trading off the benefits of future cooperation against those of reaping higher short-run profits by undercutting their rivals. Cross-industry dispersions in market leadership persistence and cash flow loadings on expected growth, as primitive characteristics, simultaneously determine the relationships among profitability, book-to-market ratios, and systematic risk exposures, thereby quantitatively rationalizing the gross profitability and value premium across industries and, importantly, their interactions. Controlling for the book-to-market ratio (gross profitability) makes the gross profitability (value) premium more pronounced.

This study examines whether the availability of traded credit default swaps (CDS) influences the referenced firms' incentive to smooth their performance. We show that with the introduction of CDS trading on their debt, CDS-referenced firms (CDS firms) lower both their earnings and cash flow volatility. Specifically, earnings volatility declines faster than cash flow volatility, which is consistent with income smoothing behavior. The effect of CDS trading on performance smoothing is qualitatively similar under different market and economic conditions. These results support the notion that CDS firms smooth their performance to avoid renegotiation with CDS-protected creditors. We also find that CDS firms smooth their cash flows via hedging with derivatives and smooth their earnings using discretionary accruals after the inception of CDS trading.

In this study, we forecast the realized volatility of the S&P 500 index using the heterogeneous autoregressive model for realized volatility (HAR-RV) and its various extensions. Our models take into account the time-varying property of the models’ parameters and the volatility of realized volatility. A dynamic model averaging (DMA) approach is used to combine the forecasts of the individual models. Our empirical results suggest that DMA can generate more accurate forecasts than individual model in both statistical and economic senses. Models that use time-varying parameters have greater forecasting accuracy than models that use the constant coefficients. The superiority of time-varying parameter models is also found in volatility density forecasting.

We develop a model in which customer capital depends on key talents' contribution and pure brand recognition. Customer capital guarantees stable demand but is fragile to financial constraints risk if retained mainly by talents, who tend to quit financially constrained firms, damaging customer capital. Using a proprietary, granular brand‐perception survey, we construct a firm‐level measure of the inalienability of customer capital (ICC) that captures the degree to which customer capital depends on talents. Firms with higher ICC have higher average returns, higher talent turnover, and more precautionary financial policies. The ICC‐sorted long‐short portfolio's spread comoves with financial constraints factor.