We develop a technique to assess the impact of changes in mortgage markets on households, exploiting an implication of the permanent income hypothesis: The higher a household's expected future income, the higher its desired consumption, ceteris paribus. With perfect credit markets, desired consumption matches actual consumption and current spending forecasts future income. Because credit market imperfections mute this effect, the extent to which house spending predicts future income measures the “imperfectness” of mortgage markets. Using micro‐data, we find that since the early 1980s, mortgage markets have become less imperfect in this sense, and securitization has played an important role.

We propose a latent variables approach within a present‐value model to estimate the expected returns and expected dividend growth rates of the aggregate stock market. This approach aggregates information contained in the history of price‐dividend ratios and dividend growth rates to predict future returns and dividend growth rates. We find that returns and dividend growth rates are predictable with values ranging from 8.2% to 8.9% for returns and 13.9% to 31.6% for dividend growth rates. Both expected returns and expected dividend growth rates have a persistent component, but expected returns are more persistent than expected dividend growth rates.

The paper tests whether individuals have value‐relevant information about local stocks (where “local” is defined as being headquartered near where an investor lives). Our methodology uses two types of calendar‐time portfolios—one based on holdings and one based on transactions. Portfolios of local holdings do not generate abnormal performance (alphas are zero). When studying transactions, purchases of local stocks significantly underperform sales of local stocks. The underperformance remains when focusing on stocks with potentially high levels of information asymmetries. We conclude that individuals do not help incorporate information into stock prices. Our conclusions directly contradict existing studies.

Collateral constraints imply that financing and risk management are fundamentally linked. The opportunity cost of engaging in risk management and conserving debt capacity to hedge future financing needs is forgone current investment, and is higher for more productive and less well‐capitalized firms. More constrained firms engage in less risk management and may exhaust their debt capacity and abstain from risk management, consistent with empirical evidence and in contrast to received theory. When cash flows are low, such firms may be unable to seize investment opportunities and be forced to downsize. Consequently, capital may be less productively deployed in downturns.

The monthly volatility of IPO initial returns is substantial, fluctuates dramatically over time, and is considerably larger during “hot” IPO markets. Consistent with IPO theory, the volatility of initial returns is higher for firms that are more difficult to value because of higher information asymmetry. Our findings highlight underwriters’ difficulty in valuing companies characterized by high uncertainty, and raise serious questions about the efficacy of the traditional firm‐commitment IPO process. One implication of our results is that alternate mechanisms, such as auctions, could be beneficial for firms that value price discovery over the auxiliary services provided by underwriters.

Consistent with recent theoretical models where binding capital constraints lead to sudden liquidity dry‐ups, we find that negative market returns decrease stock liquidity, especially during times of tightness in the funding market. The asymmetric effect of changes in aggregate asset values on liquidity and commonality in liquidity cannot be fully explained by changes in demand for liquidity or volatility effects. We document interindustry spillover effects in liquidity, which are likely to arise from capital constraints in the market making sector. We also find economically significant returns to supplying liquidity following periods of large drops in market valuations.

We show that market‐maker balance sheet and income statement variables explain time variation in liquidity, suggesting liquidity‐supplier financing constraints matter. Using 11 years of NYSE specialist inventory positions and trading revenues, we find that aggregate market‐level and specialist firm‐level spreads widen when specialists have large positions or lose money. The effects are nonlinear and most prominent when inventories are big or trading results have been particularly poor. These sensitivities are smaller after specialist firm mergers, consistent with deep pockets easing financing constraints. Finally, compared to low volatility stocks, the liquidity of high volatility stocks is more sensitive to inventories and losses.