Climate finance is the study of local and global financing of public and private investment that seeks to support mitigation of and adaptation to climate change. In 2017, the Review of Financial Studies launched a competition among scholars to develop research proposals on the topic with the goal of publishing this special volume. We describe the competition, how the nine projects featured in this volume came to be published, and frame their findings within what we view as a broader climate finance research program.

Credit ratings of corporations are biased, but the forces driving this bias are unclear. We argue it would be difficult for rating agencies to issue high grades for a firm’s debt when there are a lot of objective equity analyst reports about the firm’s earnings that are informative about its default. We find that an exogenous drop in analyst coverage leads to greater optimism-bias in ratings, especially for firms with little bond analyst coverage and those that are close to default. This coverage-induced shock leads to less informative ratings about future defaults and downgrades and more subsequent bond security mispricings. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

We document that banks that cut lending more during the Great Recession were lending to riskier firms ex-ante. To understand the aggregate implications of this sorting pattern, we build an assignment model in which banks have heterogeneous costs to take on risky loans and firms have different credit risks. In the model, aggregate loan volume depends on the entire distribution of bank holding costs and firm credit risks. We then use our model to recover the change in the distribution of bank holding costs during the Great Recession and show that it explains two-thirds of the decline of aggregate loan volume during this period.

We develop a model of asset price bubbles based on the communication process between advisors and investors. Advisors are well-intentioned and want to maximize the welfare of their advisees (like a parent treats a child). But only some advisors understand the new technology (the tech-savvies); others do not and can only make a downward-biased recommendation (the old-fogies). While smart investors recognize the heterogeneity in advisors, naive ones mistakenly take whatever is said at face value. Tech-savvies inflate their forecasts to signal that they are not old-fogies, since more accurate information about their type improves the welfare of investors in the future. A bubble arises for a wide range of parameters, and its size is maximized when there is a mix of smart and naive investors in the economy. Our model suggests an alternative source for stock over-valuation in addition to investor overreaction to news and sell-side bias.

Various theories have been proposed to explain momentum in stock returns. We test the gradual‐information‐diffusion model of Hong and Stein (1999) and establish three key results. First, once one moves past the very smallest stocks, the profitability of momentum strategies declines sharply with firm size. Second, holding size fixed, momentum strategies work better among stocks with low analyst coverage. Finally, the effect of analyst coverage is greater for stocks that are past losers than for past winners. These findings are consistent with the hypothesis that firm‐specific information, especially negative information, diffuses only gradually across the investing public.

The liquidity premium theory of interest rates predicts that the Treasury yield curve steepens with inflation uncertainty as investors demand larger risk premiums to hold long-term bonds. By using the dispersion of inflation forecasts to measure this uncertainty, we find the opposite. Since the prices of long-term bonds move more with inflation than short-term ones, investors also disagree and speculate more about long-maturity payoffs with greater uncertainty. Shorting frictions, measured by using Treasury lending fees, then lead long maturities to become overpriced and the yield curve to flatten. We estimate this inflation-betting effect using time variation in inflation disagreement and Treasury supply. Received September 3, 2014; editorial decision August 5, 2016 by Editor Andrew Karolyi

We develop a speculation-based theory of home improvements. Housing services are produced from a mix of land and structures. Homeowners optimistic about future prices for these services speculate by making improvements, which we model as them increasing their structures holding fixed their land. The recoup value (the difference between the resale value of improvements and construction costs) is simultaneously increasing in home price appreciation and falls with construction cost growth. This prediction stands in contrast to a consumption-cum-financial constraints motive in which rising home prices loosen financial constraints and lead to lower recoup values. We provide evidence consistent with a speculative motive using data on the costs and recoup values of remodeling projects across US cities.

We develop a stock market model with differences of opinion and short-sales constraints. When breadth is low—i.e., when few investors have long positions—this signals that the short-sales constraint is binding tightly, and that prices are high relative to fundamentals. Thus reductions in breadth should forecast lower returns. Using data on mutual fund holdings, we find that stocks whose change in breadth in the prior quarter is in the lowest decile of the sample underperform those in the top decile by 6.38% in the twelve months after formation. Adjusting for size, book-to-market, and momentum, the figure is 4.95%.

We develop a series of cross-sectional regression specifications to forecast skewness in the daily returns of individual stocks. Negative skewness is most pronounced in stocks that have experienced (1) an increase in trading volume relative to trend over the prior six months, consistent with the model of Hong and Stein (NBER Working Paper, 1999), and (2) positive returns over the prior 36 months, which fits with a number of theories, most notably Blanchard and Watson's (Crises in Economic and Financial Structure. Lexington Books, Lexington, MA, 1982, pp. 295–315) rendition of stock-price bubbles. Analogous results also obtain when we attempt to forecast the skewness of the aggregate stock market, though our statistical power in this case is limited.

The Russell 1000 and 2000 stock indexes comprise the first 1000 and next 2000 largest firms ranked by market capitalization. Small changes in the capitalizations of firms ranked near 1000 move them between these indexes. Because the indexes are value-weighted, more money tracks the largest stocks in the Russell 2000 than the smallest in the Russell 1000. Using this discontinuity, we find that additions to the Russell 2000 result in price increases and deletions result in price declines. We then identify time trends in indexing effects and the types of funds that provide liquidity to indexers.