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We identify all return leader-follower pairs among individual stocks using Granger causality regressions. Thus-identified leaders reliably predict their followers' returns out of sample, and the return predictability works at the level of individual stocks rather than industries. Our results indicate that, independent of its size, any firm may emerge as a return leader by being at the center of an important news development that has ramifications for other firms. Indeed, stocks undergoing news-generating developments see an increase in the number of stocks whose returns they lead.

We document that stocks that experience sudden increases in idiosyncratic volatility underperform otherwise similar stocks in the future, and we propose that this phenomenon can be explained by the Miller conjecture [Miller E (1977) Risk, uncertainty, and divergence of opinion. J. Finance 32(4):1151–1168]. We show that volatility shocks can be traced to unusual firm-level news flow, which temporarily increases the level of investor disagreement about the firm value. At the same time, volatility shocks pose a barrier to short selling, preventing pessimistic investors from expressing their views. In the presence of divergent opinions and short-selling constraints, prices initially reflect optimistic views but adjust downward in the future as investors’ opinions converge. The online appendix is available at https://doi.org/10.1287/mnsc.2017.2726 . This paper was accepted by Wei Xiong, finance.

We classify a unique and comprehensive data set of corporate press releases into topics and study the market reaction to various types of news. While confirming prior findings regarding strong stock price responses to financial news, we also document significant reactions to news about corporate strategy, customers and partners, products and services, management changes, and legal developments. Consistent with regulators' expectations, the level of informational asymmetry in the market declines following most types of press releases. At the same time, return volatility frequently increases in the post-announcement period, which we show can be attributed to higher levels of valuation uncertainty.

∗∗∗ Using new data on market-based transactions we construct real estate price indexes for Manhattan between 1920 and 1939. During the 1920s prices reached their highest level in the third quarter of 1929 before falling by 67% at the end of 1932 and hovering around that value for most of the Great Depression. The value of high-end properties strongly co-moved with the stock market between 1929 and 1932. A typical property bought in 1920 would have retained only 56% of its initial value in nominal terms two decades later. An investment in the stock market index (including dividends) would have outperformed an investment in a typical property (including net rental income) by a factor of 5.2 over our time period. It is often assumed that the Great Depression was associated with both stock market and real estate shocks (e.g., Shiller 2006, Piazzesi, Schneider and Tuzel 2007), especially in light of the recent sub-prime financial crisis where parallels with the past are frequently drawn (Reinhart and Rogoff 2009). Yet empirical evidence on movements in real estate prices is limited for this time period. We construct the first high-frequency real estate quarterly index using transaction prices for Manhattan, a major market in the United States. We use the new data to examine stock market and real estate cycles during one of the most significant crises in U.S. economic and financial history. We show that the real estate market suffered a sudden and severe downturn in 1929, from which it still had not recovered in 1939. Although Manhattan represents a small geographic area, in 1930 it contained approximately 4% of all United States real estate wealth despite having 1.5% of the population. 1 Moreover, Long Jr. (1936) writes that between 1919 and 1933, the total value of building plans for Manhattan was “only slightly less than 10% of the total

Behavioural models offer new insights into why bubbles are ubiquitous in residential real estate markets. These markets are dominated by unsophisticated households who often develop optimistic views by extrapolating from past returns. Rational investors cannot easily trade against an overvaluation of housing assets because of high transaction costs and a binding short sale constraint. Circumventing the effect of the latter, the supply of housing frequently increases in response to rising prices. This helps to mitigate bubbles but often leads to overbuilding, which slows down the recovery after a bubble bursts. Models that incorporate the effects of perverse incentives and limits to arbitrage are especially helpful in explaining the bubble that developed in mortgage-backed securities and helped fuel the recent real estate bubble by relaxing home buyers’ borrowing constraints. The literature is ambiguous about whether governments should intervene to burst bubbles, as a better response may lie in improving incentives of key market players.

We document that stocks that experience sudden increases in idiosyncratic volatility underperform otherwise similar stocks in the future, and we propose that this phenomenon can be explained by the Miller (1977) conjecture. We show that volatility shocks can be traced to the unusual firm-level news flow, which temporarily increases the level of investor disagreement about the firm value. At the same time, volatility shocks pose a barrier to short selling, preventing pessimistic investors from expressing their views. In the presence of divergent opinions and short selling constraints, prices end up initially reflecting optimistic views but adjust down in the future as investors' opinions converge.

Examining returns of stocks with high levels of analyst disagreement about future earnings reveals a close link between mispricing and liquidity. Previous research finds these stocks often to be overpriced, but prices to correct down within a fiscal year as uncertainty about earnings is resolved. We conjecture that one reason mispricing has persisted is that these stocks have higher trading costs than otherwise similar stocks, possibly because some investors are better informed than the market maker about how to aggregate analysts’ opinions. As analyst disagreement increases so does the informational disadvantage of the marker maker, and trading costs rise. In the cross-section, less liquid stocks are, on average, more severely mispriced. Moreover, increases in aggregate market liquidity accelerate convergence of prices to fundamentals. As a result, returns of initially overpriced stocks are negatively correlated with the time series of innovations in aggregate market liquidity.

We provide evidence that stocks with higher dispersion in analysts’ earnings forecasts earn lower future returns than otherwise similar stocks. This effect is most pronounced in small stocks and stocks that have performed poorly over the past year. Interpreting dispersion in analysts’ forecasts as a proxy for differences in opinion about a stock, we show that this evidence is consistent with the hypothesis that prices will ref lect the optimistic view whenever investors with the lowest valuations do not trade. By contrast, our evidence is inconsistent with a view that dispersion in analysts’ forecasts proxies for risk. IN THIS PAPER WE ANALYZE THE ROLE of dispersion in analysts’ earnings forecasts in predicting the cross section of future stock returns. We find that stocks with higher dispersion in analysts’ earnings forecasts earn significantly lower future returns than otherwise similar stocks. In particular, a portfolio of stocks in the highest quintile of dispersion underperforms a portfolio of stocks in the lowest quintile of dispersion by 9.48 percent per year. This effect is strongest in small stocks, and stocks that have performed poorly over the past year. Our results are robust to various risk-adjustment techniques, and are inconsistent with an interpretation of dispersion in analysts’ forecasts as a proxy for risk. We postulate that dispersion in analysts’ earnings forecasts can be viewed as a proxy for differences of opinion among investors. Differences of opinion are typically modeled via dogmatic beliefs or asymmetric information sets, and have been included in numerous models that relax the standard

Why do asset price bubbles continue to appear in various markets? This paper provides an overview of recent literature on bubbles, with significant attention given to behavioral models and rational models with frictions. Unlike the standard rational models, the new literature is able to model the common characteristics of historical bubble episodes and offer insights for how bubbles are initiated and sustained, the reasons they burst, and why arbitrage forces do not routinely step in to squash them. The latest U.S. real estate bubble is described in the context of this literature.

Why do asset price bubbles continue to appear in various markets? What types of events give rise to bubbles and why do arbitrage forces fail to quickly burst them? Do bubbles have real economic consequences and should policy makers do more to prevent them? This paper provides an overview of recent literature on bubbles, with significant attention given to behavioral models and rational models with frictions. The latest U.S. real estate bubble is described in the context of this literature.

Using new data on market-based transactions we construct real estate price indexes for Manhattan between 1920 and 1939. During the 1920s prices reached their highest level in the third quarter of 1929 before falling by 67 percent at the end of 1932 and hovering around that value for most of the Great Depression. The value of high-end properties strongly co-moved with the stock market between 1929 and 1932. A typical property bought in 1920 would have retained only 56 percent of its initial value in nominal terms two decades later. An investment in the stock market index (including dividends) would have outperformed an investment in a typical property (including net rental income), by a factor of 5.2 over our time period.

We show that stocks that experience a sudden increase in idiosyncratic volatility earn abnormally high contemporaneous returns but significantly underperform otherwise similar stocks in the future. Our findings indicate that volatility shocks can be traced to unusual firm-level news. We conjecture that these unusual news events increase the level of investor disagreement about firms’ fundamental values. Because short-selling of highly volatile stocks is costly, prices rise to reflect the more optimistic views but then revert down as investors’ opinions start to converge. The observed patterns of trade order imbalances and changes in investor disagreement lend support for this hypothesis.

I present evidence of inefficient information processing in equity markets by documenting that negative information withheld by securities analysts is incorporated in stock prices with a significant delay. I estimate the extent of the withheld negative information based on the proportion of analysts who stop revising their annual earnings forecasts. This measure predicts negative earnings surprises and negative price reaction around earnings announcements. It could also be used to generate profitable trading strategies. I show that institutions tend to sell their stock holdings as my measure of unreported negative news increases, thus ameliorating the mispricing. Copyright 2008, Oxford University Press.

This study demonstrates that the U.S. equity premium has declined significantly during the last three decades. The study calculates the equity premium using a variation of a formula in the classic Gordon stock valuation model. The calculation includes the bond yield, the stock dividend yield, and the expected dividend growth rate, which in this formulation can change over time. The study calculates the premium for several measures of the aggregate U.S. stock portfolio and several assumptions about bond yields and stock dividends and gets basically the same result. The premium averaged about 7 percentage points during 192670 and only about 0.7 of a percentage point after that. This result is shown to be reasonable by demonstrating the roughly equal returns that investments in stocks and consol bonds of the same duration would have earned between 1982 and 1999, years when the equity premium is estimated to have been zero.

I provide empirical support for Miller's (1977) hypothesis that a stock price will reflect the optimistic view whenever there is disagreement about its value. Using dispersion in analyst earnings forecasts as a proxy for disagreement, I find that high-dispersion stocks earn lower returns than otherwise similar stocks. This effect is more pronounced for small-cap and growth stocks. The subnormal returns are linked to the resolution of uncertainty. I also document that consensus earnings forecasts are more optimistic the higher the dispersion in underlying estimates - consistent with a view that the more pessimistic analysts chose not to issue forecasts.