Knowledge that Transforms

Existing empirical research investigating the size of the equity premium has largely consisted of a series of innovations around a common theme: producing a better estimate of the equity premium by using better data or a better estimation technique. The equity premium estimate that emerges from most of this work matches one moment of the data alone: the mean difference between an estimate of the return to holding equity and a risk-free rate. We instead match multiple moments of U.S. market data, exploiting the joint distribution of the dividend yield, return volatility, and realized excess returns, and find that the equity premium lies within 50 basis points of 3.5%, a range much narrower than was achieved in previous studies. Additionally, statistical tests based on the joint distribution of these moments reveal that only those models of the conditional equity premium that embed time variation, breaks, and/or trends are supported by the data. In order to develop the joint distribution of the dividend yield, return volatility, and excess returns, we need a model of price and return fundamentals. We document that even recently developed analytically tractable models that permit autocorrelated dividend growth rates and discount rates impose restrictions that are rejected by the data. We therefore turn to a wider range of models, requiring numerical solution methods and parameter estimation by the simulated method of moments.

This paper investigates how a firm’s capital structure choice affects the informational efficiency of its security prices in the secondary markets. We identify two new determinants of a firm’s capital structure policy: the liquidity (adverse selection) premium due to investors’ anticipated losses to informed trading, and operating efficiency improvement due to information revelation from the firm’s security prices. We show that the capital structure decision affects traders’ incentives to acquire information and subsequently, the distribution of informed traders across debt and equity claims. When information is less imperative for improving its operating decisions, a firm issues zero or negative debt (i.e., holding excess cash reserves) in order to reduce socially wasteful information acquisition and the liquidity premium associated with it. When information is crucial for a firm’s operating decisions, the optimal debt level is one that achieves maximum information revelation at the lowest possible liquidity cost. Our model can explain why many firms consistently hold no debt. It also provides new implications for financial system design and for the relationship among leverage, liquidity premium, profitability, and the cost of information acquisition.

In a recently published paper, Edmans, García, and Norli (2007) reveal a strong association between results of soccer games and local stock returns. Inspired by their work, we propose a novel approach to exploit this effect on the aggregate international level with the following three unique features: i) The aggregate effect does not depend on the games’ results; hence, the effect is an exploitable predictable effect. ii) The aggregate effect is based on many games; hence, it is very large and highly significant. We find that the average return on the U.S. market over the World Cup’s effect period is – 2.58%, compared to +1.21% for all-days average returns over the same period length. iii) Exploiting the aggregate effect is involved with trading in a single index for a relatively long period.

I test for stock return predictability in the largest and most comprehensive data set analyzed so far, using four common forecasting variables: the dividend-price (DP) and earnings-price (EP) ratios, the short interest rate, and the term spread. The data contain over 20,000 monthly observations from 40 international markets, including 24 developed and 16 emerging economies. In addition, I develop new methods for predictive regressions with panel data. Inference based on the standard fixed effects estimator is shown to suffer from severe size distortions in the typical stock return regression, and an alternative robust estimator is proposed. The empirical results indicate that the short interest rate and the term spread are fairly robust predictors of stock returns in developed markets. In contrast, no strong or consistent evidence of predictability is found when considering the EP and DP ratios as predictors.

We examine the extent to which investment opportunities and/or mispricing motivate equity issuance and contribute to post-issue stock underperformance. We decompose market-to-book ratios into misvaluation and growth option components and find that issuing firms are both overvalued and have greater growth opportunities relative to nonissuers. Firms with greater growth opportunities invest more in capital expenditures and research and development (R&D) after issuance but do not experience lower post-issue stock returns. In contrast, issuing firms with greater mispricing tend to decrease long-term debt and/or increase cash holdings and do earn lower returns. Our findings are consistent with behavioral explanations for post-issue stock price underperformance.

I test whether social influence affects individual investors’ trading and stock returns. In each of the 20 most active stocks in Finland over 9 years, the number of owners in a municipality multiplied by the number of investors who do not own a stock, a measure of the rate of transmission of diseases and rumors through social contact, predicts individual investor trading. I control for known determinants of trade, including daily news, and show that competing explanations for the relation are unlikely. Socially motivated trades predict stock returns, and the effects are not reversed, suggesting that individuals share useful information. Individuals’ susceptibility to social influence has declined during the period, but the opportunities for social influence have increased.

This study develops an econometric model that incorporates features of price dynamics across assets as well as through time. With the dynamic factors extracted via the Kalman filter, we formulate an asset pricing model, termed the dynamic factor pricing model (DFPM). We then conduct asset pricing tests in the in-sample and out-of-sample contexts. Our analyses show that the ex ante factors are a key component in asset pricing and forecasting. By using the ex ante factors, the DFPM improves upon the explanatory and predictive power of other competing models, including unconditional and conditional versions of the Fama and French (1993) 3-factor model. In particular, the DFPM can explain and better forecast the momentum portfolio returns, which are mostly missed by alternative models.

This paper tests whether the persistence of the momentum and reversal effects is the result of idiosyncratic risk limiting arbitrage. Idiosyncratic risk deters arbitrage, regardless of the arbitrageur’s diversification. Reversal is prevalent only in high idiosyncratic risk stocks, suggesting that idiosyncratic risk limits arbitrage in reversal mispricing. This finding is robust to controls for transaction costs, informed trading, and systematic relations between idiosyncratic risk and subsequent returns. Momentum is not related to idiosyncratic risk. Momentum generates a smaller aggregate return than reversal, so the findings along with those in related studies suggest that transaction costs are sufficient to prevent arbitrageurs from eliminating momentum mispricing.

Recent research finds that the stocks that mutual fund managers buy outperform the stocks that they sell (e.g., Chen, Jegadeesh, and Wermers (2000)). We study the nature of this stock-picking ability. We construct measures of trading skill based on how the stocks held and traded by fund managers perform at subsequent corporate earnings announcements. This approach increases the power to detect skilled trading and sheds light on its source. We find that the average fund’s recent buys significantly outperform its recent sells around the next earnings announcement, and that this accounts for a disproportionate fraction of the total abnormal returns to fund trades estimated in prior work. We find that mutual fund trades also forecast earnings surprises. We conclude that mutual fund managers are able to trade profitably in part because they are able to forecast earnings-related fundamentals.

We investigate the empirical relation between corporate governance and stock market liquidity. We find that firms with better corporate governance have narrower spreads, higher market quality index, smaller price impact of trades, and lower probability of information-based trading. In addition, we show that changes in our liquidity measures are significantly related to changes in the governance index over time. These results suggest that firms may alleviate information-based trading and improve stock market liquidity by adopting corporate governance standards that mitigate informational asymmetries. Our results are remarkably robust to alternative model specifications, across exchanges, and to different measures of liquidity.