Knowledge that Transforms

This paper reexamines, at a range of investment horizons, the asymmetric dependence between hedge fund returns and market returns. Given the current availability of hedge fund data, the joint distribution of longer-horizon returns is extracted from the dynamics of monthly returns using the filtered historical simulation; we then apply the method based on copula theory to uncover the dependence structure therein. While the direction of asymmetry remains unchanged, the magnitude of asymmetry is attenuated considerably as the investment horizon increases. Similar horizon effects also occur on the tail dependence. Our findings suggest that nonlinearity in hedge fund exposure to market risk is more short term in nature, and that hedge funds provide higher benefits of diversification, the longer the horizon.

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.

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.

This paper argues that, contrary to the conventional wisdom, stock return synchronicity (or R 2 ) can increase when transparency improves. In a simple model, we show that, in more transparent environments, stock prices should be more informative about future events. Consequently, when the events actually happen in the future, there should be less “surprise” (i.e., less new information is impounded into the stock price). Thus a more informative stock price today means higher return synchronicity in the future. We find empirical support for our theoretical predictions in 3 settings: namely, firm age, seasoned equity offerings (SEOs), and listing of American Depositary Receipts (ADRs).

Motivated by the effect on valuation of stopped or reduced debt coupon payments from a company in financial distress, we value a level-dependent annuity contract where the annuity rate depends on the value of an underlying asset process. The range of possible values of this asset is divided into a finite number of regions, with constant annuity rates within each region. We present closed-form formulas for the market value of level-dependent annuities contracts when the market value of the underlying asset is assumed to follow a geometric Brownian motion. Such annuities occur naturally in models of debt with credit risk in financial economics. Our results are applied for valuing both corporate debt with suspended interest payments under the U.S. Chapter 11 provisions and loans with contractual level-dependent interest rates.

Disagreement, a key factor inducing trading, has been receiving ever increasing attention in recent years. Most research has focused on disagreement about the expected returns. Several authors have shown that if the average belief coincides with the true expected return, in the portfolio context prices are unaffected by disagreement. In this paper we study the pricing effects of disagreement about return variances. We show that i) disagreement about variances has systematic and significant pricing effects—more disagreement leads to higher prices, and ii) prices are very sensitive to the degree of disagreement: Even if the average belief about the variance is constant, tiny fluctuations in the disagreement about the variance lead to substantial price fluctuations. This second result may offer an explanation for the excess volatility puzzle: When small changes in the degree of disagreement occur, they induce relatively large price changes. Yet, the changes in disagreement may be hard to directly detect empirically, leading to apparent “excess volatility.”

We integrate appealing features of Markowitz’s mean-variance portfolio theory (MVT) and Shefrin and Statman’s behavioral portfolio theory (BPT) into a new mental accounting (MA) framework. Features of the MA framework include an MA structure of portfolios, a definition of risk as the probability of failing to reach the threshold level in each mental account, and attitudes toward risk that vary by account. We demonstrate a mathematical equivalence between MVT, MA, and risk management using value at risk (VaR). The aggregate allocation across MA subportfolios is mean-variance efficient with short selling. Short-selling constraints on mental accounts impose very minor reductions in certainty equivalents, only if binding for the aggregate portfolio, offsetting utility losses from errors in specifying risk-aversion coefficients in MVT applications. These generalizations of MVT and BPT via a unified MA framework result in a fruitful connection between investor consumption goals and portfolio production.