Return Seasonalities

A strategy that selects stocks based on their historical same‐calendar‐month returns earns an average return of 13% per year. We document similar return seasonalities in anomalies, commodities, and international stock market indices, as well as at the daily frequency. The seasonalities overwhelm unconditional differences in expected returns. The correlations between different seasonality strategies are modest, suggesting that they emanate from different systematic factors. Our results suggest that seasonalities are not a distinct class of anomalies that requires an explanation of its own, but rather that they are intertwined with other return anomalies through shared systematic factors.     

Long‐Term Return Reversals: Overreaction or Taxes?

Long‐term reversals in U.S. stock returns are better explained as the rational reactions of investors to locked‐in capital gains than an irrational overreaction to news. Predictors of returns based on the overreaction hypothesis have no power, while those that measure locked‐in capital gains do, completely subsuming past returns measures that are traditionally used to predict long‐term returns. In data from Hong Kong, where investment income is not taxed, reversals are nonexistent, and returns are not forecastable either by traditional measures or by measures based on the capital gains lock‐in hypothesis that successfully predict U.S. returns.     

Rare disaster risk and the expected equity risk premium

Consistent with the predictions of rare disaster models, we find that a proxy for the time‐varying probability of rare disasters helps to explain fluctuations in expectations of the equity risk premium. Our proxy for disaster risk is a recently developed measure of global political instability, and the expected market risk premium is from Value Line analysts' expected stock returns. Consistent with long‐run risk models, uncertainty about expected GDP growth and expected consumption growth is also significantly positively related to the expected market risk premium. We obtain similar results when we use the earnings–price ratio and the dividend–price ratio as proxies for the expected market risk premium.     

Average Returns,B/M,and Share Issues

The book‐to‐market ratio (B/M) is a noisy measure of expected stock returns because it also varies with expected cashflows. Our hypothesis is that the evolution of B/M, in terms of past changes in book equity and price, contains independent information about expected cashflows that can be used to improve estimates of expected returns. The tests support this hypothesis, with results that are largely but not entirely similar for Microcap stocks (below the 20^th NYSE market capitalization percentile) and All but Micro stocks (ABM).     

Evidence on the Trade-Off between Risk and Return for IPO and SEO Firms

Do the low long‐run average returns of equity issuers reflect underperformance due to mispricing or the risk characteristics of the issuing firms? We shed new light on this question by examining how institutional lenders price loans of equity issuing firms. Accounting for standard risk factors, we find that equity issuing firms' expected debt return is equivalent to the expected debt return of nonissuing firms, implying that institutional lenders perceive equity issuers to be as risky as similar nonissuing firms. In general, institutional lenders perceive small and high book‐to‐market borrowers as systematically riskier than larger borrowers with low book‐to‐market ratios, consistent with the asset pricing approach in Fama and French (1993) . Finally, we find that firms' expected debt returns decline after equity offerings, consistent with recent theoretical arguments suggesting that firm risk should decline following an equity offering. Overall, our analysis provides novel evidence consistent with risk‐based explanations for the observed equity returns following IPOs and SEOs.     

Infrequent Rebalancing,Return Autocorrelation,and Seasonality

A model of infrequent rebalancing can explain specific predictability patterns in the time series and cross‐section of stock returns. First, infrequent rebalancing produces return autocorrelations that are consistent with empirical evidence from intraday returns and new evidence from daily returns. Autocorrelations can switch sign and become positive at the rebalancing horizon. Second, the cross‐sectional variance in expected returns is larger when more traders rebalance. This effect generates seasonality in the cross‐section of stock returns, which can help explain available empirical evidence.     

Understanding Stock Price Volatility: The Role of Earnings

In an efficient capital market, asset prices vary when investors change their expectations about cash flows, discount rates, or both. Using dividends to measure cash flows, previous research shows that the aggregate dividend‐price ratio varies due to changes in expected discount rates (returns) rather than expected cash flows. In contrast, using accounting earnings instead of dividends as a measure of cash flows, this paper shows that as much as 70% of the variation in the dividend‐price ratio can be explained by changes in expected earnings. Moreover, the paper documents a significant negative correlation between expected returns and expected earnings, suggesting that variations in a common factor to both may generate significant price volatility. The results are consistent with the dividend‐policy irrelevance hypothesis.     

Income Hedging,Dynamic Style Preferences,and Return Predictability

We propose a theoretical measure of income hedging demand and show that it affects asset prices. We focus on the value factor and first demonstrate that our demand estimates are correlated with the actual demands of retail and mutual fund investors. We then show that the aggregate high‐minus‐low (HML) demand predicts HML returns. Exploiting the state‐level variation in income risk, we demonstrate that state‐level hedging demands predict state‐level HML returns. A long‐short portfolio that exploits this hedging‐induced predictability earns an annualized risk‐adjusted return of 6%.     

A novel downside beta and expected stock returns

A number of studies have found that the cross-section of stock returns reflects a risk premium for bearing downside beta; however, existing measures of downside beta have poor power for predicting returns. This paper proposes a novel measure of downside beta, the ES-implied beta, to improve the prediction of the cross-section of asset returns. The ES-implied beta explains stock returns over the same period as well as the widely used downside beta, but improves the prediction for future returns due to its high persistence. In the empirical analysis, the widely used downside beta shows a weak relation with future expected returns, but the ES-implied beta implies a statistically and economically significant risk premium of 0.6% per month and explains 0.6% of the variation in the cross-sectional returns. The effect cannot be explained by traditional cross-sectional effects and is different from the CAPM beta, the downside beta in Ang et al. (2006), coskewness, and cokurtosis.     

Implied volatility skews and stock return skewness and kurtosis implied by stock option prices

The Black-Scholes* option pricing model is commonly applied to value a wide range of option contracts. However, the model often inconsistently prices deep in-the-money and deep out-of-the-money options. Options professionals refer to this well-known phenomenon as a volatility ‘skew’ or ‘smile’. In this paper, we examine an extension of the Black-Scholes model developed by Corrado and Su that suggests skewness and kurtosis in the option-implied distributions of stock returns as the source of volatility skews. Adapting their methodology, we estimate option-implied coefficients of skewness and kurtosis for four actively traded stock options. We find significantly nonnormal skewness and kurtosis in the option-implied distributions of stock returns.     

ESTIMATING EXPECTED EXCESS RETURNS USING HISTORICAL AND OPTION‐IMPLIED VOLATILITY

We test the relation between expected and realized excess returns for the S&P 500 index from January 1994 through December 2003 using the proportional reward‐to‐risk measure to estimate expected returns. When risk is measured by historical volatility, we find no relation between expected and realized excess returns. In contrast, when risk is measured by option‐implied volatility, we find a positive and significant relation between expected and realized excess returns in the 1994–1998 subperiod. In the 1999–2003 subperiod, the option‐implied volatility risk measure yields a positive, but statistically insignificant, risk‐return relation. We attribute this performance difference to the fact that, in the 1994–1998 subperiod, return volatility was lower and the average return was much higher than in the 1999–2003 subperiod, thereby increasing the signal‐to‐noise ratio in the latter subperiod.     

A Model of Return Volatility with Application to Estimating Relative Risk Aversion

We estimate a monthly return volatility model that allows for the abrupt changes in volatility often observed in returns data. Using this model we are able to identify key months likely to correspond to draws from a high volatility regime. Using our model in conjunction with Merton's (1980) model relating expected risk premia to risk we obtain reasonable estimates of the coefficient of relative risk aversion.     

Volatility as an Asset Class: European Evidence

Abstract

Volatility movements are known to be negatively correlated with stock index returns. Hence, investing in volatility appears to be attractive for investors seeking risk diversification. The most common instruments for investing in pure volatility are variance swaps, which now enjoy an active over-the-counter (OTC) market. This paper investigates the risk-return tradeoff of variance swaps on the Deutscher Aktienindex and Euro STOXX 50 index over the time period from 1995 to 2004. We synthetically derive variance swap rates from the smile in option prices. Using quotes from two large investment banks over two months, we validate that the synthetic values are close to OTC market prices. We find that variance swap returns exhibit an option-like profile compared to returns of the underlying index. Given this pattern, it is crucial to account for the non-normality of returns in measuring the performance of variance swap investments. As in the US, the average returns of selling variance swaps are found to be strongly positive and too large to be compatible with standard equilibrium models. The magnitude of the estimated risk premium is related to variance uncertainty and past index returns. This indicates that the variance swap rate does not seem to incorporate all past information relevant for forecasting future realized variance.     

Institutional Ownership and Return Reversals Following Short‐Term Return Consistency

Securities with consistently strong positive (negative) returns during the previous two weeks have future returns that are higher (lower) than those that do not. The results hold for various robustness checks, including those involving firm size, share turnover, past return levels, and bid‐ask bounce. The returns to short horizon consistency trading strategies are reliable through time and are both economically and statistically significant. There is also some evidence that longer periods of consistency lead to greater risk‐adjusted profits. Most surprising is that this effect holds only for those firms with high institutional ownership.     

Do Sovereign Re‐Ratings Destabilize Equity Markets during Financial Crises? New Evidence from Higher Return Moments

This study investigates the effects of S&P's sovereign re‐ratings on the higher moments of equity market returns over recent financial crises. Using a set of intraday stock market index prices and sovereign credit ratings for a sample of 36 countries that experienced sovereign rating changes over the period from 1996 to 2013, we find that the higher moments of stock market returns are significantly more responsive to sovereign re‐ratings during financial crises, but the effects on stock markets are not the same across different financial crises. The effects during crises are, however, magnified for large downgrades and those that are associated with a loss of investment grade status. We find that there are asymmetric effects during financial crises in that downgrades are consistently more significant than upgrades in increasing realized volatility and realized kurtosis. Both upgrades and downgrades affect realized skewness in times of crises in the expected direction.     

Value-Enhancing Capital Budgeting and Firm-specific Stock Return Variation

We document a robust cross‐sectional positive association across industries between a measure of the economic efficiency of corporate investment and the magnitude of firm‐specific variation in stock returns. This finding is interesting for two reasons, neither of which is a priori obvious. First, it adds further support to the view that firm‐specific return variation gauges the extent to which information about the firm is quickly and accurately reflected in share prices. Second, it can be interpreted as evidence that more informative stock prices facilitate more efficient corporate investment.     

Explaining the Magnitude of Liquidity Premia: The Roles of Return Predictability,Wealth Shocks,and State‐Dependent Transaction Costs

Constantinides (1986) documents how the impact of transaction costs on per‐annum liquidity premia in the standard dynamic allocation problem with i.i.d. returns is an order of magnitude smaller than the cost rate itself. Recent papers form portfolios sorted on liquidity measures and find spreads in expected per‐annum return that are the same order of magnitude as the transaction cost spread. When we allow returns to be predictable and introduce wealth shocks calibrated to labor income, transaction costs are able to produce per‐annum liquidity premia that are the same order of magnitude as the transaction cost spread.     

Labor‐Technology Substitution: Implications for Asset Pricing

This paper studies the asset pricing implications of a firm's opportunities to replace routine‐task labor with automation. I develop a model in which firms optimally undertake such replacement when their productivity is low. Hence, firms with routine‐task labor maintain a replacement option that hedges their value against unfavorable macroeconomic shocks and lowers their expected returns. Using establishment‐level occupational data, I construct a measure of firms' share of routine‐task labor. Compared to their industry peers, firms with a higher share of routine‐task labor (i) invest more in machines and reduce more routine‐task labor during economic downturns, and (ii) have lower expected stock returns.     

Bank exposure to market fear

We find that increases in implied market volatility (a proxy for market fear) have a significant impact on returns of bank stocks, above and beyond systematic risk proxied by the expected excess market return during a bad economic regime. Large bank returns are favorably affected by increases in implied market volatility during the crisis, while small banks are adversely affected by increases in implied market volatility. We attribute the different effects among the size-categorized bank portfolios to the perception that large banks are protected by too-big-to-fail policies. Within the sample of small banks, the adverse share price response to increased implied market volatility is more pronounced for banks that rely more heavily on non-traditional sources of funds, use a high proportion of loans in their assets, have a higher level of non-performing assets, and have a relatively low provision for loan losses. The adverse effect of negative innovations in implied market volatility on small bank returns during the crisis is primarily driven by exposure of their loan portfolio to weak economic conditions.     

Nonlinearity and Flight‐to‐Safety in the Risk‐Return Trade‐Off for Stocks and Bonds

We document a highly significant, strongly nonlinear dependence of stock and bond returns on past equity market volatility as measured by the VIX. We propose a new estimator for the shape of the nonlinear forecasting relationship that exploits variation in the cross‐section of returns. The nonlinearities are mirror images for stocks and bonds, revealing flight‐to‐safety: expected returns increase for stocks when volatility increases from moderate to high levels while they decline for Treasuries. These findings provide support for dynamic asset pricing theories in which the price of risk is a nonlinear function of market volatility.