Volatility Risk Premium,Risk Aversion,and the Cross‐Section of Stock Returns

We test if innovations in investor risk aversion are a priced factor in the stock market. Using 25 portfolios sorted on book‐to‐market and size as test assets, our new factor together with the market factor explains 64% of the variation in average returns compared to 60% for the Fama‐French model. The new factor is generally significant with an estimated risk premium close to its time series mean also when industry portfolios and portfolios sorted on previous returns are augmented to the test assets.     

Can tail risk explain size,book‐to‐market,momentum, and idiosyncratic volatility anomalies?

We examine the impact of tail risk on the return dynamics of size, book‐to‐market ratio, momentum and idiosyncratic volatility sorted portfolios. Our time‐series analyses document significant portfolio return exposures to aggregate tail risk. In particular, portfolios that contain small, value, high idiosyncratic volatility and low momentum stocks exhibit negative and statistically significant tail risk betas. Our cross‐sectional analyses at the individual stock level suggest that tail risk helps in explaining the four pricing anomalies, particularly size and idiosyncratic volatility anomalies.     

IS THE BOOK‐TO‐MARKET RATIO A MEASURE OF RISK?

We develop a leverage‐based alternative to traditional asset pricing models to investigate whether the book‐to‐market ratio acts as a proxy for risk. We argue that the book‐to‐market ratio should act as a proxy because of the expected relations between (1) financial risk and measures of capital structure based on the market value of equity and (2) asset risk and measures of capital structure based on the book value of equity. We find no relation between average stock returns and the book‐to‐market ratio in all‐equity firms after controlling for firm size, and an inverse relation between average stock returns and the book‐to‐market ratio in firms with a negative book value of equity.     

Size and momentum in European equity markets: empirical findings from varying beta Capital Asset Pricing Model

We use securities listed on 13 European equity markets to form size and momentum portfolios. We find limited evidence of a size premium but significant momentum returns in eight sample markets. We find that these premia may not constitute an anomaly because they are consistent with a varying‐beta Capital Asset Pricing Model. We also show that systematic risk is related to the business cycle. Furthermore, the results suggest that although size and especially momentum returns are significant, it would be difficult to exploit them in the short to medium run, because they are positive and sizeable in very few years in our sample.     

Risk‐Adjusted Long‐Term Contrarian Profits: Evidence from Non‐S&P 500 High‐Volume Stocks

Can trading volume help unravel the long‐term overreaction puzzle? With portfolios of non‐S&P 500 NYSE stocks, we show that (1) both the high‐ and low‐volume (abnormal volume) contrarian portfolios earn a much higher market‐adjusted excess return than the normal‐volume contrarian portfolio, (2) however, when leverage‐induced risk is factored in, excess returns from contrarian portfolios with normal‐ and low‐volume stocks are insignificant, (3) only excess returns from high‐volume contrarian stocks are significant and cannot be explained by the time‐varying risk and return framework, and (4) such high‐volume, risk‐adjusted excess returns arise mainly from winner (glamour) stocks.     

The Piotroski F‐score: evidence from Australia

A market‐neutral strategy that is long [short] stocks with a high [low] Piotroski F‐score generates an index‐weighted 0.8 percent pm on S&P/ASX 200 stocks and 1.4 percent pm on smaller stocks. Equal‐weighted returns are higher and in all cases returns are statistically significant. However, the Carhart model alphas are not statistically significant except in the case of equal‐weighted small cap portfolios. For such portfolios, however, most of the alpha comes from the short side and most institutional investors would find them uninvestable due to capacity constraints. A range of tests indicate that analyst neglect does not explain the F‐score premium.     

Extreme downside risk and expected stock returns

We propose a measure for extreme downside risk (EDR) to investigate whether bearing such a risk is rewarded by higher expected stock returns. By constructing an EDR proxy with the left tail index in the classical generalized extreme value distribution, we document a significantly positive EDR premium in cross-section of stock returns even after controlling for market, size, value, momentum, and liquidity effects. The EDR premium is more prominent among glamor stocks and when high market returns are expected. High-EDR stocks are generally characterized by high idiosyncratic risk, large downside beta, lower coskewness and cokurtosis, and high bankruptcy risk. The EDR premium persists after these characteristics are controlled for. Although Value at Risk (VaR) plays a significant role in explaining the EDR premium, it cannot completely subsume the EDR effect.     

On the Stability of the Cross‐Section of Expected Stock Returns in the Cross‐Section: Understanding the Curious Role of Share Turnover

In this paper, we shed further light on cross‐sectional predictors of stock return performance. Specifically, we explore whether the cross‐section of expected stock returns is robust within stock groups sorted by past monthly return. We find that the book/market and momentum effects are remarkably robust to sorting on past returns. However, share turnover is negatively related to future returns for stocks with abnormally low stock price performance in the recent past, but postively related to returns for well‐performing stocks. This casts doubt on the use of turnover as a liquidity proxy, but is consistent with turnover being a proxy for momentum trading which pushes prices in the direction of past price movements. Our results are robust to both NYSE/AMEX and Nasdaq stocks, and also robust to stratifying the sample by time period.     

Market Expectations in the Cross‐Section of Present Values

Returns and cash flow growth for the aggregate U.S. stock market are highly and robustly predictable. Using a single factor extracted from the cross‐section of book‐to‐market ratios, we find an out‐of‐sample return forecasting R² of 13% at the annual frequency (0.9% monthly). We document similar out‐of‐sample predictability for returns on value, size, momentum, and industry portfolios. We present a model linking aggregate market expectations to disaggregated valuation ratios in a latent factor system. Spreads in value portfolios’ exposures to economic shocks are key to identifying predictability and are consistent with duration‐based theories of the value premium.     

Empirical Evidence of the Existence of Investable Premiums in Emerging Market Investable Stocks

This paper shows that portfolios of more investable securities bear a premium when compared to portfolios of less investable stocks, reflecting compensation for local risk factors. The investable premium is overwhelmingly priced across 3,782 companies traded in 29 emerging markets from 1988 to 2006. The investable premium impacts stock returns at least as much as other fundamental premiums such as size, value, momentum, and loads on political, economic, and financial risk factors. The impact of the investable premium on emerging stocks returns has increased in strength, implying that foreign ownership has greater influence on local markets in recent years.     

ROBUSTNESS OF THE HEADQUARTERS‐CITY EFFECT ON STOCK RETURNS

Recent studies report that U.S. firms headquartered near each other experience positive comovement in their stock returns, a finding suggestive of local biases in equity trading activity. We investigate the robustness of these findings and find that including additional pricing factors in models for monthly stock returns materially reduces the magnitude of the headquarters‐city effect in stock returns. Additionally, we find that an implicit null hypothesis of zero local return comovement is inappropriate as there is positive comovement between a stock's return and returns on portfolios of stocks from nonheadquarters cities, on average. Nevertheless, results benchmarked against estimates based on resampling methods indicate a significant and robust headquarters‐city effect in stock returns.     

UNDERSTANDING SIZE AND THE BOOK‐TO‐MARKET RATIO: AN EMPIRICAL EXPLORATION OF BERK'S CRITIQUE

Because they are scaled by price, the ability of size (i.e., the market capitalization of a firm) and the book‐to‐market equity ratio to determine expected returns may, according to Berk (1995) , reflect only a simultaneity bias. The two‐stage least squares approach is used to control for this bias and to investigate the economic meanings of these variables. We discover that size and the book‐to‐market ratio contain distinct and significant components of financial distress, growth options, the momentum effect, liquidity, and firm characteristics. Our findings support Berk in his contention that that size and the book‐to‐market ratio reflect a combination of different economic mechanisms that are misspecified in the expected return process.     

Is default risk the hidden factor in momentum returns? Some empirical results

This paper analyzes the role of default risk in the momentum effect focusing on data from four developed European stock markets (France, Germany, Spain and the United Kingdom). Using a market‐based measure of default risk, we show that it is not the hidden factor behind this effect. While the loser portfolio is characterized by high default risk, small size, high book‐to‐market and illiquidity, characterization of the winner portfolio is somewhat more complex. Given that the momentum strategy is the return differential between the winners and the losers, factors such as the stock market cycle or the evolution of momentum portfolios against their reference point make momentum profits difficult to forecast.     

Are good-news firms riskier than bad-news firms?

This paper examines the relative risk of good-news firms, i.e., those with high standardized unexpected earnings (SUE), and bad-news (low SUE) firms using a stochastic discount factor approach. We find that a stochastic discount factor constructed from a set of basis assets helps explain post-earnings-announcement drift (PEAD). The risk exposures on the pricing kernel increase monotonically from the lowest to highest SUE sorted portfolios. Specifically, good-news firms always have higher risk exposures than bad-news firms in both 10 SUE sorted portfolios and 25 size and SUE sorted portfolios. However, the estimated expected risk premium is too small to explain the observed magnitude of returns on the PEAD strategy. Our risk adjustment can explain only about one-fourth of the total magnitude of the average realized return to the PEAD strategy. As a result, the average risk-adjusted returns of earnings momentum strategies are mostly positive and significant. Overall, our results support the view that at least some portion of the returns to the earnings momentum strategies examined represent compensation for bearing increased risk.     

Size,value and momentum in stock returns: evidence from India

This paper examines the effects of size, value and momentum on the cross-sectional relation between expected returns and risk in the Indian stock market. We find that the conditional Carhart four-factor model empirically describes the variation of cross-section of return better than the unconditional model. When size, book-to-market and momentum effects are controlled in the conditional model, the positive relation of market beta, book-to-market and momentum with expected returns remains economically and statistically significant. However, this evidence is found to be subject to characteristics of test portfolios. The expected returns are sensitive to changes in predictive macroeconomic variables.     

Fails‐to‐Deliver before and after the Implementation of Rule 203 and Rule 204

We study the determinants of fails‐to‐deliver in the period before and after the implementation of Rule 203 (elimination of option market maker exception from the locate and close‐out requirement) and Rule 204 (t+3 close‐out rule) in September 2008. We find a positive relation between short selling and fails‐to‐deliver that weakens after the implementation of these rules. Fails‐to‐deliver are higher for stocks with low institutional ownership, low book‐to‐market, small market capitalization, high turnover, and put option availability. The relation between short selling and these measures of borrowing costs is also weaker after the implementation of these rules.     

Cashflow risk,systematic earnings revisions,and the cross-section of stock returns

The returns of stocks are partially driven by changes in their expected cashflow. Using revisions in analyst earnings forecasts, we construct an analyst earnings beta that measures the covariance between the cashflow innovations of an asset and those of the market. A higher analyst earnings beta implies greater sensitivity to marketwide revisions in expected cashflow, and therefore higher systematic risk. Our analyst earnings beta captures exposure to macroeconomic fluctuations and has a positive risk premium that provides a partial explanation for the value premium, size premium, and long-term return reversals. From 1984 to 2005, 55.1% of the return variation across book-to-market, size, and long-term return reversal portfolios is captured by their analyst earnings betas.     

Productivity Risk and Industry Momentum

A productivity shock identified through a vector autoregression model is a priced risk factor for one‐month industry momentum portfolios and commands a positive risk premium. Stocks in winning industries have greater sensitivity to productivity news, thereby earning higher average returns than stocks in losing industries. This evidence lends support to an Intertemporal Capital Asset Pricing Model (ICAPM) with human wealth. In many specifications, exposure to productivity risk captures more than half of the observed industry momentum profits. This paper studies the sources of profits and attributes the risks of industry momentum portfolios to the behavior of their underlying cash flows.     

Do firm characteristics matter in explaining the herding effect on returns?

This paper explores whether firm characteristics matter in determining the effect of investor herding on asset returns. We find that the level of herding alone does not command a significant effect on industry returns, implied by insignificant return spreads between industries that experience high and low degrees of herding. On the other hand, we observe that herding has a significant interaction with size and past returns. We find that small firms with high level of herding significantly underperform small firms that experience low herding. Similarly, past loser industries with high level of herding significantly outperform loser industries with low herding. No significant interactions between book‐to‐market and market beta with herding are observed. Overall, the findings suggest that the herding effect presents itself via size and momentum channels with significant investment implications.