The Conditional Beta and the Cross-Section of Expected Returns

We examine the cross-sectional relation between conditional betas and expected stock returns for a sample period of July 1963 to December 2004. Our portfolio-level analyses and the firm-level cross-sectional regressions indicate a positive, significant relation between conditional betas and the cross-section of expected returns. The average return difference between high- and low-beta portfolios ranges between 0.89% and 1.01% per month, depending on the time-varying specification of conditional beta. After controlling for size, book-to-market, liquidity, and momentum, the positive relation between market beta and expected returns remains economically and statistically significant.     

Conditional Skewness in Asset Pricing Tests

If asset returns have systematic skewness, expected returns should include rewards for accepting this risk. We formalize this intuition with an asset pricing model that incorporates conditional skewness. Our results show that conditional skewness helps explain the cross-sectional variation of expected returns across assets and is significant even when factors based on size and book-to-market are included. Systematic skewness is economically important and commands a risk premium, on average, of 3.60 percent per year. Our results suggest that the momentum effect is related to systematic skewness. The low expected return momentum portfolios have higher skewness than high expected return portfolios.     

Optimal Investment, Growth Options, and Security Returns

As a consequence of optimal investment choices, a firm's assets and growth options change in predictable ways. Using a dynamic model, we show that this imparts predictability to changes in a firm's systematic risk, and its expected return. Simulations show that the model simultaneously reproduces: (i) the time-series relation between the book-to-market ratio and asset returns; (ii) the cross-sectional relation between book-to-market, market value, and return; (iii) contrarian effects at short horizons; (iv) momentum effects at longer horizons; and (v) the inverse relation between interest rates and the market risk premium.     

Beta,size, book-to-market equity and returns: A study based on UK data

This paper examines the role of beta, size and book-to-market equity as competing risk measurements in explaining the cross-sectional returns of UK securities for the period July 1980 through June 2000. The methodology of [Fama, E., French, K., 1992. The cross-section of expected stock returns. Journal of Finance 47, 427–467] and [Pettengill, G., Sundaram, S., Mathur, I., 1995. The conditional relation between beta and returns. Journal of Financial and Quantitative Analysis 30, 101–116] is adopted. Results show that, when adopting the methodology of [Pettengill, G., Sundaram, S., Mathur, I., 1995. The conditional relation between beta and returns. Journal of Financial and Quantitative Analysis 30, 101–116], where data is segmented between up and down markets, a significant relationship is found between beta and returns even in the presence of size and book-to-market equity. Size is not found to be a significant risk variable, whereas book-to-market equity is found to be priced by the market and is thus a significant determinant of security returns. This is the case irrespective of the methodology adopted.     

Return dispersion and expected returns

This paper proposes a two-factor asset-pricing model that incorporates market return and return dispersion. Consistent with this model, we find that stocks with higher sensitivities to return dispersion have higher average returns, and that return dispersion carries a significant positive price of risk. In particular, the return dispersion factor dominates the book-to-market factor in explaining cross-sectional expected returns. The return dispersion model outperforms the CAPM, MVM, IVM, and FF-3M when using a set of 5×5 test portfolios constructed from NYSE and AMEX stock returns from August 1963 to December 2005. Return dispersion continues to play an important role in explaining the cross-sectional variation of expected returns, even when market volatility, idiosyncratic volatility, size, book-to-market factors, and a momentum factor are included. This study sheds some light on the ability of return dispersion to explain expected returns beyond the standard asset-pricing factors. Our finding suggests that return dispersion captures two dimensions of systematic risk: the business cycle and fundamental economic restructuring.     

Can stochastic discount factor models explain the cross-section of equity returns?

We propose a multivariate test of the capital asset pricing model (C-CAPM) of the cross-sectional variation in equity returns in which we compare cross-sectional variation in equity returns to the cross-sectional variation in their conditional covariance with stochastic discount factors. We use a multivariate generalized heteroskedasticity in mean model to estimate 25 portfolios that are formed on size and the book-to-market ratio. Each portfolio is allowed to have its own no-arbitrage condition. We find that although the conditional covariances of returns with consumption exhibit negative variation across size, they do not vary across the book-to-market ratio. Thus, C-CAPM can capture the size effect, but not the value effect. The fit is, however, improved by allowing the coefficients on the consumption covariances to be different. The value effect appears to be associated with the book-to-market ratio as well as size. On its own the book-to-market ratio does not generate additional information about average returns to C-CAPM. A possible explanation for these findings is that both small and low book-to-market ratio firms are expected to have higher rates of growth.     

Determinants of idiosyncratic volatility: Evidence from the Indian stock market

This paper investigates whether firm-specific characteristics explain idiosyncratic volatility in the stocks of non-financial firms traded in the Indian stock market. It employs the linear time series five-factor model, augmented with a liquidity factor and the conditional EGARCH model, to extract yearly idiosyncratic volatility. We estimate a panel data regression to quantify the relationship between firm-specific characteristics and the volatility of individual securities. The results show that idiosyncratic volatility is significant in emerging markets such as India, and that cross-sectional return variations of firms are associated with firm-specific characteristics such as firm size, book-to-market ratio, momentum, liquidity, cash flow-to-price ratio, and returns on assets. We find that the idiosyncratic risk documented in this study is associated with smaller size of company, higher liquidity, low momentum, high book-to-market ratio, and low cash flow-to-price ratio. The findings suggest need to develop alternative tools to make investment decisions in emerging markets.     

The intertemporal relation between expected returns and risk

This paper explores the time-series relation between expected returns and risk for a large cross section of industry and size/book-to-market portfolios. I use a bivariate generalized autoregressive conditional heteroskedasticity (GARCH) model to estimate a portfolio's conditional covariance with the market and then test whether the conditional covariance predicts time–variation in the portfolio's expected return. Restricting the slope to be the same across assets, the risk-return coefficient is highly significant with a risk–aversion coefficient (slope) between one and five. The results are robust to different portfolio formations, alternative GARCH specifications, additional state variables, and small sample biases. When conditional covariances are replaced by conditional betas, the risk premium on beta is estimated to be in the range of 3% to 5% per annum and is statistically significant.     

Cross-sectional determinants of New Zealand share market returns

We present evidence of the cross-sectional relation between security returns, beta, firm size and book-to-market ratio over the period 1971 to 1993 on the New Zealand sharemarket. Our results suggest that the NZSE-40 market index is not a mean-variance efficient market proxy—the betas calculated with respect to it being of little use for explaining expected returns cross-sectionally. Also, there is a significant positive relation between book-to-market ratio and average return.     

Market skewness risk and the cross section of stock returns

The cross section of stock returns has substantial exposure to risk captured by higher moments of market returns. We estimate these moments from daily Standard & Poor's 500 index option data. The resulting time series of factors are genuinely conditional and forward-looking. Stocks with high exposure to innovations in implied market skewness exhibit low returns on average. The results are robust to various permutations of the empirical setup. The market skewness risk premium is statistically and economically significant and cannot be explained by other common risk factors such as the market excess return or the size, book-to-market, momentum, and market volatility factors, or by firm characteristics.     

Does Financial Distress Risk Drive the Momentum Anomaly?

This paper brings together the evidence on two asset pricing anomalies—continuation of prior returns (momentum) and the market mispricing of distressed firms—using UK data. Our analysis demonstrates both these effects are driven by market underreaction to financial distress risk. In particular, we find momentum is proxying for distress risk, and is largely subsumed by our distress risk factor. We also find, as with US studies, no evidence that size and book-to-market (B/M) effects in stock returns are linked to financial distress .     

The conditional relation between dispersion and return

The main goal of this paper is to examine the conditional pricing effect of return dispersion on the cross section of returns. We observe a systematic conditional relation between dispersion and return even after controlling for market, size and book-to-market factors. However, we find that return dispersion risk is asymmetrically priced with a significantly positive premium observed during periods of large market gains only. The findings are found to be robust to alternative conditional specifications of market returns, suggesting asymmetric pricing effect of the return dispersion factor. We provide alternative explanations for the systematic risk captured by the return dispersion factor and discuss implications for portfolio management and corporate decisions.     

An Analysis of Contrarian Investment Strategies in the UK

The performance of contrarian, or value strategies – those that invest in stocks that have low market value relative to a measure of their fundamentals – continues to attract attention from researchers and practitioners alike. While there is much extant evidence on the profitability of value strategies, however, most of this evidence pertains to the US. In this paper, we provide a detailed characterisation of value strategies using data on UK stocks for the period 1975 to 1998. We first undertake simple one-way and two-way classifications of stocks in which value is defined using both past performance and expected future performance. Using sales growth as a proxy for past performance and book-to-market, earnings yield and cash flow yield as measures of expected future performance, we find that that stocks that have both poor past performance and low expected future performance have significantly higher returns than those that have either good past performance or good expected future performance. Allowing for size effects in returns reduces the value premium but it nevertheless remains significant. We go on to explore whether the profitability of value strategies in the UK can be explained using the three factor model of Fama and French (1996). Broadly consistent with the results for the US, we find that using the one-way classification the excess returns to almost all value strategies can be explained by their loading on the market, book-to-market and size factors. However, in contrast with the US, using the two-way classification there are excess returns to value strategies based on book-to-market and sales growth, even after controlling for their loading on the market, book-to-market and size factors.     

Default Risk and Equity Returns: Evidence from the Taiwan Equities Market

Studies of risk and return characteristics of different portfolios have recently gained enormous attention. Differing from past studies, this paper uses a compound option model to build the proxy of default risk and evaluate the relationship between default risk effect and equity returns. The primary goal of this paper is to evaluate the relationship among default risk, size, book-to-market, and equity returns, using data drawn from the Taiwan equities market, and to also examine whether size and book-to-market are proxies for default risk. The results show that the effects of size and book-to-market exist in different default portfolios when default risks are controlled. If size or book-to-market is controlled, there are no default effects. In the regression analysis, when default risk is included in Fama and French’s Three Factor Model, it shows that size, book-to-market and default risk have significant influence on equity returns and default risk is a systematic risk. Default risk is also more powerful in explaining returns when the compound option model is adopted for estimating default risks.     

Using Expectations to Test Asset Pricing Models

Asset pricing models generate predictions relating assets' expected rates of return and their risk attributes. Most tests of these models have employed realized rates of return as a proxy for expected return. We use analysts' expected rates of return to examine the relation between these expectations and firm attributes. By assuming that analysts' expectations are unbiased estimates of market-wide expected rates of return, we can circumvent the use of realized rates of return and provide evidence on the predictions emanating from traditional asset pricing models. We find a positive, robust relation between expected return and market beta and a negative relation between expected return and firm size, consistent with the notion that these are risk factors. We do not find that high book-to-market firms are expected to earn higher returns than low book-to-market firms, inconsistent with the notion that book-to-market is a risk factor.     

Market liquidity risk factor and financial market anomalies: Evidence from the Chinese stock market

The Chinese stock market is an order-driven market and hence its characteristics are structurally different from quote-driven markets. There are no studies that consider the role of the market liquidity risk factor in determining cross-sectional stock returns in a model including financial market anomalies for order-driven markets. Our aim is to test whether financial market anomalies such as firm size, the book-to-market ratio, the turnover rate, and momentum both with and without the inclusion of the market liquidity risk factor in the case of the Chinese stock market can explain cross-sectional stock returns. The empirical framework is based on the model proposed by Avramov and Chordia (AC, 2006). Our main finding is that the AC model can capture financial market anomalies except momentum when we include the market liquidity risk factor on the Chinese stock market.     

In search of distress risk in China's stock market

We examine the significance of size, book-to-market, and momentum factors in capturing financial distress risk in China's stock market. Consistent with the market underreaction hypothesis, we find that the momentum factor proxies for distress risk in China's stock market and that the explanatory power of momentum is subsumed when a distress factor is included in the asset pricing model. Our analysis demonstrates no evidence that size and book-to-market effects are driven by financial distress risk.¹     

Macroeconomic risk and the cross-section of stock returns

We develop a conditional version of the consumption capital asset pricing model (CCAPM) using the conditioning variable from the cointegrating relation among macroeconomic variables (dividend yield, term spread, default spread, and short-term interest rate). Our conditioning variable has a strong power to predict market excess returns in the presence of competing predictive variables. In addition, our conditional CCAPM performs approximately as well as Fama and French’s (1993) three-factor model in explaining the cross-section of the Fama and French 25 size and book-to-market sorted portfolios. Our specification shows that value stocks are riskier than growth stocks in bad times, supporting the risk-based story.     

A neoclassical interpretation of momentum

The neoclassical theory of investment implies that expected stock returns are tied with the expected marginal benefit of investment divided by the marginal cost of investment. Winners have higher expected growth and expected marginal productivity (two major components of the marginal benefit of investment), and earn higher expected stock returns than losers. The investment model succeeds in capturing average momentum profits, reversal of momentum in long horizons, long-run risks in momentum, and the interaction of momentum with several firm characteristics. However, the model fails to reproduce the procyclicality of momentum as well as its negative interaction with book-to-market equity.     

Institutional investors and the limits of arbitrage

The returns and stock holdings of institutional investors from 1980 to 2007 provide little evidence of stock-picking skill. Institutions as a whole closely mimic the market portfolio, with pre-cost returns that have nearly perfect correlation with the value-weighted index and an insignificant CAPM alpha of 0.08% quarterly. Institutions also show little tendency to bet on any of the main characteristics known to predict stock returns, such as book-to-market, momentum, or accruals. While particular groups of institutions have modest stock-picking skill relative to the CAPM, their performance is almost entirely explained by the book-to-market and momentum effects in returns. Further, no group holds a portfolio that deviates efficiently from the market portfolio.