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.     

Stock Return Predictability of Residual‐Income‐Based Valuation: Risk or Mispricing?

In an influential paper, Frankel and Lee (1998) conclude that the stock return predictability of the value‐to‐price ratio (V/P) results from market mispricing. This paper confirms whether the V/P reflects the rational risk premiums associated with the V/P factor or is better explained by market inefficiency. Following Daniel and Titman (1997), this paper examines whether the V/P characteristics or the V/P factor loadings predict stock returns. The findings show that the V/P loadings are positively associated with average returns even after controlling for the V/P characteristics in both time series and cross‐sectional tests. The overall results suggest that the mispricing explanation of the V/P effect is premature.     

Does Risk Management Add Value? A Survey of the Evidence

The fact that 92% of the world's 500 largest companies recently reported using derivatives suggests that corporate managers believe financial risk management can increase shareholder value. Surveys of finance academics indicate that they too believe that corporate risk management is, on the whole, a valueadding activity. This article provides an overview of almost 30 years of broadbased, stock‐market‐oriented academic studies that address one or more of the following questions:

• ? Are interest rate, exchange rate, and commodity price risks reflected in stock price movements?
• ? Is volatility in corporate earnings and cash flows related in a systematic way to corporate market values?
• ? Is the corporate use of derivatives associated with reduced risk and higher market values?

The answer to the first question, at least in the case of financial institutions and interest rate risk, is a definite yes; all studies with this focus find that the stock returns of financial firms are clearly sensitive to interest rate changes. The stock returns of industrial companies exhibit no pronounced interest rate exposure (at least as a group), but industrial firms with significant cross‐border revenues and costs show considerable sensitivity to exchange rates (although such sensitivity actually appears to be reduced by the size and geographical diversity of the largest multinationals). What's more, the corporate use of derivatives to hedge interest rate and currency exposures appears to be associated with lower sensitivity of stock returns to interest rate and FX changes. But does the resulting reduction in price sensitivity affect value—and, if so, how? Consistent with a widely cited theory that risk management increases value by limiting the corporate “underinvestment problem,” a number of studies show a correlation between lower cash flow volatility and higher corporate investment and market values. The article also cites a small but growing group of studies that show a strong positive association between derivatives use and stock price performance (typically measured using price‐to‐book ratios). But perhaps the nearest the research comes to establishing causality are two studies—one of companies that hedge FX exposures and another of airlines' hedging of fuel costs—that show that, in industries where hedging with derivatives is common, companies that hedge outperform companies that don't.     

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).     

Bank Capital: Lessons from the Financial Crisis

Using a multicountry panel of banks, we study whether better capitalized banks experienced higher stock returns during the financial crisis. We differentiate among various types of capital ratios: the Basel risk‐adjusted ratio, the leverage ratio, the Tier 1 and Tier 2 ratios, and the tangible equity ratio. We find several results: (i) before the crisis, differences in capital did not have much impact on stock returns; (ii) during the crisis, a stronger capital position was associated with better stock market performance, most markedly for larger banks; (iii) the relationship between stock returns and capital is stronger when capital is measured by the leverage ratio rather than the risk‐adjusted capital ratio; (iv) higher quality forms of capital, such as Tier 1 capital and tangible common equity, were more relevant.     

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.     

Do Decomposed Financial Ratios Predict Stock Returns and Fundamentals Better?

We investigate the prediction of excess returns and fundamentals by financial ratios, which include dividend‐price ratios, earnings‐price ratios, and book‐to‐market ratios, by decomposing financial ratios into a cyclical component and a stochastic trend component. We find both components predict excess returns and fundamentals. Cyclical components predict increases in future stock returns, while stochastic trend components predict declines in future stock returns in long horizons. This helps explain previous findings that financial ratios in the absence of decomposition find weak predictive power in short horizons and some predictive power in long horizons. We also find both components predict fundamentals.     

Leverage and the Cross‐Section of Equity Returns

Building on theoretical asset pricing literature, we examine the role of market risk and the size, book‐to‐market (BTM), and volatility anomalies in the cross‐section of unlevered equity returns. Compared with levered (stock) returns, unlevered market beta plays a more important role in explaining the cross‐section of unlevered equity returns, even after controlling for size and BTM. The size effect is weakened, while the value premium and the volatility puzzle virtually disappear for unlevered returns. We show that leverage induces heteroskedasticity in returns. Unlevering returns removes this pattern, which is otherwise difficult to address by controlling for leverage in regressions.     

Improving the Health of Healthcare Companies

The healthcare sector has been extremely effective in improving human health while at the same time delivering outstanding returns to shareholders, at least on average. But averages can hide a lot of poor performance, and careful examination of the sector shows a sizable disparity between the long‐run productivity and value added of the top companies and the rest. To better understand the reasons for this disparity, the authors undertook a comprehensive study of how differences in capital deployment strategies, financial policies, and measures of corporate operating performance such as sales growth and return on capital are associated with returns to shareholders. Perhaps the most striking finding is the strong positive correlation in the healthcare industry between higher rates of reinvestment, especially in the form of spending on R&D and acquisitions, and stock price performance. And given the importance of such reinvestment, it is not surprising that maintaining financial flexibility by paying down net debt and otherwise limiting corporate leverage—and even issuing significant equity—are all associated with higher stock returns. When it comes to operating performance, moreover, it's not enough just to be good; it takes growth and improvement in cash flow and earnings to drive share prices higher. Measures of changes in performance such as increases in EBIT and ROIC, and high rates of growth in sales, all show consistently strong and positive relationships with stock returns while measures of levels of performance, especially EBIT margins and EBITDA margins, demonstrate relationships that are weak and in some cases even negative. Last, and consistent with the findings reported above, despite often vocal investor demands to pay dividends and buy back shares, in the case of healthcare as a whole such distributions have a clearly inverse relationship with share price performance. That is to say, the larger the payouts to shareholders, the lower the shareholder returns.     

The relationship between size,book-to-market equity ratio,earnings–price ratio,and return for the Hong Kong stock market

In this paper, we investigate the relation between stock returns and β, size (ME), leverage, book-to-market equity ratio, and earnings–price ratio (E/P) in Hong Kong stock market using the Fama and French (FF) [J. Finance 47 (1992) 427] approach. FF find that two variables, size and book-to-market equity, combine to capture the cross-sectional variation in average stock returns associated with β, size, leverage, book-to-market equity, and E/P ratios. In this paper, similar to previous studies in Hong Kong and US stock markets, we find that β is unable to explain the average monthly returns on stocks continuously listed in Hong Kong Stock Exchange for the period July 1984–June 1997. But three of the variables, size, book-to-market equity, and E/P ratios, seem able to capture the cross-sectional variation in average monthly returns over the period. The other two variables, book leverage and market, are also able to capture the cross-sectional variation in average monthly returns. But their effects seem to be dominated by size, book-to-market equity, and E/P ratios, and considered to be redundant in explaining average returns when size, book-to-market equity, and E/P ratios are also considered. The results are consistent across subperiods, across months, and across size groups. These suggest that the results are not driven by extreme observations or abnormal return behavior in some of the months or by size groups.     

Oil and stock market activity when prices go up and down: the case of the oil and gas industry

We examine the asymmetric effects of daily oil price changes on equity returns, market betas, oil betas, return variances, and trading volumes for the US oil and gas industry. The responses of stock returns associated with negative changes in oil prices are higher than that associated with positive changes in oil prices. Stock risk measured by market beta is influenced more due to oil price decreases than due to oil price increases. On the other hand, oil risk exposures (oil betas) and return variances are more influenced by oil price increases than oil price decreases. The results of our study indicate that oil and gas firm returns, market betas, oil betas, return variances respond asymmetrically to oil price changes. We also find that relative changes in oil prices along with firm-specific factors such as firm size, ROA, leverage, market-to-book ratio (MBR) are important in determining the effects of oil price changes on oil and gas firms’ returns, risks, and trading volumes.     

Housing Collateral, Consumption Insurance, and Risk Premia: An Empirical Perspective

In a model with housing collateral, the ratio of housing wealth to human wealth shifts the conditional distribution of asset prices and consumption growth. A decrease in house prices reduces the collateral value of housing, increases household exposure to idiosyncratic risk, and increases the conditional market price of risk. Using aggregate data for the United States, we find that a decrease in the ratio of housing wealth to human wealth predicts higher returns on stocks. Conditional on this ratio, the covariance of returns with aggregate risk factors explains 80% of the cross‐sectional variation in annual size and book‐to‐market portfolio returns.     

Can Operating Leverage Be the Cause of the Value Premium?

Recent theoretical models (Carlson, Fisher, and Giammarino, 2004) predict an association between the book-to-market equity ratio (BE/ME) and operating leverage in the cross-section. Consistent with these models, we find a positive association between BE/ME and the degree of operating leverage (DOL), between DOL and stock returns, and between DOL and systematic risk. Overall, our findings provide support for a risk-based explanation for the value premium that is consistent with existing theoretical models. The evolution of systematic risk associated with firm-level investment activity, rather than financial distress, seems to be the main determinant of the value premium.     

Share Issuance and Factor Timing

We show that characteristics of stock issuers can be used to forecast important common factors in stocks' returns such as those associated with book‐to‐market, size, and industry. Specifically, we use differences between the attributes of stock issuers and repurchasers to forecast characteristic‐related factor returns. For example, we show that large firms underperform after years when issuing firms are large relative to repurchasing firms. While our strongest results are for portfolios based on book‐to‐market (i.e., HML), size (i.e., SMB), and industry, our approach is also useful for forecasting factor returns associated with distress, payout policy, and profitability.     

Time‐Varying Risk–Return Trade‐off in the Stock Market

We uncover a strong comovement of the stock market risk–return trade‐off with the consumption–wealth ratio (CAY). The finding reflects time‐varying investment opportunities rather than countercyclical aggregate relative risk aversion. Specifically, the partial risk–return trade‐off is positive and constant when we control for CAY as a proxy for investment opportunities. Moreover, conditional market variance scaled by CAY is negatively priced in the cross‐section of stock returns. Our results are consistent with a limited stock market participation model, in which shareholders require an illiquidity premium that increases with CAY, in addition to the risk premium that is proportional to conditional market variance.     

Equilibrium "Anomalies"

Many empirical “anomalies” are actually consistent with the single beta capital asset pricing model if the empiricist utilizes an equity‐only proxy for the true market portfolio. Equity betas estimated against this particular inefficient proxy will be understated, with the error increasing with the firm's leverage. Thus, firm‐specific variables that correlate with leverage (such as book‐to‐market and size) will appear to explain returns after controlling for proxy beta simply because they capture the missing beta risk. Loadings on portfolios formed on relative leverage and relative distress completely subsume the powers of the Fama and French (1993) returns to small minus big market capitalization (SMB) portfolios and returns to high minus low book‐to‐market (HML) portfolios factors in explaining cross‐sectional returns.     

Stock Liquidity Risk and the Cross‐sectional Earnings‐Returns Relationship

We argue that a higher sensitivity to aggregate market‐wide liquidity shocks (i.e., a higher liquidity risk) implies a tendency for a stock's price to converge to fundamentals. We test this intuition within the framework of the earnings‐returns relationship. We find a positive liquidity risk effect on the relationship between return and expected change in earnings. This effect on the earnings‐returns relationship is distinct from the negative effect observed for stock illiquidity level. Notably, the liquidity risk effect is evident (absent) during periods of neutral/low (high) aggregate market liquidity. We also show that the liquidity risk effect is dominant in firms that: (a) are of intermediate size; (b) are of intermediate book‐to‐market; and (c) are profit making.     

How Do Investors Regard ESOs?

All top‐50 and more than 80% of the top‐500 Australian listed companies now reward their executives with stock options (ESOs) of one kind or another.₁ We address the question: “Which method of accounting for ESOs — current practice, the US FASB's recommended practice or the AASB's preferred position — most closely reflects investors' pricing decisions?” We answer the question using models that relate a company's stock price to its earnings and book value of equity calculated according to these three choices of accounting treatment.     

Accounting Ratios and the Cross‐section of Expected Stock Returns

Under clean‐surplus accounting, the log return on a stock can be decomposed into a linear function of the contemporaneous log return on equity, the contemporaneous log dividend–price ratio (if the stock pays a dividend), and both the contemporaneous and lagged values of the log book‐to‐market equity ratio. This paper studies the implications of this decomposition for the cross‐section of conditional expected stock returns. The empirical analysis reveals that the log accounting ratios capture cross‐sectional variation in both the conditional mean and conditional variance of log stock returns, which is consistent with the decomposition. It also brings fresh insights to the relation between firm size (market equity) and conditional expected stock returns. The evidence indicates that the conditional median return increases with firm size, while the conditional return skewness decreases with firm size. Empirically, the skewness effect outweighs the median effect, leading to the well‐documented inverse relation between size and average returns. The results of out‐of‐sample tests suggest that investors could use the information provided by the observed values of the log accounting ratios to formulate more effective portfolio strategies.     

Future Realized Return,Firm‐specific Risk and the Implied Expected Return

In this paper, I propose a novel approach to derive a firm‐specific measure of expected return. It builds on recent accounting‐based valuation models developed by Clubb (2013) and Ashton and Wang (2013). The measure is intrinsically linked to commonly used financial ratios, including book‐to‐market, (forward) earnings yield, and dividend‐to‐price, as well as growth and past returns. The empirical evidence shows that it is significantly positively associated with future realized stock returns and also significantly correlated with commonly used risk characteristics in a theoretically predictable manner. The results are likely to be of interest to practitioners and managers in making capital allocation decisions and to academics in need of proxies for firms’ discount rates and expected returns.