Relations Between Stock Returns and Fundamental Variables: Evidence from a Segmented Market

This study examines relations between stock returns and potential explanatory factors in Korea, an important and segmented emerging market. Our results show that Korean stock returns in general and returns on stocks listed in Section 1 in particular are significantly positively related to book-to-market, sales-price, and debt-equity ratios, but not significantly related to market value of equity. Returns on stocks listed in Section 2 are, however, negatively related to market value of equity and not significantly related to the other three variables. Among the variables investigated by us, book-to-market ratio has the greatest explanatory power for stock returns and it indicates superior returns for value stocks. Our findings strengthen the international evidence of the role of book-to-market ratio in explaining stock returns by demonstrating its significance even in the segmented Korean market.     

Evidence on the Characteristics of Cross Sectional Variation in Stock Returns

Firm sizes and book-to-market ratios are both highly correlated with the average returns of common stocks. Fama and French (1993) argue that the association between these characteristics and returns arise because the characteristics are proxies for nondiversifiable factor risk. In contrast, the evidence in this article indicates that the return premia on small capitalization and high book-to-market stocks does not arise because of the comovements of these stocks with pervasive factors. It is the characteristics rather than the covariance structure of returns that appear to explain the cross-sectional variation in stock returns.     

Risk,Mispricing, and Value Investing

We evaluate the stock return performance of a modified version of the book-to-market strategy and its implications for market efficiency. If the previously documented superior stock return of the book-to-market strategy represents mispricing, its performance should be improved by excluding fairly valued firms with extreme book-to-market ratios. To attain this, we classify stocks as value or glamour on book-to-market ratios and accounting accruals jointly. This joint classification is likely to exclude stocks with extreme book-to-market ratios due to mismeasured accounting book values reflecting limitations underlying the accounting system. Using both 12-month buy-and-hold returns and earnings announcement returns, our results show that this joint classification generates substantially higher portfolio returns in the post-portfolio-formation year than the book-to-market classification alone with no evidence of increased risk. In addition, this superior stock return performance is more pronounced among firms held primarily by small (unsophisticated) investors and followed less closely by market participants (stock price <$10). Finally, and most importantly, financial analysts are overly optimistic (pessimistic) about earnings of glamour (value) stock, and for a subset of firms identified as overvalued by our strategy, the earnings announcement raw return, as well as abnormal return, is negative. These last results are particularly important because it is hard to envision a model consistent with rational investors holding risky stocks with predictable negative raw returns for a long period of time rather than holding fT-bills and with financial analysts systematically overestimating the earnings of these stocks while underestimating earnings of stocks that outperform the stock market.     

The cross-section and time series of stock and bond returns

Bond factors which predict future U.S. economic activity at business cycle horizons are priced in the cross-section of U.S. stock returns. High book-to-market stocks have larger exposures to these bond factors than low book-to-market stocks, because their cash flows are more sensitive to the business cycle. Because of this new nexus between stock and bond markets, a parsimonious three-factor dynamic no-arbitrage model can be used to jointly price book-to-market-sorted portfolios of stocks and maturity-sorted bond portfolios, while reproducing the time-series variation in expected bond returns. The business cycle itself is a priced state variable in stock and bond markets.     

Value versus Growth: The International Evidence

Value stocks have higher returns than growth stocks in markets around the world. For the period 1975 through 1995, the difference between the average returns on global portfolios of high and low book-to-market stocks is 7.68 percent per year, and value stocks outperform growth stocks in twelve of thirteen major markets. An international capital asset pricing model cannot explain the value premium, but a two-factor model that includes a risk factor for relative distress captures the value premium in international returns.     

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.     

Higher-Order Systematic Comoments and Asset Pricing: New Evidence

We provide evidence supporting Rubinstein's (1973) model that if returns are not normal, measuring risk requires more than just measuring covariance. Higher-order systematic comoments should be important to risk-averse investors who are concerned about the extreme outcomes of their investments. Our paper shows that the Fama-French factors [SMB (return on small stocks less the return on big stocks), HML (return on high book-to-market stocks less the return on low book-to-market stocks)] as well as the momentum and market liquidity factors can be explained by the higher-order systematic comoments, and it lends support to the traditional covariance risk-based theory without having to resort to behavior assumptions.     

Institutional investors,intangible information,and the book-to-market effect

This paper establishes a robust link between the trading behavior of institutions and the book-to-market effect. Building on work by Daniel and Titman (2006), who argue that the book-to-market effect is driven by the reversal of intangible returns, I find that institutions tend to buy (sell) shares in response to positive (negative) intangible information and that the reversal of the intangible return is most pronounced among stocks for which a large proportion of active institutions trade in the direction of intangible information. Furthermore, the book-to-market effect is large and significant in stocks with intense past institutional trading but nonexistent in stocks with moderate institutional trading. This influence of institutional trading on the book-to-market effect is distinct from that of firm size. These results are consistent with the view that the tendency of institutions to trade in the direction of intangible information exacerbates price overreaction, thereby contributing to the value premium.     

Why does book-to-market value of equity forecast cross-section stock returns?

In this paper, we derive a model of book-to-market value of equity based on the present value model and estimate it using panel data on individual stocks. We explicitly include in the model all the determinants of book-to-market except the firm-specific discount rate, which we capture using fixed individual effects in the panel data model. The model is particularly successful, explaining nearly 90% of the time series and cross-section variation in the ratio of book-to-market value of equity. Moreover, the estimated firm-specific fixed effects are more successful than the most recent book-to-market value of equity in forecasting subsequent returns. This is consistent with an efficient market in which book-to-market is a proxy for risk.     

Do Industries Explain Momentum?

This paper documents a strong and prevalent momentum effect in industry components of stock returns which accounts for much of the individual stock momentum anomaly. Specifically, momentum investment strategies, which buy past winning stocks and sell past losing stocks, are significantly less profitable once we control for industry momentum. By contrast, industry momentum investment strategies, which buy stocks from past winning industries and sell stocks from past losing industries, appear highly profitable, even after controlling for size, book-to-market equity, individual stock momentum, the cross-sectional dispersion in mean returns, and potential microstructure influences.     

Is the Value Spread a Good Predictor of Stock Returns? UK Evidence

Abstract:  This paper explores the predictive ability of the value spread in the UK. I replicate the US analysis of Liu and Zhang (2007) using UK data. In addition, I extend their work by exploring the predictive ability of the book-to-market, market-to-book and value spread on other size and value investment strategies, namely: large-caps only; small-caps minus large-caps (SML); value stocks only; growth stocks only; value stocks minus growth stocks (VMG) and a market portfolio that includes all stocks. The results are consistent with Liu and Zhang (2007) on the value spread. The value spread shows no predictive power for portfolio returns. Therefore, I show that the predictive power of book-to-market and market-to-book spreads depend on the portfolio formation strategies and the relative proportion of small-cap, large-cap, value and growth stocks in the portfolio.     

The information content of stock split announcements: Do options matter?

We provide a new test of the informational efficiency of trading in stock options in the context of stock split announcements. These announcements tend to be associated with positive abnormal returns. Our traditional event study results show abnormal returns that are significantly lower for optioned than non-optioned stocks, whether traded on the NYSE, Amex, or Nasdaq. After controlling for market returns, capitalization, book-to-market ratio, and trading volume, we find that the abnormal returns are significantly lower for NYSE/Amex optioned than non-optioned stocks. Although the results for Nasdaq stocks are not as clear, the overall effects tend to be lower after optioning. These findings are consistent with the hypothesis that the prices of optioned stocks embody more information, diminishing the impact of the stock split announcement. They provide new evidence of the beneficial effects of options on their underlying stocks.     

Are extreme returns priced in the stock market? European evidence

This paper revisits some recently found evidence in the literature on the cross-section of stock returns for a carefully constructed dataset of euro area stocks. First, we confirm recent results for US data and find evidence of a negative cross-sectional relation between extreme positive returns and average returns after controlling for characteristics such as momentum, book-to-market, size, liquidity and short term return reversal. We argue that this is the case because these stocks have lottery-like characteristics, which is attractive to certain investors. Also, these stocks tend to be very volatile so that arbitrageurs are discouraged from correcting potential mispricing. As a consequence, these stocks are often overpriced and hence face lower expected returns. Second, when we control for extreme returns, the recently found negative relationship between idiosyncratic risk and future returns is less robust. In our models, after adding maximum returns, the relationship is insignificant and sometimes even positive. We also find that idiosyncratic skewness and coskewness play an important role for asset pricing, as predicted by several theoretical models.     

On the relationship between concentration of prospect theory/mental accounting investors,cointegration, and momentum

We examine the role of cointegration between stock prices and their estimated fundamental values in return momentum. We find that the positive relationship between capital gains overhang and future stock returns in Grinblatt and Han (2005) is significantly stronger among the “non-cointegrated” group of stocks as compared with the “cointegrated” group of stocks. Further, for the cointegrated stocks, the slower the speed of adjustment to the cointegrating equilibrium, the greater (smaller) is the future return of stocks with unrealized capital gains (losses). These findings are robust to various firm characteristics including firm size, book-to-market ratio, past returns, idiosyncratic volatility, dispersion in analysts’ earnings forecasts, turnover, individual investor ownership, and industry returns.     

Illiquidity Premium in the MILA

This article analyzes the illiquidity premium in the MILA. Using seven proxies for illiquidity, we find a positive and significant illiquidity premium for our sample. A microstructure bias-free portfolio weighting based on past returns is critical in our finding of an illiquidity premium, which is robust to several methodological changes in our portfolio simulations. We also document that the premium is present only in small and high book-to-market stocks. Nonetheless, when we control for size and distress effects, the difference and significance in risk-adjusted returns between portfolios of high and low illiquidity stocks remains.     

Momentum and Autocorrelation in Stock Returns

This article studies momentum in stock returns, focusing onthe role of industry, size, and book-to-market (B/M) factors.Size and B/M portfolios exhibit momentum as strong as that inindividual stocks and industries. The size and B/M portfoliosare well diversified, so momentum cannot be attributed to firm-or industry-specific returns. Further, industry, size, and B/Mportfolios are negatively autocorrelated and cross-seriallycorrelated over intermediate horizons. The evidence suggeststhat stocks covary "too strongly" with each other. I argue thatexcess covariance, not underreaction, explains momentum in theportfolios.     

Asset Growth and the Cross-Section of Stock Returns

We test for firm-level asset investment effects in returns by examining the cross-sectional relation between firm asset growth and subsequent stock returns. Asset growth rates are strong predictors of future abnormal returns. Asset growth retains its forecasting ability even on large capitalization stocks. When we compare asset growth rates with the previously documented determinants of the cross-section of returns (i.e., book-to-market ratios, firm capitalization, lagged returns, accruals, and other growth measures), we find that a firm's annual asset growth rate emerges as an economically and statistically significant predictor of the cross-section of U.S. stock returns.     

An International Dynamic Asset Pricing Model

We examine the ability of a dynamic asset-pricing model to explain the returns on G7-country stock market indices. We extend Campbell's (1996) asset-pricing model to investigate international equity returns. We also utilize and evaluate recent evidence on the predictability of stock returns. We find some evidence for the role of hedging demands in explaining stock returns and compare the predictions of the dynamic model to those from the static CAPM. Both models fail in their predictions of average returns on portfolios of high book-to-market stocks across countries.     

Predicting stock returns

This paper studies whether incorporating business cycle predictors benefits a real time optimizing investor who must allocate funds across 3,123 NYSE-AMEX stocks and cash. Realized returns are positive when adjusted by the Fama-French and momentum factors as well as by the size, book-to-market, and past return characteristics. The investor optimally holds small-cap, growth, and momentum stocks and loads less (more) heavily on momentum (small-cap) stocks during recessions. Returns on individual stocks are predictable out-of-sample due to alpha variation, whereas the equity premium predictability, the major focus of previous work, is questionable.     

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.