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.     

Glamour and Value Strategies on the Tokyo Stock Exchange

This paper evaluates the performance of glamour and value strategies and tests the extrapolation model for the Japanese equity market. In general, value stocks outperform glamour stocks by between 6 and 12 percent per annum for the five years after portfolio formation. Evidence from past, future and expected growth provides strong support for the story developed in Lakonishok, Shleifer and Vishny (1994). It is difficult to attribute the value premia to the difference, if any, in risk factors. In addition, the book-to-market premium is much closer to an arbitrage opportunity than the size premium.     

The investment value of the value premium

Value investment strategies are premised on research that value stocks outperform growth stocks. However, the research findings are dependent on the portfolio classification method that is used to sort stocks using the attributes of size and book-to-market ratios. Different stock markets contain different distributions of stocks, and in many markets, illiquidity concerns combined with a lack of investment scale, effectively create barriers to practical portfolio formations that align with the research. This study conducts a case study on one such market (Australia) and demonstrates that different methods of portfolio formation lead to different conclusions. For example, previous studies in Australia find evidence of the value premium only being present in the largest stocks, in contrast to the results from the US market. However, we find a value premium that is systematic across all size categories and generally increases inversely with size. Further, we find the well-documented size premium largely disappears once portfolios are formed that better represent feasible investment sets and once ‘penny dreadfuls’ are removed. Finally, asset pricing tests support the existence of a value premium in Australian stock returns when a more appropriate portfolio formation method is employed.     

The Value Spread

We decompose the cross-sectional variance of firms' book-to-market ratios using both a long U.S. panel and a shorter international panel. In contrast to typical aggregate time-series results, transitory cross-sectional variation in expected 15-year stock returns causes only a relatively small fraction (20 to 25 percent) of the total cross-sectional variance. The remaining dispersion can be explained by expected 15-year profitability and persistence of valuation levels. Furthermore, this fraction appears stable across time and across types of stocks. We also show that the expected return on value-minus-growth strategies is atypically high at times when their spread in book-to-market ratios is wide.     

Extreme volumes and expected stock returns: Evidence from China's stock market

We examine the relation between extreme trading volumes and expected returns for individual stocks traded on the Shanghai Stock Exchange and the Shenzhen Stock Exchange over the July 1994–December 2000 interval. Contrasted with the evidence obtained from the US data [J. Finance 56 (2001) 877], our results show that stocks experiencing extremely high (low) volumes are associated with low (high) subsequent returns. Moreover, this extreme volume–return relation significantly co-varies with security characteristics like past stock performance, firm size, and book-to-market values. In particular, stocks with extreme volumes are related to poorer performance if they are past winners, large firms, and glamour stocks than if they are past losers, small firms, and value stocks, respectively. These results are robust to both daily and weekly samples as well as stock exchange sub-samples. Although the liquidity premium hypothesis of Amihud and Mendelson [J. Financ. Econ. 17 (1986) 223] provides a partial explanation for the extreme volume–return relation, our results fit better the behavioral hypothesis of Baker and Stein [J. Financ. Mark. 7 (2004) 271].     

The other side of value: The gross profitability premium

Profitability, measured by gross profits-to-assets, has roughly the same power as book-to-market predicting the cross section of average returns. Profitable firms generate significantly higher returns than unprofitable firms, despite having significantly higher valuation ratios. Controlling for profitability also dramatically increases the performance of value strategies, especially among the largest, most liquid stocks. These results are difficult to reconcile with popular explanations of the value premium, as profitable firms are less prone to distress, have longer cash flow durations, and have lower levels of operating leverage. Controlling for gross profitability explains most earnings related anomalies and a wide range of seemingly unrelated profitable trading strategies.     

Pricing deviation,misvaluation comovement,and macroeconomic conditions

We measure an individual stock’s misvaluation based on the deviation of its price from predicted intrinsic value. Both under- and overvalued stocks identified by this misvaluation measure exhibit greater valuation uncertainty and arbitrage difficulty, and the misvaluation measure strongly predicts stock returns incremental to size, book-to-market ratio, past returns, and various return anomalies. Based on the misvaluation measure, we form a misvaluation factor and find that stock return covariances with this factor possess significant and robust return predictive power. We further show that the misvaluation factor predicts future economic conditions, providing additional insight into the real effect of systematic misvaluation in the stock market.     

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.     

Tracking down distress risk

This paper shows that exposure to aggregate distress risk is the underlying source of the premiums for the Fama-French size (SMB) and value (HML) factors. Using a unique data set of aggregate business failures of both private and public firms from 1926 to 1997, I build portfolios that track news about future firm failures. These tracking portfolios optimally hedge aggregate distress risk and earn a Capital Asset Pricing Model (CAPM) alpha of approximately −4% a year. Both HML and SMB predict changes in future failure rates. Small stocks have lower returns than large stocks and value stocks have lower returns than growth stocks when the market expects an increase in future failure rates. Finally, a two-factor model with the market and the tracking portfolio for aggregate distress as factors does as well as the Fama-French three-factor model in pricing the 25 size and book-to-market sorted portfolios.     

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.     

Multifactor Explanations of Asset Pricing Anomalies

Previous work shows that average returns on common stocks are related to firm characteristics like size, earnings/price, cash flow/price, book-to-market equity, past sales growth, long-term past return, and short-term past return. Because these patterns in average returns apparently are not explained by the CAPM, they are called anomalies. We find that, except for the continuation of short-term returns, the anomalies largely disappear in a three-factor model. Our results are consistent with rational ICAPM or APT asset pricing, but we also consider irrational pricing and data problems as possible explanations.     

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.     

Tangible and intangible information in emerging markets

Review of Quantitative Finance and Accounting - High book-to-market stocks earn higher average returns than low book-to-market stocks. This result has been verified using stock returns from the US,...     

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.     

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.     

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.     

Do zero-cost portfolios have the ability to predict economic growth? Evidence from Hong Kong, South Korea and Taiwan

In this paper we investigate the relationship between growth in future Gross Domestic Product (GDP) and Industrial Production (IDP) and the performance of SMB (small stocks minus big stocks) and HML (High book-to-market stocks minus low book-to-market stocks) portfolios for equities listed in Hong Kong, South Korea and Taiwan.We find evidence to suggest that: (a) the excess market return is positively related to future GDP or IDP growth in South Korea and Taiwan; (b) contrary to most European markets, Australia, Japan and the US, future economic growth is in general significantly negatively related to SMB in Hong Kong and South Korea; and, (c) a negative relationship between future economic growth and HML for Hong Kong. Our results cast doubt if SMB and HML portfolios are positive risk factors in the Fama and French (Fama, E. F., and French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33, 3-56) three-factor asset pricing model for Hong Kong, South Korea and Taiwan.     

Penetrating the Book-to-Market Black Box: The R&D Effect

The book-to-market (BM) phenomenon – the positive association between BM and subsequent returns – looms large among capital market enigmas. Economic theory postulates that the difference between market and book values of companies reflects their future abnormal profits. We capture these abnormal profits for a large sample of science-based companies by estimating the value of the off-balance sheet investment generating those profits – the value of R&D capital – and show empirically: (i) Firms' R&D capital is associated with their subsequent stock returns. (ii) For R&D intensive firms, this 'R&D effect' subsumes the 'book-to-market effect.' (iii) The association between R&D and subsequent returns appears to result from an extra-market risk factor inherent in R&D, rather than from stock mispricing. We thus provide an explanation for the book-to-market phenomenon of R&D companies.     

The role of future economic conditions in the cross-section of stock returns: Evidence from the US and UK

Our study investigates the explanatory power of future economic conditions on individual stock returns in the US and UK equity markets. We analyse a new trading strategy that is based on rational forecasts of future real activity. In addition, we specifically examine the performance of this trading strategy applied to two different classifications of stocks – procyclical stocks and countercyclical stocks. Our findings indicate a strong persistence in the relationship between returns on pro-cyclical stocks and the business cycle. However, such persistence is not present when moving to counter-cyclical stocks in the US and the UK. From this we suggest that US and UK equity investors who predict future real activity accurately can improve their investment profitability by longing pro-cyclical stocks when they expect future economic conditions to be above the long-run trend and shorting those stocks when future activity is anticipated to be below the steady state.     

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.