Research and Development Activity and Expected Returns in the United Kingdom

Fama and French (1992) show that size and book-to-price dominateCAPM beta and other variables such as the price-earnings ratioand dividend yield in explaining the cross-section of US stockreturns. Comparable evidence for the UK points to a book-to-priceeffect, but not a size effect (Chan and Chui, 1996; Strong andXu, 1997). In this paper, our first contribution is to showthat a measure of research and development (RD) helps explaincross-sectional variation in UK stock returns. Our cross-sectionalresults on the association between stock returns and RD areconsistent with recent US evidence reported by Lev and Sougiannis(1996, 1999) and Chan, Lakonishok and Sougiannis (2001).Famaand French (1993, 1995, 1996) also show that a three-factormodel captures a high proportion of the time series variationin portfolio returns, again for the US. Our second contributionis to show, for the UK, that a modification to the three-factormodel to take account of RD activity can significantly enhancethe explanatory power of the three-factor model. We show that,as a practical matter, estimated risk premia based on the modifiedthree-factor model can differ considerably from risk premiaestimated using the CAPM or the three-factor model. In particular,risk premia for industries in which few firms undertake RD activitiestend to be over-estimated.     

Evaluating asset pricing models in the Korean stock market

This paper evaluates and compares asset pricing models in the Korean stock market. The asset pricing models considered are the CAPM, APT-motivated models, the Consumption-based CAPM, Intertemporal CAPM-motivated models, and the Jagannathan and Wang conditional CAPM model. By using various test portfolios as well as individual stocks, we conduct time-series tests and cross-sectional regression tests based on individual t-tests, the joint F-tests, the Hansen and Jagannathan (1997) distance, and R-squares. Overall, the Fama and French (1993) five-factor model performs most satisfactorily among the asset pricing models considered in explaining the intertemporal and cross-sectional behavior of stock returns in Korea. The Fama and French (1993) three-factor model, the Chen et al. (2010) three-factor model, and the Campbell (1996) model are the next. The results indicate that the two bond portfolios, term spread and default spread, play an important role in explaining stock returns in Korea.     

Asset Pricing with Conditioning Information: A New Test

This paper presents a new test of conditional versions of the Sharpe-Lintner CAPM, the Jagannathan and Wang (1996) extension of the CAPM, and the Fama and French (1993) three-factor model. The test is based on a general nonparametric methodology that avoids functional form misspecification of betas, risk premia, and the stochastic discount factor. Our results provide a novel view of empirical performance of these models. In particular, we find that a nonparametric version of the Fama and French model performs well, even when challenged by momentum portfolios.     

CAPM, Higher Co‐moment and Factor Models of UK Stock Returns

In this paper we examine the variables that explain the cross‐section of UK stock returns. Previous studies have found that the CAPM beta has moderate or even insignificant explanatory power once the Fama French factors are included. However, we control for different realised risk premia in up and down markets by using the same methodology as Pettengill, Sundaram and Mathur (1995). Unlike previous work, we find that beta is highly significant in explaining the cross‐section of UK stock returns and more importantly remains significant even when the Fama French factors are included in the cross‐sectional regressions. We also investigate whether higher co‐moments (co‐skewness and co‐kurtosis) have any explanatory power but find that empirical support is weaker.     

Asset pricing and energy consumption risk

This paper proposes energy consumption in the US as a new measure for the consumption capital asset pricing model. We find that (i) industrial energy growth produces reasonable values for the relative risk aversion coefficient and the implied risk-free rate; (ii) compared to alternative consumption measures, industrial energy performs well in explaining the cross-sectional variation in stock returns with the lowest implied risk aversion and pricing errors; (iii) the industrial energy consumption risk model performs equally well as the Fama–French three-factor model in the cross-sectional asset pricing tests; and (iv) total energy consumption risk is priced in the presence of the Fama–French factor risks.     

Estimation of expected return: CAPM vs. Fama and French

Most practitioners favour a one-factor model (CAPM) when estimating expected return for an individual stock. For estimation of portfolio returns, academics recommend the Fama and French three-factor model. The main objective of this paper is to compare the performance of these two models for individual stocks. First, estimates for individual stock returns based on CAPM are obtained using different time frames, data frequencies, and indexes. It is found that 5 years of monthly data and an equal-weighted index, as opposed to the commonly recommended value-weighted index, provide the best estimate. However, performance of the model is very poor; it explains on average 3% of differences in returns. Then, estimates for individual stock returns are obtained based on the Fama and French model using 5 years of monthly data. This model, however, does not do much better; independent of the index used, it explains on average 5% of differences in returns. These results therefore bring into question the use of either model for estimation of individual expected stock returns.     

Do relative leverage and relative distress really explain size and book-to-market anomalies?

In a capital asset pricing model (CAPM) framework, Ferguson and Shockley [2003. Equilibrium “anomalies”. Journal of Finance 58, 2549–2580] propose two factors constructed on relative leverage and relative distress, and show that the two factors subsume Fama and French's [1993. Common risk factors in the returns on stocks and bonds. Journal of Financial Economics 33, 3–56] factors constructed on size and book-to-market (BM) in explaining the cross-sectional average returns of the 25 size-BM portfolios. Based on tests on individual securities, we find that all factors fail to fully explain the common asset-pricing anomalies. In the spirit of Merton's [1973. An intertemporal capital asset pricing model. Econometrica 41, 867–887] intertemporal CAPM, we propose an augmented five-factor model, which incorporates Ferguson and Shockley's [2003. Equilibrium “anomalies”. Journal of Finance 58, 2549–2580] factors into the Fama–French three-factor model. The empirical results show that a simple conditional version of the augmented model is able to explain most well-known asset-pricing anomalies.     

It takes a model to beat a model: Volatility bounds

Models like the CAPM and Fama–French three-factor models are commonly used as benchmarks for calculating cost of capital and evaluating portfolio performance, despite the empirical evidence to reject them. For many practical purposes, “it takes a model to beat a model.” In this paper we derive restrictions on models that could “beat” a bench-mark model but might still be misspecified. In these “takes-a-model-to-beat-a-model” (TMBM) bounds, model A beats model B if model A's quadratic form of pricing errors is smaller. The bounds generalize the Hansen–Jagannathan bound and distance measure. We use the TMBM bounds to evaluate various linear factor models and consumption-based models. The failure of the power utility model is much less extreme when it is compared with the CAPM and Fama–French model. For reasonable utility curvature, the Ferson–Constantinides model and Epstein–Zin model perform best among the consumption-based models, beating the model of Campbell and Cochrane, in which model the value of the persistence parameter that matches the time-series properties of aggregate stock market returns seems too low for cross-sectional asset pricing.     

Explaining the Cross‐Section of Stock Returns in Japan: Factors or Characteristics?

Japanese stock returns are even more closely related to their book-to-market ratios than are their U.S. counterparts, and thus provide a good setting for testing whether the return premia associated with these characteristics arise because the characteristics are proxies for covariance with priced factors. Our tests, which replicate the Daniel and Titman (1997) tests on a Japanese sample, reject the Fama and French (1993) three-factor model, but fail to reject the characteristic model.     

Long-Run Performance Persistence of Investment Funds

This article analyzes the long-run persistence of returns and risk of investment in the assets of money, bound, and stock funds recorded on the Polish market in 2000–12. Portfolios of safe, hybrid, and stock classes are formed on the basis of tested funds. The persistence of returns and the Sharpe ratio are investigated in rolled five-year sub-periods, with one year step. Also, persistence in performance is assessed using classic CAPM and Fama and French models, which allow for evaluating management skills. We find the occurrence of the Sharpe ratio long-run persistence of money and bound funds. The study does not explicitly show long-run persistence in hybrid and stock fund portfolios. The CAPM and Fama and French models simulations of returns on stock and hybrid funds indicate varying management skills during five-year periods.     

Foreign exchange volatility and stock returns

This paper explores whether foreign exchange volatility is a priced factor in the US stock market. Our investigation is motivated by a number of empirical as well as theoretical considerations. Empirically, Menkhoff et al. (2012) find that foreign exchange volatility is a pervasive factor across a variety of test assets. Theoretically, Shapiro (1974), Dumas (1978), and Levi (1990) imply that foreign exchange volatility can influence firms’ cash flow volatility therefore the discount rate. In terms of empirical implementation, we employ the cross-sectional regression methodology of Fama and MacBeth (1973) as well as the time-series regression approach of Fama and French (1996). For robustness, we also use the mimicking portfolio approach of Fama and French (1993). We find that foreign exchange volatility has no power to explain either the time-series or the cross-section of stock returns, which calls for more research on foreign exchange risk. Bartov et al. (1996) and Adrian and Rosenberg (2008) suggest an alternative and maybe promising direction.     

A conditional multifactor analysis of return momentum

Although the Fama–French three-factor model captures most CAPM anomalies, it still fails to explain return momentum. This paper shows that the incorporation of conditioning information into an asset-pricing model is one way to capture return momentum. Results from the conditional regression with linear exposures in the instruments show clear evidence that both small minus big (SMB) and high minus low (HML) risks are time varying and that momentum and reversal return patterns have different time-varying risk characteristics. The conditional Fama–French regression model seems, however, to remain misspecified. Conversely, when the linearity assumption is relaxed and cross-sectional restrictions are imposed, the conditional pricing model appears to capture both short-term momentum and long-term reversal.     

中国股票市场流动性风险溢价研究

本文在对Fama三因素模型和LACAPM模型进行改进的基础上,实证研究了中国股票市场的流动性风险溢价、规模效应以及价值效应。实证结果发现,改进的FAMA三因素模型能够比CAPM更好地解释价值效应,但却不能解释规模效应和流动性风险溢价现象;而改进的LACAPM在解释市场异象上的有效性则明显优于其他定价模型。     

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.     

Positive return premia in Japan

This paper examines Jensen's [J. Finance, 1968, 23, 389–416] alphas and the time-varying return premia unexplained by standard risk factors in Japan and presents several new findings. First, in contrast to the US experience, positive alphas remain after Fama and French's three factors are applied to excess stock returns in Japan. Second, positive alphas remain in Japan, even if the Fama–French three factors combined with momentum and reversal factors are applied to excess stock returns. Third, the positive return premia unexplained by these five factors bear little relation to the dynamics of the Japanese macroeconomy. Fourth, the time series evolution of the positive return premia indicates autonomous dynamics with at least three regimes. Fifth, we can predict or time the acquisition of the positive return premia for small-size portfolios in Japan by observing the direction and effect of the return premia of large-size portfolios and high-book equity to market equity (BE/ME) portfolios. Finally, application of the self-exciting threshold autoregressive (SETAR) model shows that the size effects are stronger than the BE/ME effects in Japan, given that the return premia from small-size portfolios in the SETAR model are bounded by positive thresholds, while the return premia from high-BE/ME portfolios are bounded by negative thresholds.     

An inquiry into the economic fundamentals of the Fama and French equity factors

This study investigates the economic underpinnings of the Fama and French three-factor (FF3) model. We evaluate the impact of surprises in 23 different types of macroeconomic announcements on stock returns in the framework of the CAPM and the FF3 model. The relative merit of the FF3 model is demonstrated whenever macroeconomic surprises have a smaller impact on the returns within an FF3 model versus their impact within the CAPM. In general, there is strong evidence to suggest that the FF3 model outperforms the CAPM. The relative merit of the FF3 model is highlighted by its ability to capture information related to Personal Consumption, Retail Sales, CPI, PPI, Factory Orders, Leading Indicators, Construction Spending, Housing Starts, and New Home Sales. An attribution analysis of the relative performance of SMB and HML equity factors indicate that both factors, in isolation, equally account for macroeconomic surprises. Lastly, there is evidence that the FF3 model can be marginally improved by incorporating credit variables.     

Technical indicators and cross-sectional expected returns

This study shows that 14 widely documented technical indicators explain cross-sectional stock returns. These indicators have lower estimation errors than the three-factor Fama–French and historical mean models. The long-short portfolios based on the cross-sectional technical signals generate substantial excess returns. These remain consistent after controlling for well-known cross-sectional return determinants, including momentum, size, book-to-market ratio, investment, and profitability. Our findings suggest that technical indicators play an important role in determining variation in cross-sectional returns.     

The UK Equity Premium: 1901–2004

Abstract:  This paper examines the UK equity premium over more than a century using dividend growth to estimate expectations of capital gains employing the approach of Fama and French (2002) . Over recent decades estimated equity premia implied by dividend growth have been much lower than that produced by average stock returns for the UK market as a whole; a finding corroborated by all economic sub-sectors. The empirical analysis suggests this is primarily due to a declining discount rate, during the latter part of the 20th century, which would rationally stimulate unanticipated equity price rises during this period. Thus, I conclude that historical stock returns over recent decades have been above investors' expectations.     

A liquidity-augmented capital asset pricing model

Using a new measure of liquidity, this paper documents a significant liquidity premium robust to the CAPM and the Fama–French three-factor model and shows that liquidity is an important source of priced risk. A two-factor (market and liquidity) model well explains the cross-section of stock returns, describing the liquidity premium, subsuming documented anomalies associated with size, long-term contrarian investment, and fundamental (cashflow, earnings, and dividend) to price ratios. In particular, the two-factor model accounts for the book-to-market effect, which the Fama–French three-factor model fails to explain.     

Industry Cost of Equity Capital: UK Evidence

Abstract:  This paper explores the industry cost of equity capital for the UK. We replicate the Fama and French (1997) US analysis for UK industries, but additionally investigate the industry cost of equity capital obtained from a conditional CAPM, the Cahart (1997) four factor model, and the Al-Horani, Pope and Stark (2003) R&D model. In line with the Fama-French US results, the out of sample performance of all the models is disappointing Whilst the FF3F model has a somewhat higher explanatory power than the CAPM in terms of explaining past returns, the SMB and HML factor slopes show considerable variability through time. However, all our models of the cost of equity capital in the UK outperform a simple 'beta one' model, a result that has implications for the regulatory process. There is also some evidence to suggest that a conditional CAPM may be of interest to regulators. The new R&D model of Al-Horani et al. clearly has potential, in that over the limited period for which data is available it yields return errors not dissimilar to those found under the FF3F model, but exhibits slope coefficients on the fourth R&D factor that seem to be relatively stable.