Distribución Interna

Expected returns vary over time and across asset groups. The size and value premium are widely referred to market anomalies, but the precise paradigm for which they present an anomaly is far from clear. The interpretations of the relative performance across styles remain an ongoing debate in the financial literature. Rational asset pricing theory argues that style spreads are compensation for the risk, behavioural finance links style premiums to mispricing of assets groups caused by investors’ irrational trading behaviour that are unrelated to fundamentals. This chapter contributes to the literature by investigating the relative importance of common risk factors and the firm-specific information in explaining the return differentials across equity styles. Understanding the relative importance of the underlying driving forces that affect the relative performance across asset classes is of obvious interest for portfolio managers and those who pursue style investing. This is because different driving forces would point to the different guidelines for investors to capitalise on the relative style performance to enhance their investment returns.

In this chapter, a set of equity characteristics PC, DY, MTBV and MV are considered to classify stocks into size, value and growth styles. The reason to use these firm characteristics is that prior studies suggest they explain significant cross-sectional variation in average stock returns, and hence at given each point in time they convey information about the expected returns relative to other stocks. Consistent with the general findings in the literature, significant size and value premiums are found in the U.K. stock market over the period of 1980:01-2004:12, which suggests the applicability to apply simple equity style investing strategies. Moreover, it is found that the size premium and value premiums tend to be more pronounced during recessionary periods, indicating that small size and value

119

stocks perform better as compared to large stocks and growth stocks in bad economic conditions. Such better performance of value stocks in unfavourable stages in the business cycle is also consistent with prior findings in the literature.

In response to the recent popularity to link macroeconomic effects with the observed cross-sectional variation on average stock returns, this chapter follows the methodology of Chordia and Shivakumar (2002) to examine the relative importance of common risk factors and the firm-specific information in affecting stock returns across styles. A multifactor business cycle model is employed to model the expected stock returns to the response of shocks originating in a set of parsimonious economically-motivated variables. Based on the role of the predicted risk premias and the pricing errors in the observed style premiums, it is suggested that the size premium and value premiums on firm characteristics of PC and MTBV are likely related to the unpredicted component of the business cycle model. Plausibly, U.K. size premium and value premiums on PC and MTBV are not driven by the economic exogenous forces that affect stock returns over time within the business cycle. Rather, they should be related to the idiosyncratic information unrelated to business cycles that may cause investors to underreact when doing trading, which is best described in behavioural finance. However, the value premium on characteristic DY seems to represent compensation for bearing business cycle risks. The divergent returns for stocks sorted on DY is mainly driven by the predicted component from the business cycle model, and the outperformance of value stocks disappear after controlling the predicted risk premias.

The finding of different sources driving the divergent stock returns across styles characterized by PC, MTBV and DY is intriguing. The characteristic variables under consideration are price-related ratios and are associated with the variation on average stock returns. Such

120

firm characteristics are correlated with business cycles (Fama and French (1989)), or are able to forecast economic activity (Estrella and Hardouvelis (1991), Ang et al. (2004)). If the multifactor business cycle model is empirically well specified, rational asset pricing argues that the evidence of style premiums would suggest that the underlying characteristics proxy for risk factors or information of mispricing. But the existence of style premiums on firm characteristics would still be consistent with traditional finance theory should the underlying characteristics associated with higher average returns are cross- sectionally correlated with risk factors. Under this condition, the style premiums still simply reflect the compensation for risk.

By examining the contemporaneous relations between characteristics, common risk factors and the mispricing from the business cycle model, This chapter finds that the pricing errors are cross-sectionally captured by exposures to other common risk factors such CAPM betas or loadings on market factor or SMB of Fama and French (1993) three-factor model. Equity characteristics of PC, MTBV and MV demonstrate no incremental explanatory ability in such mispricing. Hence the null hypothesis that MV, PC and MTBV do not proxy for risk factors or have no cross-sectional correlations with the risk factor loadings can be rejected. Overall, the empirical findings in this chapter tend to support the rational risk-based argument that equity style premiums reflect compensation for risk, although such risk may or may not directly business cycle related.

The findings in this chapter shed further light on the understanding of equity style returns and provide guidance for portfolio management in the investment practice. Investors should understand while different firm characteristics can be considered to identify value and growth stocks, the underlying mechanisms of the value premiums may be different. Although such premiums all reflect compensation of risk, stocks sharing some specific characteristics may be more vulnerable

121

to the direct business cycle risks, while others are less directly affected by macroeconomic conditions. To capitalize on the relative style returns, active managers need to identify the underlying driving forces that determine the relative style performance. More importantly, managers need to capture the mechanisms through which those underlying forces work. In the context of style investing, if portfolios are based on characteristics that proxy for macroeconomic risks, arguably active style management should aim to timing the business cycle. In contrast, for asset allocation based on characteristics that are less directly related to the business cycle fluctuations, style management should aim to pick up stock groups that have information relate to investors’ irrational behaviour in their trading process. The divergence of equity style returns evolves all the time; there is no single style or mix of styles dominating under all market states. Since timing business cycles is difficult, active portfolio management naturally aim to identify stocks that have high average returns and commove together. Perhaps due to this reason, recent studies in finance find that institutional investors follow distinct investment styles (e.g. Brown and Goetzmann (1997), Fung and Hsieh (1997), Chan et al. (2002)). It will be interesting to examine whether astute investors can profit from the information of equity style cycles as represented by current popular investment styles, which provides motivation for the research in Chapter 4.

122