«Equity Style Investing RONG, WU How to cite: Equity Style Investing, Durham theses, Durham University. RONG, WU (2013) Available at Durham E-Theses ...»
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 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 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 crosssectionally 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 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.
4.1 Introduction Recent studies in finance suggest that institutional investors follow distinct investment styles (e.g. Brown and Goetzmann (1997); Fung and Hsieh (1997); Chan et al. (2002)). The heightened attention of investment style is driven by several motives. Armott et al. (1989) argue that investment style dominates equity return patterns in the investment process. Money manager’s philosophy of selecting stocks trumps individual stock selection in determining overall performance.
Brinson et al. (1986) propose that the decision of asset allocation accounts for about 90% of the variations in large pension funds.
Similarly, Hansen (1992) argues that different investment styles account for approximately 60% of the performance over short and medium term. More specifically, Sharpe (1992) shows that over 90% of the superior performance of a typical equity investment fund can be attributable to its investment style, only less than 10% is due to the individual characteristics of the specific securities hold. Since assets in a typical style category share common characteristics that are generally related to the expected returns, investors are motivated to implement style investing to simplify the problem of their investment choice.
Considerable evidence suggests that both individual and institutional investors pursue style investing in stock markets. Kumar (2009) shows that U.S. individual investors demonstrate style-switching trading behaviour based on relative style performance, and such style trading behaviour is unrelated to fundamental factors or the expected stock returns. Style investing is arguably more attractive to pool investing such as investment fund mandates because agents generally manage large amount of funds but face the maze of investment opportunities given an overwhelming amount of assets available in the marketplace. Indeed, institutional investors such as pension and endowment funds generally accept substantial responsibilities and assume significant liabilities for their beneficiaries. These agents act as fiduciaries and tend to follow specific investment philosophy based on the contract that leads to a unique process of building portfolios.
Style-based investing is attractive to such investors because it helps organise and simplify their portfolio construction process. By chasing specific investment style to make dynamic asset allocation decision at the style level rather than individual stock level, manager’s investment practice becomes less intimidating (Barberis and Shleifer (2003)).
Perhaps for this reason, popular styles like value versus growth and small versus large are widely followed in the global equity markets. On the other hand, the concept of investment style has also been utilized to help fund sponsors evaluate managers’ area of expertise and help them to be more knowledgeable about how to allocate assets across funds with different investment styles. Hence, paralleling with the popularity of equity style investing and the growth of institutional investors, many style benchmarks are created to help evaluate money manager’s performance with dedicated investment styles. Today, leading financial markets have witnessed the popularity of Exchange Traded Fund (ETF) based on equity styles and the introduction of style index futures contract that offer low cost and high liquidity to serve the investment community.
The time-varying nature of equity style performance is well recognised in the equity markets. For example, U.S. small size stocks earn significant larger returns during 1971-80 than between 1981-90 (Ibboston and Sinquefeld (1995)), and growth stocks perform exceptionally well but value stocks do extremely poorly despite good earnings news during 1998-99 (Chen and De Bondt (2004)). The divergence of equity style returns evolves all the time, there is no single style or mix of styles dominating under all market conditions.
Such time-varying equity style return dynamics attracts investors to consider the benefit of tactical style rotations in the portfolio performance enhancement. Arguably, if style cycles exist and can last for a long duration, there is potential success for systematic tactical asset allocation strategies once investors are able to identify the turning points of the style cycles. Birch (1995) demonstrates that in principle how perfect tactic asset allocation could be implemented based on style cycle information. Other studies like Beinstein (1995), Fan (1995), Fisher et al. (1995), Sorensen and Lazzara (1995), Kao and Shumaker (1999), Levis and Liodakis (1999), Asness et al. (2000) and Lucas et al. (2002) explore the benefit of style rotations. However, as Chen and De Bondt (2004) point out, by and large these researches do not detail the specific trading strategies derived from the information of style cycles. The implementation of successful style rotation strategies requires that investors are able to correctly predict the potential style trends in the future. Given the yet not fully clear economic forces that underlie the divergent style returns, forecastbased active timing models often have difficulty in doing a good job.
Previous studies such as Henriksson (1984), Ferson and Schadt (1996), and Chan et al. (2002) suggest that active money managers have neither market timing nor style timing ability.
Style momentum investing is a style-level positive feedback trading strategy based on the information of investment style evolution to buy winner styles and to sell loser styles following the past relative style performance. Unlike forecast-based timing models, the trading signal is determined by the relative style performance over the previous period of time. The strategy is adaptive in nature because the trading signal is based on information that is readily available at the end of each time period instead of a forecast procedure.
Style momentum strategy in particularly appeals to pool investing such as investment fund mandates with large amount of assets under management. As mentioned previously, managers understand the importance of investment style and are motivated to implement style investing to simplify their asset allocation problems. It is recognised that although managers have good reason to explicitly designate style exposures for their fund products, they face strong incentives to chase current in-favour investment styles to attract fund inflows for better compensation. Although some studies such as Davis (2001) find that mutual funds are unable to generate persistent abnormal returns, as Chen and De Bondt (2004) observe empirical evidence suggests a positive linkage between fund performance and money flows. For example, Sirri and Tufano (1998) and Jain and Wu (2000) document that mutual fund investors base their purchase decisions on the underlying fund’s prior performance information. Equity mutual funds that show continued historical good performance attract more money into the funds. Cooper et al. (2005) argue that some funds even change their names to chase current in-favour investment styles, and such name changes appear to stop the money outflow. Other studies such as Choe et al. (1999) and Froot et al. (2001) also show that foreign institutional investors tend to buy into countries with good recent stock market performance. It is found that manager’s incentive to chase in-favour styles can result in what is called the style drifts in the investment practice. DiBartolomeo and Witkowski (1997) argue that during the 1990s many equity funds in the U.S. markets are mislabelled because their return patterns do not match what would have been suggested by the investment styles described in their fund prospectus. The popularity of style investing and investors’ style chasing behaviour is perhaps best described by Barberis and Shleifer (2003) in the behavioural finance framework.