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.     

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.     

Equilibrium "Anomalies"

Many empirical “anomalies” are actually consistent with the single beta capital asset pricing model if the empiricist utilizes an equity‐only proxy for the true market portfolio. Equity betas estimated against this particular inefficient proxy will be understated, with the error increasing with the firm's leverage. Thus, firm‐specific variables that correlate with leverage (such as book‐to‐market and size) will appear to explain returns after controlling for proxy beta simply because they capture the missing beta risk. Loadings on portfolios formed on relative leverage and relative distress completely subsume the powers of the Fama and French (1993) returns to small minus big market capitalization (SMB) portfolios and returns to high minus low book‐to‐market (HML) portfolios factors in explaining cross‐sectional returns.     

What do the Fama–French factors add to C-CAPM?

This study extends standard C-CAPM by including two additional factors related to firm size (SMB) and book-to-market value ratio (HML) — the Fama–French factors. C-CAPM is least able to price firms with low book-to-market ratios. The explanation of these returns, as well as the returns on the SMB and HML portfolios, is significantly improved by the inclusion of the HML factor. The component of the risk premia explained by consumption varies across size. We suggest that a possible explanation for the role of HML is its association with the investment growth prospects of firms.     

Risk adjustment and momentum sources

We show that the conventional procedure of risk adjustment by running full-sample time-series Fama-French three-factor regressions is not appropriate for momentum portfolios because the procedure fails to allow for the systematic dynamics of momentum portfolio factor loadings. We propose a simple procedure to adjust risks associated with the Fama-French three factors for momentum portfolios. Using our proposed method, the Fama-French three factors can explain approximately 40% of momentum profits generated by individual stocks and nearly all of momentum returns from style portfolios.     

On the differences in measuring SMB and HML in the UK – Do they matter?

The Fama–French (FF) three factor model expands the capital asset pricing model (CAPM) to include two additional factors to the market factor – SMB, employed to capture a firm size effect in returns and HML employed to capture book-to-market effects in returns. In the UK, different researchers use different ways of calculating SMB and HML in the context of empirical applications of the three factor model, or extensions of it, perhaps because they believe the differences in the construction of the SMB and HML factors to be relatively unimportant from an empirical standpoint. We investigate whether indeed factor construction methods are unimportant. Our conclusion is that they do matter.     

Do the Fama–French Factors Proxy for Innovations in Predictive Variables?

The Fama–French factors HML and SMB are correlated with innovations in variables that describe investment opportunities. A model that includes shocks to the aggregate dividend yield and term spread, default spread, and one‐month Treasury‐bill yield explains the cross section of average returns better than the Fama–French model. When loadings on the innovations in the predictive variables are present in the model, loadings on HML and SMB lose their explanatory power for the cross section of returns. The results are consistent with an ICAPM explanation for the empirical success of the Fama–French portfolios.     

In Search of Distress Risk

This paper explores the determinants of corporate failure and the pricing of financially distressed stocks whose failure probability, estimated from a dynamic logit model using accounting and market variables, is high. Since 1981, financially distressed stocks have delivered anomalously low returns. They have lower returns but much higher standard deviations, market betas, and loadings on value and small‐cap risk factors than stocks with low failure risk. These patterns are more pronounced for stocks with possible informational or arbitrage‐related frictions. They are inconsistent with the conjecture that the value and size effects are compensation for the risk of financial distress.     

An alternative measure of the “world market portfolio”: Determinants, efficiency, and information content

The world market portfolio plays an important role in international asset pricing, but is unobservable in practice. We first propose a framework for constructing a market proxy that corresponds to the “market portfolio” of financial theory. We then construct this proxy, analyze its determinants and test its efficiency and explanatory power over the period 1975-2007 with respect to the return generating processes of a broad asset universe. We show that its major determinants are traded assets and that it is not efficient. However, it is significant for explaining individual asset returns over an asset universe that includes stocks, bonds, money markets and commodities. The explanatory information is incremental to what is available in traded asset prices and the significance of this information is robust with respect to diversified portfolios generated by factor analysis and to characteristic-sorted portfolios as well as to various model specifications, including the single-index model, the Fama-French (1992) three factor model for stocks, and various specifications of multi-index models hedged and unhedged for foreign currency risk.     

Future labor income growth and the cross-section of equity returns

This paper examines the equilibrium relation between future labor income growth and expected asset returns; it proposes revisions in the expectation of future labor income growth as a macroeconomic state variable and suggests a three-factor model, including a factor related to this variable, along with the consumption growth factor and the market factor. The proposed future labor income growth factor is positively associated with the Fama-French factors and subsumes their explanatory power in explaining the cross-section of stock returns. These results provide a possible economic explanation for the roles of the Fama-French factors: they are compensation for higher exposure to the risk related to changes in the value of human capital. This paper also compares the performance of the proposed three-factor model with other competing models and finds that the proposed model specification better captures cross-sectional variation in average returns than any of the competing asset pricing models considered.     

Do industries contain predictive information for the Fama–French factors?

We examine whether the returns of US industry portfolios predict the returns and volatility of Fama and French's small-minus-big (SMB) and high-minus-low (HML) factors. The analysis reveals that all 30 industry returns strongly forecast one-month-ahead SMB factor returns. Moreover, a significant number of industry returns predict the volatility of the SMB and HML factors by up to two or three months. These findings suggest that US industry returns contain profitable information on Fama–French SMB and HML factors, and since most investors cannot extract the profitable information contained in industry returns in a timely manner, this information gradually diffuses in equity markets.     

中国股票市场风险溢价研究

本文通过综合资产定价理论和实证文献研究结论,对1997年到2009年中国股市A股股票的风险溢价的截面差异作了详尽的实证研究。我们构造25个投资组合作为检验资产,进行Fama-MacBeth两步回归法,建立了基于市场风险溢价,账面市值比,盈利股价比,现金流股价比,投资资本比,工业增加值变化率以及回购利率和期限利差的八因素模型。我们的主要发现有以下三点:一是相对于Fama-French三因素模型,我们模型的实证解释力有显著提高;二是与过去的文献不同,我们发现回购利率和期限利差等债市指标对股市风险溢价的截面数据有显著解释能力;三是与基于投资的资产定价理论一致,我们发现投资比率和现金流股价比能显著反映我国股市的风险溢价。     

Structural models of credit risk are useful: Evidence from hedge ratios on corporate bonds

Structural models of credit risk provide poor predictions of bond prices. We show that, despite this, they provide quite accurate predictions of the sensitivity of corporate bond returns to changes in the value of equity (hedge ratios). This is important since it suggests that the poor performance of structural models may have more to do with the influence of non-credit factors rather than their failure to capture the credit exposure of corporate debt. The main result of this paper is that even the simplest of the structural models [Merton, R., 1974. On the pricing of corporate debt: the risk structure of interest rates. Journal of Finance 29, 449–470] produces hedge ratios that are not rejected in time-series tests. However, we find that the Merton model (with or without stochastic interest rates) does not capture the interest rate sensitivity of corporate debt, which is substantially lower than would be expected from conventional duration measures. The paper also shows that corporate bond prices are related to a number of market-wide factors such as the Fama-French SMB (small minus big) factor in a way that is not predicted by structural models.     

A note on the relationship between Fama–French risk factors and innovations of ICAPM state variables

This note examines, over various time scales, the extent to which SMB (the difference between the average returns of the small-stock portfolios and big-stock portfolios) and HML (the difference in returns between the high-BM portfolios and low-BM portfolios) factors share information with the innovations of state variables, which are interpreted as alternative investment opportunities. To examine the relationship, we adopt a new and innovative approach of wavelet analysis as our main empirical method. It is found that SMB and HML may play only a limited role in capturing alternative investment opportunities in the short run, but they share much information with alternative investment opportunities in the long run.     

Contrarian Investment and Macroeconomic Risk

It is now widely accepted that contrarian, or value investment strategies deliver superior returns. Gregory, Harris and Michou (2001) examine the performance of contrarian investment strategies in the UK and find that value strategies formed on the basis of a wide range of measures of value have delivered excess returns that are both statistically and economically significant. However, while value strategies appear to be profitable, the reason for their superior perform‐ ance is far from clear. Under the contrarian model, value strategies are profitable because they are contrarian to naïve strategies such as those that erroneously extrapolate past performance, while under the rational pricing model, value strategies are profitable because they are fundamentally riskier in some sense. In this paper, we discriminate between these two possibilities by undertaking a comprehensive investigation of the relationship between the returns to value investment strategies and various macroeconomic state variables that in a multi‐factor asset pricing model could reasonably be taken as proxies for risk. Moreover, we examine whether the returns to value strategies predict future GDP, consumption and investment growth over and above the contribution of the Fama and French (1993 and 1996) SMB, HML and market factors. While the SMB and HML factors behave in a manner consistent with the rational pricing model, we show that some value strategies in the UK are able to generate excess returns that do not seem to be related to known risk factors.     

The Role of Beta and Size in the Cross-Section of European Stock Returns

This paper examines the ability of beta and size to explain cross-sectional variation in average returns in 12 European countries. We find that average stock returns are positively related to beta and negatively related to firm size. The beta premium is in part due to the fact that high beta countries outperform low beta countries. Within countries high beta stocks outperform low beta stocks only in January, not in other months. We reject the hypothesis that differences in average returns on size- and beta-sorted portfolios can be explained by market risk and exposure to the excess return of small over large stocks (SMB). Consistent with recent US evidence, we find that after controlling for size, there is no association between average returns and exposure to SMB.     

Interaction of size,book‐to‐market and momentum effects in Australia

This study seeks to disentangle the effects of size, book‐to‐market and momentum on returns. Initial results show that each characteristic has a role in explaining returns, but that there is interaction between size and momentum, as well as between size and book‐to‐market. Three key findings emerge. First, the size premium is the strongest, particularly in the loser portfolios. Second, the value premium is generally limited to the smallest portfolios. Third, the momentum premium is evident for the large‐ and middle‐sized portfolios, but loser stocks significantly outperform winner stocks in the smallest size portfolio. When these interactions are controlled with multivariate regression, we find a significant negative average relation between size and returns, a significant positive average relation between book‐to‐market and returns, and a significant positive average relation between momentum and returns.     

Implied volatility and future portfolio returns

Prior studies find that the CBOE volatility index (VIX) predicts returns on stock market indices, suggesting implied volatilities measured by VIX are a risk factor affecting security returns or an indicator of market inefficiency. We extend prior work in three important ways. First, we investigate the relationship between future returns and current implied volatility levels and innovations. Second, we examine portfolios sorted on book-to-market equity, size, and beta. Third, we control for the four Fama and French [Fama, E., French, K., 1993. Common risk factors in the returns on stocks and bonds. Journal of Financial Economics 33, 3–56.] and Carhart [Carhart, M., 1997. On persistence in mutual fund performance. Journal of Finance, 52, 57–82.] factors. We find that VIX-related variables have strong predictive ability.     

Do Beta Pricing Models Explain January Mean Reversion in Stock Returns?

Jegadeesh (1991) finds evidence of January mean reversion in stock returns. In this paper we attempt to distinguish between two competing economic explanations of January mean reversion in returns: (1) mispricing in irrational markets versus (2) predictable time variation in security risk premia. Excess portfolio returns are decomposed into “explained” and “unexplained” components using the Fama-French (1993) pricing model. The explained excess returns exhibit January mean reversion. The unexplained excess returns are not mean reverting. Mean reversion is therefore consistent with rational pricing in the framework of the Fama-French model. Mean reversion can be attributed to the component of return related to a relative distress factor (SMB). A comparison with the Chen, Roll, and Ross (1986) macroeconomic factors reveals that mean reversion is due to the components related to SMB and bond default premium.     

News and the cross-section of expected corporate bond returns

We study the cross-section of expected corporate bond returns using an inter-temporal CAPM (ICAPM) with three-factors: innovations in future excess bond returns, future real interest rates and future expected inflation. Our test assets are a broad range of corporate bond market index portfolios. We find that two factors – innovations about future inflation and innovations about future real interest rates – explain the cross-section of expected corporate bond returns in our sample. Our model provides an alternative to the ad hoc risk factor models used, for example, in evaluating the performance of bond mutual funds.