TRANSITORY MARKET STATES AND THE JOINT OCCURRENCE OF MOMENTUM AND MEAN REVERSION

In this article we derive and investigate the implications of the Fama–French and Poterba–Summers model—in which the market price of equity contains permanent and temporary components—to explain cross‐sectional differences in equity risk premia and returns. Shocks to the transitory component are regarded a Merton risk factor. We obtain estimates from a simple Kalman decomposition of the market price. The transitory component estimate is used in a conditional capital asset pricing model to test implications of the model related to predictability, cross‐sectional performance, and the existence of momentum and mean reversion.     

In America's thrall: the effects of the US market and US security characteristics on Australian stock returns

Can Australian equity returns be modelled by ‘home‐grown’ factors? We examine the indigenous capital asset pricing model, the indigenous Fama–French three‐factor model, and extensions to the latter, and find them all wanting. We find evidence of domestic market segmentation in Australia. For the smallest firms, all the models we study fail. For the largest Australian firms, we find that the US Fama–French three factors (downloaded from French's website: http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/ ) provide a successful model of Australian returns. It is as if the largest firms in the Australian market are simply part of the larger US market.     

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.     

THE FAMA‐FRENCH MODEL,LEVERAGE, AND THE MODIGLIANI‐MILLER PROPOSITIONS

For a cost‐of‐equity model to conform to the Modigliani‐Miller cost‐of‐capital propositions, any sensitivity coefficients in the model must be related to the firm's leverage. In this paper I apply these principles to the Fama‐French model for the cost of equity and develop the relation between its sensitivity coefficients and firm leverage. I then examine an empirical process developed by Fama and French (1997) to model the evolution through time of their sensitivity coefficients and show that this empirical process is inconsistent with the Modigliani‐Miller propositions. Separable functions are proposed for these sensitivity coefficients that are consistent with the Modigliani‐Miller propositions.     

Regulator's Determination of Return on Equity in the Absence of Public Firms: The Case of Automobile Insurance in Ontario

In a regulated market, such as automobile insurance (AI), regulators set the return on equity that insurers are allowed to achieve. Most insurers are engaged in a variety of insurance lines of business, and thus the full information beta methodology (FIB) is commonly employed to estimate the AI beta. The FIB uses two steps: first, the beta of each insurer is estimated, and then the beta of each line of business is estimated, as the beta of an insurer is a weighted average of the betas of the lines of business. When there are a sufficient number of public companies, company and market returns are used. Otherwise, researchers have resorted to using accounting data in the FIB. Theoretically, the two steps are not separable and the estimation should be done with one step. We introduce the one‐step methodology in our article. The one‐step and two‐step methodologies are compared empirically for the Ontario market of AI. Insurers in Ontario are predominantly private companies; thus, accounting data are used to estimate the AI beta. We show that a significant bias is introduced by the traditional, two‐step FIB methodology in estimating the betas for different lines of business, while insurers’ betas are very similar under both methods. This has a significant application to the estimation of betas of “pure players” in classic corporate finance. It implies that their betas and hence the resulting, required rates of return used in the net present value calculations should be estimated based on the one‐step method that we develop in this article.     

Performance and Persistence in Institutional Investment Management

Using new, survivorship bias‐free data, we examine the performance and persistence in performance of 4,617 active domestic equity institutional products managed by 1,448 investment management firms between 1991 and 2008. Controlling for the Fama–French (1993) three factors and momentum, aggregate and average estimates of alphas are statistically indistinguishable from zero. Even though there is considerable heterogeneity in performance, there is only modest evidence of persistence in three‐factor models and little to none in four‐factor models.     

Alternative measures of the Federal Reserve Banks’ cost of equity capital

The Monetary Control Act of 1980 requires the Federal Reserve System to provide payment services to depository institutions through the 12 Federal Reserve Banks at prices that fully reflect the costs a private-sector provider would incur, including a cost of equity capital (COE). Although Fama and French [Fama, E.F., French, K.R., 1997. Industry costs of equity. Journal of Financial Economics 43, 153–193] conclude that COE estimates are “woefully” and “unavoidably” imprecise, the Reserve Banks require such an estimate every year. We examine several COE estimates based on the CAPM model and compare them using econometric and materiality criteria. Our results suggest that the benchmark CAPM model applied to a large peer group of competing firms provides a COE estimate that is not clearly improved upon by using a narrow peer group, introducing additional factors into the model, or taking account of additional firm-level data, such as leverage and line-of-business concentration. Thus, a standard implementation of the benchmark CAPM model provides a reasonable COE estimate, which is needed to impute costs and set prices for the Reserve Banks’ payments business.     

Extending the capital asset pricing model: the reward beta approach

This paper offers an alternative method for estimating expected returns. The proposed reward beta approach performs well empirically and is based on asset pricing theory. The empirical section compares this approach with the capital asset pricing model (CAPM) and the Fama–French three‐factor model. In out‐of‐sample testing, both the CAPM and the three‐factor model are rejected. In contrast, the reward beta approach easily passes the same test. In robustness checks, the reward beta approach consistently outperforms both the CAPM and the three‐factor model.     

The reduced-rank beta in linear stochastic discount factor models

In a linear stochastic discount factor model, failure of the full-rank conditions affects the standard statistical inference of coefficients. We propose a novel risk measurement, the reduced-rank beta, which is the risk sensitivity to the effective part of factors for the full-rank covariance matrix. Our reduced-rank beta is a generalisation of the standard beta when the full-rank condition is not satisfied. By considering the Fama–French five-factor (FF5) model for the US equity market, the failure of the full-rank condition is found to affect beta estimates. We demonstrate the reduced-rank beta has important empirical implications for model reductions and anomaly explanations.     

Anomalies and stock returns: Australian evidence

Prior research has identified the existence of several cross‐sectional patterns in equity returns, commonly referred to as effects. This paper tests for the existence of a number of well‐known effects using data from the Australian equities market. Specifically, we investigate the size effect, book‐to‐market effect, earnings‐to‐price effect, cashflow‐to‐price effect, leverage effect and the liquidity effect. An additional aim of this paper is to investigate the capability of the Fama–French model in explaining any observed effects. We document a size, book‐to‐market, earnings‐to‐price and cashflow‐to‐price effect but fail to find evidence of a leverage or liquidity effect. Although our findings indicate that the Fama–French model can partially explain some of the observed effects, we conclude that its performance is less than satisfactory in Australia.     

Earnings Quality, Insider Trading, and Cost of Capital

Previous research argues that earnings quality, measured as the unsigned abnormal accruals, proxies for information asymmetries that affect cost of capital. We examine this argument directly in two stages. In the first stage, we estimate firms' exposure to an earnings quality factor in the context of a Fama‐French three‐factor model augmented by the return on a factor‐mimicking portfolio that is long in low earnings quality firms and short in high earnings quality firms. In the second stage, we examine whether the earnings quality factor is priced and whether insider trading is more profitable for firms with higher exposure to that factor. Generally speaking, we find evidence consistent with pricing of the earnings quality factor and insiders trading more profitably in firms with higher exposure to that factor.     

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.     

A Dynamic Model of Firm Valuation

We propose a dynamic version of the dividend discount model, solve it in closed form, and assess its empirical validity. The valuation method is tractable and can be easily implemented. We find that our model produces equity value forecasts that are very close to market prices, and explains a large proportion of the observed variation in share prices. Moreover, we show that a simple portfolio strategy based on the difference between market and estimated values earns considerably positive returns. These returns cannot be simply explained either by the Fama‐French three‐factor model (even after adding a momentum factor) or the Fama‐French five‐factor model.     

The Performance of Hedge Fund Strategies and the Asymmetry of Return Distributions

We present hedge fund performance estimates that adjust for stale prices, Fama‐French risk factors and skewness. We contrast these new performance estimates with traditional performance measures. Using three‐factor models to adjust for staleness in prices and to incorporate Fama‐French factors along with the Harvey‐Siddique (2000) two‐factor model that incorporates skewness, we find that for the period 1990–2003, all hedge fund categories achieve above average performance when measured against an aggregate market index. More significantly, however, when we estimate performance at the individual hedge fund level, we discover that only 40 to 47% of the funds are shown to achieve an above average performance over that time period depending on the model used. These results have important implications for investors, endowments and pensions when they choose hedge fund managers.     

UK Evidence on the Characteristics versus Covariance Debate

We evaluate the Fama–French three‐factor model in the UK using the approach of Daniel and Titman (1997) to determine whether characteristics or covariance risk better explains the size and value premiums. Across all three factors, we find that return premiums bear little relationship to the corresponding loadings. We show that small and value stocks earn higher returns irrespective of their return covariance. Our study contributes to the existing literature by reporting original findings on the Fama–French three‐factor model in the UK and by reporting results that complement existing evidence from similar studies in the USA and Japan.     

Estimating the Cost of Equity for Property-Liability Insurance Companies

Due to the highly skewed and heavy‐tailed distributions associated with the insurance claims process, we evaluate the Rubinstein‐Leland (RL) model for its ability to improve the cost of equity estimates of insurance companies because of its distribution‐free feature. Our analyses show that there is as large as a 94‐basis‐point difference in the estimated cost of insurance equity between the RL model and the capital asset pricing model (CAPM) for the sample of property‐liability insurers with more severe departures from normality. In addition, consistent with our hypotheses, significant differences in the market risk estimates are found for insurers with return distributions that are asymmetrically distributed, and for small insurers. Third, we find significant performance improvements from using the RL model by showing smaller values of excess return of the expected return of the portfolio to the model return for a portfolio of insurers with returns that are more skewed and for a portfolio of small insurers. Finally, our panel data analysis shows the differences in the market risk estimates are significantly influenced by firm size, degree of leverage, and degree of asymmetry. The implication is that insurers should use the RL model rather than the CAPM to estimate its cost of capital if the insurer is small (assets size is less than $2,291 million), and/or its returns are not symmetrical (the value of skewness is greater than 0.509 or less than ?0.509).     

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.     

Asset pricing models with errors-in-variables

This paper revisits Fama and French [Fama, Eugene F., French, Kenneth R., (1993) Common risk factors in the returns on stock and bonds. Journal of Financial Economics 33 (1), 3–56] and Carhart [Carhart, Mark M., 1997. On persistence in mutual fund performance. Journal of Finance 52 (1), 57–82] multifactor model taking into account the possibility of errors-in-variables. In their well known paper, Fama and French [Fama, Eugene F., French, Kenneth R., 1997. Industry costs of equity. Journal of Financial Economic 43 (2), 153–193] concluded that estimates of the cost of equity for the three-factor model of FF (1993) were imprecise. We argue that this imprecision is even more severe because of the pervasive effects of measurement errors. We propose Dagenais and Dagenais [Dagenais, Marcel G., Dagenais, Denyse L., 1997. Higher moment estimators for linear regression models with errors in the variables. Journal of Econometrics 76 (1–2), 193–221] higher moments estimator as a solution. Our results show that estimates of the cost of equity obtained with Dagenais and Dagenais estimator differ sharply from popular OLS estimates and shed a new light on performance attribution and abnormal performance (α). Adapting the Generalized Treynor Ratio, recently developed by Hübner [Hübner, Georges, 2005. The generalized treynor ratio. Review of Finance 9 (3), 415–435], we show that the performance of managed portfolios with multi-index models should be revisited in presence of errors-in-variables.     

APPLICABILITY OF THE FAMA‐FRENCH THREE‐FACTOR MODEL IN FORECASTING PORTFOLIO RETURNS

For the model‐based estimation of the equity cost of capital, evidence shows that the common practice of using the average historical factor premiums as the estimates of the next‐period factor premiums generates inaccurate estimates. I propose an alternative way to estimate factor premiums by using the structural variables that are important predictors of future asset returns. Based on the out‐of‐sample results from a trading strategy with four in‐sample model‐selection criteria, I find that my estimation procedure performs better than the common practice even when transaction costs are considered.     

International Islamic funds

Internationally‐investing Islamic equity funds from developed Islamic and non‐Islamic markets perform in general similar to the market. However, analyzing different market conditions, we provide evidence that funds domiciled in Islamic markets outperform their peers and funds from non‐Islamic markets during market turmoil, irrespective of the applied performance measurement model. We suggest that this outperformance is owed to the expertise of fund managers from developed Islamic markets who operate in a financial environment that is driven by Islamic principles. Our results are robust with respect to the standard Fama‐French three‐factor and four‐factor models as well as to the novel five‐factor model.