Fama French Research Articles

Asset pricing factors in Islamic equity returns

AbstractPrevious studies have compared risk–return characteristics of Islamic equity indices with their conventional counterparts, which may produce spurious results because a conventional equity index includes both Islamic and non‐Islamic constituents. Hence, this study compares Islamic equity portfolios with their non‐Islamic counterparts. We find that aggregate Islamic equity portfolios generally outperform non‐Islamic equity portfolios after controlling for the five asset pricing factors—market, size, value, profitability, and investment (Fama and French, 2015). The average cost of equity is 2.77 percentage points lower for Islamic firms compared to non‐Islamic firms. The findings hold for the various segments of the global equity market, and remain robust when the interest rate‐augmented and the liquidity factor‐augmented versions of the Fama–French five‐factor model are employed. The GRS test results suggest these asset pricing models may not be adequate for pricing both Islamic and non‐Islamic equities.

Do Fama–French common risk-factor portfolio investors herd on a daily basis? Implications for common risk-factor regressions

Purpose The purpose of this paper is to examine whether Fama–French common risk-factor portfolio investors herd on a daily basis for five developed markets, namely, Europe, Japan, Asia Pacific ex Japan, North America and Globe. Design/methodology/approach To examine the herd behavior of common risk-factor portfolio investors, this paper utilizes the cross-sectional absolute deviations (CSAD) methodology, covering a daily data sampling period of July 1990 to January 2019 from Kenneth R. French-Data Library. CSAD driven by fundamental and non-fundamental information is assessed using Fama–French five-factor model. Findings The results do not provide evidence for herding under normal market conditions, either when reacting to fundamental information or non-fundamental information, for any region under consideration. However, Fama–French common risk-factor portfolio investors mimic the underlying risk factors in returns related to size and book-to-market value, size and operating profitability, size and investment and size and momentum of the equity stocks in European and Japanese markets during crisis period. Also, no considerable evidence is found for herding (on fundamental information) under crisis and up-market conditions except for Japan. Ancillary findings are discussed under conclusion. Research limitations/implications Further research on new risk factors explaining stock return variation may help improve the model performance. The performance can be improved by adding new risk factors that are free from behavioral bias but significant in explaining common stock return variation. Also, it is necessary to revisit the existing common risk factors in order to understand behavioral aspects that may affect cost of capital calculations (e.g. pricing errors) and valuation of investment portfolios. Originality/value This is the first paper that examines the herd behavior (fundamental and non-fundamental) of Fama–French common risk-factor investors using five-factor model.

Show me the money: Option moneyness concentration and future stock returns

AbstractInformed traders often use options that are not in‐the‐money due to higher potential gains for a smaller upfront cost. Thus, trading activity by option moneyness should be a gauge of informed option trading. We construct a dollar volume‐weighted average moneyness measure to capture option trading activity at different moneyness levels. Stock returns increase with this measure, suggesting more trading activity in options with higher leverage predicts future stock returns. Our results hold cross‐sectionally and at the portfolio level yielding a Fama–French five‐factor α of 12% per year for all stocks and 33% per year for high implied volatility stocks.

Factor Investing in Currency Markets: Does It Make Sense?

The concept of factor investing emerged at the end of the 2000s and has completely changed the landscape of equity investing. This approach has been extended to multiasset portfolios and, more recently, has gained popularity in the fixed-income universe. In this article, the authors focus on currency markets. The dynamics of foreign exchange rates are generally explained by several theoretical economic models that are commonly presented as competing approaches. In the opinion of the authors, they are more complementary and can be the backbone of a Fama–French–Carhart risk factor model for currencies. In particular, the authors show that these risk factors may explain a significant part of time-series and cross-section returns in foreign exchange markets. TOPICS:Factors/risk premia, quantitative methods, performance measurement, derivatives Key Findings • Risk factors explain 50% of the cross-section of currency returns on average. • The most important risk factors are carry and time-series momentum. • Only the value risk factor exhibits a positive risk premium priced by the market.

Institutional Investors and Corporate Performance: Insights from China

This study uses the annual data of Chinese A-share listed companies held by institutional investors during the period of 2005–2016 for empirical analysis. First, this study uses the panel regression model to explore the relationship between institutional ownership and stock return volatility. Then, the CAPM one-factor model and the Fama–French three-factor model are used to analyze the relationship between institutional ownership and idiosyncratic risks. Finally, we estimate the relationship between institutional ownership and corporate governance. Furthermore, we compare the empirical results before, during, and after the crisis. This study uses the Hausman test and the endogenous test to validate the results. The empirical results show that the management behavior of independent institutional investors is more obvious post-crisis. However, gray institutional investors have no impact on idiosyncratic risks. In the regression of the CAPM one-factor model, domestic institutional investors have effectively reduced the idiosyncratic risks before the financial crisis. Foreign institutions’ monitoring performance before, during, and after the crisis is not obvious. All institutional ownership has a significant positive impact on the top 10 shareholders, but independent and domestic institutional ownership has a significant negative impact on senior shareholders. Institutional ownership has little impact on the movement of the first shareholder and CEO.

Choosing factors: Australian evidence

Using a factor-pricing approach, this paper investigates the extent to which the factors in the Fama–French five-factor model, including momentum, explain Australian equity returns. A comparison of the United States and Australia suggests common components in asset returns. All the factors examined are useful in pricing Australian equities, whereas the HML factor is redundant for the United States. The findings suggest that the Fama–French five-factor model should be at least considered as a benchmark model in asset pricing research.

Profitability, Product Market Competition, and Stock Returns

This paper finds that product market competition level (measured by Herfindahl Hirschman Index using Fama French 48 industries) affects the performance of zero-cost investment strategies based on gross probability. From 1973 to 2017, the positive returns from such strategy mainly comes from the most competitive industry quintile while a strong reversal exists the second most competitive quintile. The same strategy does not generate any statistically significant returns in concentrated industry quintiles. Out of 25 dependently sorted portfolios on product market competition level and gross profitability, the top performing portfolio comes from the least profitable firms in the second most competitive industry quintile, where 65% of firms are from pharmaceutical and oil industries.

DFA, Fidelity, and Vanguard: Comparing the Returns of these Leading Mutual Fund Families

This chapter evaluates the returns of the domestic equity funds of three major American companies: Vanguard, Fidelity, and Dimensional Fund Advisors relative to benchmarks using the Fama-French factors from January 2001 through December 2018. We also present Sharpe’s (1992) style analysis combined with the Fama French 25 portfolios, sorted by the dimensions of book to market value and size. Both the two factor and the Sharpe analyses benchmark according to size and valueness. Comparing the two explores the robustness of our findings. Table 6 presents a succinct comparison of the results from both the 2 factor model and the Sharpe analyses. Both methods show that that for Fidelity the index portfolio consistently out-returns the managed portfolio. Table 7 finds that between 2001and 2018 DFA, the indexed and managed portfolios from Vanguard, and the managed portfolio from Fidelity out-returned the US stock market. This is also true of the Fidelity index portfolio from 2005-2018. We also construct efficient frontiers to assess which groups of funds and from which families are included and which are left out.

Industry classification, product market competition, and firm characteristics

We examine twelve industry classifications from three classification systems: SIC (including Fama French classifications), NAICS and GICS, over the period from 1963 to 2017. The results show different classifications can generate conflicting descriptions of product market competition and firm characteristics across product market competition levels. We also demonstrate that the choice of industry classification and sample period are the causes of opposite empirical results that support the conflicting theories of Schumpeter. We find Fama French 48 and eight-digit GICS to be the only classifications that generate consistent performance of industry portfolios formed by production market level, throughout the sample period.

Market pricing of liquidity risk: evidence from China

Purpose The purpose of this paper is to investigate whether liquidity risk (i.e. the returns’ vulnerability to the unexpected changes in overall market liquidity) is a priced risk factor in China. Moreover, it investigates the potential role of a stock’s information quality in reducing its liquidity risk during the period of post-non-tradable shares reforms in China. Design/methodology/approach The authors collect data of all the A-share issuing firms listed either on the Shanghai Stock Exchange or Shenzhen Stock Exchange during the period 2006–2016. The authors perform two-stage cross-sectional regression testing. First, the authors perform firm-specific time-series regressions of excess returns over Fama–French’s three-factor model and a liquidity factor. Second, to test whether firm-specific liquidity risk is a priced risk factor, the authors apply Fama and MacBeth’s regressions. Findings Firm-level asset pricing tests provide substantial evidence for market pricing of liquidity risk in China. The authors find a significant negative association between information quality and liquidity risk. The authors also find that the reduction in liquidity risk induced by better information quality is substantial enough to reduce required returns. These findings are robust to alternative measures of liquidity risk and information quality. Practical implications The study underscores that a policy initiative to enhance the information environment can significantly reduce the market volatility in China. Originality/value To the best of authors’ knowledge, this is the first study that considers the Shanghai Stock Exchange as well as Shenzhen Stock Exchange to investigate market pricing of liquidity risk in China.

Asset pricing and energy consumption risk

AbstractThis 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.

Asset pricing model uncertainty

Abstract This paper provides a unified calendar-time portfolio methodology for assessing whether returns following an event are abnormal which efficiently handles asset pricing model uncertainty and allows for time-varying alpha and factor exposures. The approach disciplines researchers’ use of asset pricing factors and assigns a probability measure to the appropriateness of (dynamically) selecting a single model that best approximates the true factor structure or whether model averaging across an asset pricing universe is desired. It is applied to the long-horizon effect of dividend initiations and resumptions in the 1980 to 2015 period. Resulting post-announcement conditional abnormal returns are generally significant, statistically and economically, which contrasts recent evidence, and exhibits a break in mean from positive until the mid-1990s and negative onwards. We document substantial time-variation in the dimensionality and composition of the factor structure in expected returns, which goes beyond what captured by conditional versions of the CAPM and Fama–French specifications. This also generalizes to a large panel of 202 characteristics-sorted portfolios.

Factors influencing SRI fund performance

Purpose The purpose of this paper is to examine socially responsible investment (SRI) fund performance and investigate the factors influencing fund performance. Design/methodology/approach The study uses return data from the Morningstar database for 152 SRI funds from January 1995 to May 2015. The initial analysis includes the use of various risk-adjusted performance measures, including Sharpe ratio, Treynor ratio, Information ratio, Sortino ratio and M2. The study also uses four factor models, including Jensen single-factor model, Fama–French three-factor model, Carhart four-factor model and Fama–French five-factor model to explain SRI fund returns. Finally, a cross-sectional regression analysis is applied to investigate the determinants of SRI fund returns. Findings The results show that, on average, the SRI funds provide comparable risk-adjusted returns relative to various benchmark market indices. Market factor is significant in explaining SRI fund returns. Examining each factor model, the results do not support Fama–French’s three-factor model as neither size nor value factor is significant. The author finds weak support for Carhart’s momentum factor along with the market factor. Finally, the Fama–French five-factor model shows market, size and operating profit factors explain SRI fund returns. The study also finds the fund performance is stronger for funds with the higher turnover ratio, the larger fund size and more managerial experience and lower for funds with higher expense ratio. Also, funds formed with negative screening perform better than positive or mixed screened funds. Originality/value SRI funds have received considerable attention from investors. This study contributes to the literature by examining SRI fund performance and investigating factors influencing their performance using multiple factor models and cross-sectional regression analysis. The findings are relevant for investors who demand responsible investment opportunities without sacrificing returns for nonfinancial screenings. Findings also suggest that investors should consider fund characteristics when selecting SRI funds.

Fama–French Factor Timing: The Long-Only Integrated Approach

There is ample evidence that factor momentum exists in the standard long--short mixed approach to factor investing. However, the excess returns are put under scrutiny due to the high implementation costs. We present a novel real-life approach that relies on the long-only integrated approach to factor investing. Instead of exploiting the potential momentum in factor portfolios, our strategy builds on the momentum of the optimal factor score weights in the integrated approach, which allows us to additionally profit from the serial dependence in the factors' interaction effects. One limitation of short-term timing strategies is their high turnover. By including the information of the covariance matrix and minimizing the strategy’s risk to the market portfolio, we can substantially reduce turnover. The resulting timing alpha remains significant even after transaction costs in a robust statistical test framework across the major stock markets.

Passive ESG Portfolio Management - The Benchmark Strategy for Socially Responsible Investors

In this article, we analyze the possibility to do well, while doing good from a passive portfolio management strategy. In this analysis, we distinguish the regions Europe and the US and refer to the stock price data of composites from the most important indices in these regions. Based on these, we design portfolios that mimic a typical index, and compare their performance in terms of risk, ESG and return. All strategies proposed are passive and thus, not affected by management skills or fees. We show, that there are significant differences across the regions which can only partly be explained by the Fama French factors. We find that there is no significant difference between an ESG based strategy and the naive one in terms of returns or sharpe ratios, whereas a clear outperformance in the ESG value is evident. From this, it can be concluded, that socially responsible investors are willing to pay for the impact of the portfolio, as in opposite to the naive strategy transaction costs have to be paid. Comparing the ESG based strategy to the value weighted strategy that is used for most indices, we observe no significant ESG difference but a significant superior performance of the ESG based portfolio, arguing in favor of the ESG strategy being preferable to all investors - not only the social ones.

Does the Five-Factor Asset Pricing Model Have Sufficient Power?

The central purpose of this article is to assess whether the newly developed five-factor model of Fama and French (2015) has sufficient power to identify the long-term abnormal performance of firms experiencing major corporate events. In order to check the robustness of the five-factor model, power of the Fama–French three-factor model (1993) has also been investigated. Simulations show that although the five-factor specification is more powerful than the three-factor specification, the extended model still lacks power. The findings further suggest that if the book-to-market factor is excluded from the five-factor model, the four-factor model documents almost similar power like the five-factor model. In addition, the power is found to be substantially reduced as the event period advances.

Dynamic Shrinkage Processes

SummaryWe propose a novel class of dynamic shrinkage processes for Bayesian time series and regression analysis. Building on a global–local framework of prior construction, in which continuous scale mixtures of Gaussian distributions are employed for both desirable shrinkage properties and computational tractability, we model dependence between the local scale parameters. The resulting processes inherit the desirable shrinkage behaviour of popular global–local priors, such as the horseshoe prior, but provide additional localized adaptivity, which is important for modelling time series data or regression functions with local features. We construct a computationally efficient Gibbs sampling algorithm based on a Pólya–gamma scale mixture representation of the process proposed. Using dynamic shrinkage processes, we develop a Bayesian trend filtering model that produces more accurate estimates and tighter posterior credible intervals than do competing methods, and we apply the model for irregular curve fitting of minute-by-minute Twitter central processor unit usage data. In addition, we develop an adaptive time varying parameter regression model to assess the efficacy of the Fama–French five-factor asset pricing model with momentum added as a sixth factor. Our dynamic analysis of manufacturing and healthcare industry data shows that, with the exception of the market risk, no other risk factors are significant except for brief periods.

Return reversal effect in Shanghai A share market

PurposeThe existing literature about return reversal effect in Chinese stock markets is inconclusive and controversial. Therefore, the purpose of this paper is to investigate the presence of return reversal effect in the Shanghai A stock market.Design/methodology/approachThe authors used the late-stage contrarian strategy of Malin and Bornholt (2013) for the period March 2011‒March 2016.FindingsThe results show that there is a long-term return reversal effect in the Shanghai A stock market for the period March 2011‒March 2016. When portfolios are in the formation period (P=24 months), the excess returns are significant in the holding period, Q=6, 9, 12, 24 months. Further, there is also a significant short-term momentum effect in the Shanghai A stock market. For the robustness check, a new reversal factor was introduced into the Fama‒French three-factor model. Results show that portfolios have a smaller size and have lower book-to-market ratios; the return reversal factor explains a portion of the abnormal returns and coefficient of the reversal effect is significant.Research limitations/implicationsThe authors caution readers from generalizing the findings of this study, as the sample is small and the focus is only on A stocks listed on the Shanghai Stock Exchange.Originality/valueThe present research expands the current literature by providing a comprehensive information about the presence of the long-term and short-term return reversal effects in Shanghai A stock market. Furthermore, the Chinese stock markets have distinctive features in comparison to the developed stock markets in terms of government control, institutional structure, liquidity, cultural background, etc. Such differences affect the pattern in stock returns compared with those observed in developed stock markets. Contrary to previous studies, the present study also accounts for robustness checks. Finally, it also evaluates the possible reasons for the return reversal effect in the Shanghai market.

Investor sentiment and its role in asset pricing: An empirical study for India

In this paper, we experiment with the construction of alternative investor sentiment indices. Further, we evaluate the role of the sentiment-based factor in asset pricing to explain prominent equity market anomalies such as size, value, and price momentum for India. Based on the findings, we confirm that our Composite Sentiment index leads other sentiment indices currently in vogue in investment literature. The asset pricing models, including the more recent Fama French 5 factor model, are not fully able to explain the small firm effect which is captured by our sentiment-based factor which seems to proxy for the price over-reactions.

Return Predictability: Evidence from the US–China Supply Chain

In this article, by investigating return predictability across a transnational supply chain, the authors present new evidence supporting the hypothesis that value-relevant information diffuses gradually in financial markets because of limited attention from investors. They find that the corresponding trading strategy delivers superior abnormal return. Using a sample of supply chains between Chinese customers and US suppliers from 2009 to 2015 and corresponding financial and return data, the authors show that Chinese customer returns can predict US supplier future return at the firm level. A long–short portfolio strategy based on these findings yields significant abnormal monthly returns of 2.179% (equal-weighted portfolio) in the Fama–French five-factor model. The authors also employ Fama–MacBeth regression analysis and propensity score matching–matched sample analysis, and the conclusions continue to hold.