Fama-French Five-factor Model Research Articles

Intangible assets and the cross-section of stock returns

We examine whether intangible assets are priced in the cross-section of stock returns. We find that intangible asset intensity has more explanatory power than size, value, profitability, and investment. An intangibles-based long-short factor has a higher Sharpe ratio than these established factors. Adding the intangible factor to the Fama-French five-factor model improves the description of average returns and makes the investment factor redundant. The intangible factor is distinct from traditional growth strategies, provides a hedge to value and quality strategies, and expands investors’ opportunity sets. Intangible intensity as characteristic is more important than as risk factor, consistent with intangibles-based mispricing.

Do funds selected by managers’ skills perform better?

We construct a simple intuitive rating mechanism to evaluate stock picking and market timing skills of equity and hybrid equity fund managers in China. We find that both our skill-rated 5-star (SR-5S) fund and the Morningstar 5-star (MS-5S) fund portfolios outperform the market. The SR-5S fund portfolio outperforms its counterpart MS-5S portfolio in most situations, depending on whether portfolio performance is measured by the abnormal returns of the CAPM model, the Fama-French three-factor (FF3) model, the Carhart four-factor (CH4) model and the Fama-French five-factor (FF5) model. Both market timing skill and stock picking skill affect the performance difference between the SR-5S fund and MS-5S fund portfolios. Additionally, the departure of a SR-5S or MS-5S fund manager is associated with fund performance declines, and the declines in performance for SR-5S funds are generally larger than the declines for the MS-5S funds.

Fama-French five-factor asset pricing model: empirical evidence from Indian stock market

The present study examines the applicability of five-factor model of Fama-French (2015). This model considers five factors namely market, size, value, profitability and investment in explaining the cross-sectional variations, i.e., variations across different stock or portfolios in the equity returns in Indian stock markets using the monthly closing price data of a sample of 486 companies which are a part of CNX 500 index over the period from July 2000 to June 2015. The paper investigates whether including any or all of the additional four factors can better explain the cross-sectional variations than the single factor capital assets pricing model. The investment strategies based on size, value and profitability provided abnormal returns over the study period. By making use of the Davis et al. (2000) methodology, we find that Fama-French five-factor model based on market premium, size premium, value premium, profitability premium and investment premium explains the variations in the equity returns better than single factor capital assets pricing model but it does not increase the adjusted R2 significantly. The results have implications for asset pricing, market efficiency and investment strategies in the Indian stock market.

The Fama-French five-factor model and emerging market equity returns

We test the Fama-French five-factor asset-pricing model on average stock returns for selected emerging and developed equity markets. We deploy the generalized method of moments (GMM) regression on 313 weekly data observations for the period, January 2010 through December 2015. We find that the profitability factor is the most useful for explaining the cross-section of emerging markets equity returns. The five-factor model performs dismally on country-specific portfolios and on geographically diversified portfolios using the Gibbons-Ross-Shanken (GRS) tests. Our results are broadly consistent with those of studies that use Australian, Chinese and South African data but contrary to studies examining American and Japanese data.

Who Knocks on the Door of Portfolio Performance Heaven: Sinner or Saint Investors?

To sin, or not to sin: that has been the question for many people for a long time, and nowadays that question has moved to the financial markets. The existence of studies that show that investing in vice sectors such as the alcohol, tobacco, and gambling industries, collectively known as the “triumvirate of Sin”, is profitable has created some uncertainty for investors who wonder whether or not to be socially responsible. We show that by implementing an investment strategy based on the Fama–French five-factor model, “saint” investors obtain better portfolio performance, even when transaction costs are taken into consideration, and therefore they are the ones chosen to knock on the door of portfolio performance heaven.

The Fama-French Five-Factor Model Plus Momentum: Evidence for the German Market

We implement the Fama-French five-factor model and enhance it with a momentum factor for the German market using recent monthly data from 2002 to 2019. We construct the factors associated with the market, size, value, profitability, investment, and momentum for the CDAX constituents and examine to what extent this six-factor model captures the return premia in the German market. Our preliminary analysis does not document any significant evidence on the profitability or investment premium.The results on the six-factor model compared with the three-factor model reveal that the additional factors do not add significant explanatory power to the analysis. We conclude that the relevance of the profitability and investment factors within the context of international asset pricing studies cannot be transferred to the country- specific case of the German market.

Mind the gap! Machine Learning, ESG Metrics and Sustainable Investment

This work proposes a novel approach for overcoming the current inconsistencies in ESG scores by using Machine Learning (ML) techniques to identify those indicators that better contribute to the construction of efficient portfolios. ML can achieve this result without needing a model-based methodology, typical of the modern portfolio theory approaches. The ESG indicators identified by our approach show a discriminatory power that also holds after accounting for the contribution of the style factors identified by the Fama-French five-factor model and the macroeconomic factors of the BIRR model. The novelty of the paper is threefold: a) the large array of ESG metrics analysed, b) the model-free methodology ensured by ML and c) the disentangling of the contribution of ESG-specific metrics to the portfolio performance from both the traditional style and macroeconomic factors. According to our results, more information content may be extracted from the available raw ESG data for portfolio construction purposes and half of the ESG indicators identified using our approach are environmental. Among the environmental indicators, some refer to companies' exposure and ability to manage climate change risk, namely the transition risk.

Carry Strategies and the US Dollar Risk of US and Global Bonds

In this article, the authors investigate the ability of currency carry strategies to mitigate the US-dollar risk of US and global bond benchmark indices. Using the Fama-French and currency factors, the authors analyze the bond benchmarks and find that currency carry strategies can easily be modified to suit bond investors, portfolio managers, and allocators. A central finding of the authors is that currency carry strategies help to mitigate the currency risk of the US dollar. Specifically, broad indices (including credit and government exposure) deserve modified carry strategies to mitigate the impact on the US dollar The results show that the exposure to the equity-based profitability factor—one of the factors in the Fama-French five-factor model—is to some extent a natural hedge against the US-dollar risk of high-yield and corporate indices. Moreover, combined currency carry overlay strategies and fixed-income investments generate Probabilistic Sharpe ratios above a certain threshold level. The results suggest that investors should consider modified currency carry strategies rather than simple carry rules when managing both US and global-high yield, corporate, and government debt. The authors also provide a framework that can be used to diversify the impact of individual equity-based factors and the currency style factors on fixed-income benchmarks. TOPICS:Analysis of individual factors/risk premia, factor-based models, style investing Key Findings • Carry strategies seek to reduce the US-dollar risk and improve the risk-return profile of US domestic and global fixed-income investments. The carry strategies can easily be implemented and monitored by portfolio managers and allocators desiring to control for their US-dollar risk. • Fixed-income adjusted currency carry strategies produce better results than the simple carry strategy as measured by the Probabilistic Sharpe ratio. Investors can utilize currency carry and manage the currency risk of corporate and high-yield US and global bond benchmarks. • Currency carry strategies generate diversified factor exposure to the Fama-French factors by mitigating the US-dollar risk and increasing alternative factor exposure.

The evaluation and comparison of three benchmark asset pricing models with daily data: supplementary evidence

ABSTRACT Recent studies advocate two new benchmark models (the Fama-French five-factor model and the Hou, Xue and Zhang four-factor model) with monthly data. Our daily data approach provides considerable supplement to the monthly data approach presented in recent studies. We adopt the advanced bootstrap methodology by replicating the original data sample, and this approach should effectively alleviate the problem of too much noise in the data of daily return. A two-pass cross-sectional regression and GMM with several useful testing statistics are used to more thoroughly diagnose the specifications of the model. The following consistency is observed when using different frequencies of sample data: the evidence indicates that the two newer benchmark models (the Fama-French five-factor model and the Hou, Xue and Zhang four-factor model) outperform the Fama-French three-factor model in estimating a few well-known portfolios (formed on different anomalies). However, several specification tests do not robustly accept the correct specifications of the Fama-French five-factor model and the Hou, Xue and Zhang four-factor model.

Credit Risk and Equity Returns: An Augmented Fama-French Five-Factor Model in the Chinese Market

Whether the credit risk should be priced has been widely debated. We study this issue in the Chinese context, where the financial market has been long dominated by indirect financing. We employ the Merton’s (1974) model to measure the credit risk of firms listed on Chinese A-share market monthly. We document a positive relationship between credit risk and subsequent returns. Following a high-minus-low strategy, we construct a credit risk factor DMU, which is then incorporated into Fama-French models. By comparing the performance of 6 competing models, we find that the credit risk factor helps improve the description of portfolio returns while the investment factor makes little contribution. The conclusions are further confirmed by regression details including adjusted-R2, AIC tests and intercepts. Meanwhile, the slopes on DMU are significant for most tested portfolios and present monotonic patterns when the credit risk increases, implying that the credit risk factor can well explain the variation in the cross section of portfolio returns. Our findings show that in the Chinese context, the credit risk factor is relevant and the DMU-augmented Fama-French five-factor model is a preferred model.

What lies behind the asset growth effect?

This study finds that changes in total factor productivity (TFP) serve as one of the drivers behind the asset growth effect. Firms increase (decrease) assets when there is an increase (decrease) in TFP. And increases (decreases) in TFP also cause corresponding increases (decreases) in earnings and returns. Subsequently, changes in TFP reverse, which also reverse earnings and returns, leading to the observed asset growth effect. Our results are robust to sorting using the Fama-French five-factor model and momentum factor, and its asset pricing implications, using low-high spread asset growth portfolios with correspondingly low-high spread TFP changes.

Emerging market currency risk exposure: evidence from South Africa

PurposeThe purpose of this paper is to examine the level of foreign exchange exposure of listed nonfinancial firms in South Africa. The study spans the period January 2002 and November 2015. Foreign exchange risk exposure is estimated in relation to the exchange rate of the South African Rand relative to the US$, the Euro, the British Pound and the trade-weighted exchange rate index.Design/methodology/approachThe study is based on the augmented-market model of Jorion (1990). The Jorion (1990) is a capital asset pricing model-inspired framework which models share returns as a function of the return on the market index and changes in the exchange rate factor. The market risk factor is meant to discount the effect of macroeconomic factors on share returns, thus isolating the foreign exchange risk factor. In addition, the study further added the size, value, momentum, investment and profitability risk factors in line with the Fama–French three-factor model, Carhart four-factor model and the Fama–French five-factor model to account for the fact that equity capital markets in countries such as South Africa are known to be partially segmented.FindingsForeign exchange risk exposure levels were estimated at more than 40% for all the proxy currencies on the basis of the standard augmented market model. However, after controlling for idiosyncratic factors, through the application of the Fama–French three-factor model, the Carhart four-factor model and the Fama–French five-factor model, exposure levels were found to range between 6.5 and 12%.Research limitations/implicationsThese results indicate the importance of controlling for the effects of idiosyncratic facto0rs in the estimation of foreign exchange risk exposure in the context of emerging markets of Sub-Saharan Africa (SSA).Originality/valueThis is the first study to apply the Fama–French three-factor model, Carhart four-factor model and the Fama–French five-factor model in the estimation of foreign exchange exposure of nonfinancial firms in the context of a SSA country. These results indicate the importance of controlling for the effects of idiosyncratic factors in the estimation of foreign exchange risk exposure in the context of emerging markets.

The Fama-French’s five-factor model relation with interest rates and macro variables

Innovations in variables describing future investment opportunities command a risk premium and are correlated with Fama-French factors. As showed in literature, shocks to the aggregate dividend yield and term spread, default spread, and one-month T-bill rate are proxies for HML and SMB factors. However, in the context of five-factor model, they cannot explain RMW. As CPI is related to operational profitability, and so does RMW, we include its unanticipated shocks in the set of macro variables and factors to help explaining the cross section of returns. In the presence of CPI, RMW loses its explanatory power, and, combined with term structure’s slope innovations, all Fama-French factors lose their explanatory ability and the pricing errors become statistically close to zero. We show that for US data, inflation’s innovations not only proxy for RMW, but a model including only excess market returns, shocks to CPI and term structure’s slope explain the cross section of average returns better than innovations to the previous literature’s four-variable set and Fama-French five-factor model.

Time-Series Efficient Factors

We show that factors in prominent asset pricing models are unconditionally minimum-variance inefficient. Factor returns are positively autocorrelated while risk, conditional on past returns, is constant. We derive a transformation that turns an autocorrelated factor into a factor. Time-series efficient factors earn 40% higher Sharpe ratios than the original factors and contain all the information found in the original factors. Momentum strategies profit from the inefficiencies in factor returns. An asset pricing model with time-series efficient factors, such as an efficient Fama-French five-factor model, prices momentum. Our results impose novel restrictions on theoretical models of asset returns.

Testing Liquidity Augmented Fama-French Five-Factor Model in Pakistan Stock Exchange

This study examines the empirical evaluation of the six-factor asset pricing model that augments the Fama-French (2015) five-factor asset pricing model with liquidity factor. Using data from July 2010 to June 2017 of non-financial firms listed on PSX, a 2x3 sort approach is used to construct six left-hand side portfolios, and a 2x2 approach is used to construct right-hand side factors namely, SMB, HML, RMW, CMA, and IML. Time series regression is used to analyze the data to obtained results. The empirical evidence illustrates that in PSX the six-factor model has efficient and better outcomes. Furthermore, the liquidity factor has a strong role in improving the performance of the asset pricing model.

An empirical investigation of the Fama-French five-factor model

The article deals with evaluating the securities portfolios in the process of transition from the one-factor CAPM model to the Fama-French five-factor model (FF5F). It identifies the advantages of the latter and discusses the controversial issues regarding its use by portfolio investors in different countries, given the anomalies inherent in asset pricing. Besides, the peculiarities of the statistical stratification method used in the FF5F model to group stock portfolios are revealed, and attention is drawn to some of the debating points of the five-factor model. The proposals have been formulated, which offer broader avenues for taking advantage of the FF5F model and increase the validity of the portfolio analysis results. The article also gives recommendations on modifying the approaches to analyzing small-size portfolios versus big-size portfolios based on partial changes in RMW and CMA factors, threshold proportions, and the use of STARR for asymmetric portfolios. The study substantiates the use of these approaches in testing the Fama-French five-factor model with portfolios composed of blue chips.

Sustainable Development Goals and Investment Strategies: The Profitability of Using Five-Factor Fama-French Alphas

This study focuses on assets related to Sustainable Development Goals (SDGs), which are the most recent aspect of the Socially Responsible Investment framework and have caught the attention of investors due to their investment opportunities as well as the global challenges that can be achieved. The profitability of developing an investment strategy is shown based on the value of the alphas obtained from the estimation of the Fama-French five-factor model when compared to an equally weighted portfolio, even when transaction costs are taken into consideration. In addition, it is proven that investors should focus their investments on two main SDGs: Good health and well-being (Goal 3) and Industry, innovation and infrastructure (Goal 9).

Testing Multi-Factor Models in ADRs: Emerging Market vs. Developed Market

This paper tests whether the Carhart four-factor model and the Fama-French five-factor model can explain variation in returns of 1,230 ADRs originating from six developed markets and five emerging markets. We aim to compare emerging market ADRs with developed market ADRs in terms of traditional risk factors significance, model fitness and the existence of abnormal returns. Overall, we find that substantial variations exist among ADRs by their origin-of-market. First, both models show that most of the positive abnormal returns we document accrue to emerging market ADRs, mainly Chinese ADRs. Among the risk factors, market risk premium is found to be most prevalent in both emerging and developed markets. Although we find some difference in the presence of particular risk factors employed in the four-factor vs. five-factor model, overall, there are no significant differences in the explanation power between the two models. Lastly, the low R2 values imply that both models do not work very well with the international market ADRs.

Empirical tests of the Fama-French five-factor model in Indonesia and Singapore

We examine the performance of the Fama-French three-factor (FF3) and five-factor (FF5) models in Indonesia and Singapore markets. We also investigate whether the book-to-market factor (HML) is redundant in both markets if profitability and investment factors are present. Different from previous studies, our empirical findings highlight that FF5 does not perform better than FF3 in explaining excess portfolio returns in both markets. Unlike the US market, we find that HML factor is not redundant in both markets. The results are robust for equally-weighted and value-weighted portfolios and also for various factor construction methods.

Empirical tests of the Fama-French five-factor model in Indonesia and Singapore

We examine the performance of the Fama-French three-factor (FF3) and five-factor (FF5) models in Indonesia and Singapore markets. We also investigate whether the book-to-market factor (HML) is redundant in both markets if profitability and investment factors are present. Different from previous studies, our empirical findings highlight that FF5 does not perform better than FF3 in explaining excess portfolio returns in both markets. Unlike the US market, we find that HML factor is not redundant in both markets. The results are robust for equally-weighted and value-weighted portfolios and also for various factor construction methods.