French Three-factor Model Research Articles

Applying the Fama and French three-factor model to analyze risk/reward in the Spanish REITs: an ARDL approach

PurposeThis paper aims to analyse the risk and excess returns of the Spanish real estate investment trusts (S-REITs) using various methods, though focusing primarily on the Fama-French three-factor (FF3) model, over the period from 2007Q3 to 2017Q2.Design/methodology/approachThe autoregressive distributed lag model is used for the empirical analysis to test long-term stable relationships between variables.FindingsThe findings indicate that the FF3 model is suitable for the S-REITs market, better explaining the S-REITs’ returns variation than the traditional single-index capital asset pricing model (CAPM) and the Carhart four-factor model. The empirical evidence is reasonably consistent with the FF3 model; the values for the market, size and value are highly statistically significant over the analysis period, with 68.7% variation in S-REITs’ returns explained by the model. In the long run, the market factor has less explanatory power than the size and value factors; the positive long-term multiplier of the size factor indicates that small S-REIT companies have higher returns, along with higher risk, while the negative multiplier of the value indicator suggests that S-REITs portfolios prefer to allocate growth REITs with low book-to-market ratios. The empirical findings from a modified FF3 model, which additionally incorporates Spain’s gross domestic product (GDP) growth rate, two consumer price index (CPI) macro-factors and three dummy variables, indicates that GDP growth rate and CPI also affect S-REITs’ yields, while investment funds with capital calls have a small influence on S-REITs’ returns.Practical implicationsThe regression results of the standard and extended FF3 model can help researchers understand S-REITs’ risk and return through a general stock pattern. Potential investors are given more information to consider the new Spanish investment vehicle before making a decision.Originality/valueThe paper uses standard techniques but applies them for the first time to the S-REIT market.

Research on the application of Fama and French three-factor and five-factor models in American industry

By conducting ordinary least square estimations using the Fama and French Three-Factor and Five-Factor models on thirty U.S. based industry portfolios, the significant rate of all the variables is compared. Using the comparison, the impacts of the COVID-19 Pandemic on the markets and the Fama and French models are significant. As a result, the significance level of all the independent variables has increased during the COVID-19 Pandemic. The Five-Factor model fares a more substantial increase in efficiency during the Pandemic, and some variables, such as HML and CMA, see tremendous changes. The market becomes less sophisticated during the Pandemic, and the Fama and French Five-Factor model may be more suitable for estimation under certain market environments, contrary to many previous studies.

Research on Mathematical Methods of Improving Fama and French Three-factor Model Based on ETF Factors

Will ETF factors help to improve Fama and French 3 factor Model? Research has examined the Fama French model in different countries and its risk premium in different mathematical ways. This paper reconstructs the Fama-French model by replacing market capitalization size index (SMB) and book-to-market ratio index (HML) to other Exchange Traded Fund (ETF) factors to investigate whether ETF factors will improve the Fama French model. After comparing 15 ETFs, Factors EMD (GDP growth index) and SMG (factor IYC minus factor IYK) are chosen for our adapted risk model because of a relatively low rate of correlation and covariance. 20 sample stocks are selected form various industries and market capitalization size, and used to test to the performance of FFM and the new FFM. The result has been analyzed from 3 different ways: correlation and covariance, R squared, and p value. Although the new model fails to perform better than a traditional FFM, it may be improved by adding more factors or choosing factors which are more representative of the market.

Structural changes in sentiment and returns: evidence from the Trump election

ABSTRACT Given that regime changes may induce new tendencies and behaviours of financial models, we analyse the impact of sentiment variables on stock market returns for time periods before and after Donald Trump’s election. Using the CAPM and Fama–French three-factor model augmented with sentiment measures, we find evidence of a structural break in the 2016 presidential election data. Our results suggest that the relationship between sentiment and abnormal returns is more negative for the periods following the election, and that researchers modelling sentiment and returns should account for structural breaks.

Do Stock Market Risk Factors Explain Mutual Fund Returns? Evidence from Saudi Arabia

This paper examines the risk factors of the Saudi Arabian equity market using an extensive data set. The study demonstrates which risk factors explain mutual fund returns in the largest mutual fund market in the Middle East, a fast-growing economy and a major player in the oil market. This paper also assesses the global and emerging market risk factors. This study analyzes 256 equity funds that operated in Saudi Arabia from January 2006 to July 2017. Time series regression models (e.g., the CAPM, the Fama and French three-factor model and the Carhart four-factor model) are used. In addition, modified versions of the asset pricing models were applied by adding stock market volatility and oil market volatility. The results indicate that the single-factor model, representing the market portfolio, captures most of the mutual funds’ excess returns. Size, value and momentum factors do not enhance the explanatory power of mutual fund returns significantly. The emerging market risk factors capture a small portion of the return variations where most effects were explained by the market risk factor. In explaining these results, we emphasize the important implications for investors, academics and regulators to better understand the risk factors that drive fund returns in a fast-growing emerging market.

Illiquidity Premium in the Indian Stock Market: An Empirical Study

India has the highest global mean illiquidity ratio (Amihud, Hameed, Kang, & Zhang, 2019), which is the primary motivation for this study. This paper aims to price the traded illiquidity and test the well-documented asset pricing models: the capital asset pricing model and the Fama & French’s (1993) three-factor model. The average annual illiquidity premium for the Indian stock market is found to be considerably high when compared to the illiquidity premiums in other developed and developing nations, suggesting that market illiquidity is of more concern to investors in India. It is also found that illiquidity augmented capital asset pricing model and illiquidity augmented Fama & French (1993) three-factor model outperforms the traditional capital asset pricing model and the Fama & French (1993) three-factor models, respectively. It is concluded that illiquidity is definitely a priced component and a key factor in designing asset pricing models for an emerging market such as India’s. Findings of the paper contribute to existing literature on liquidity and asset pricing and help investors design better investment strategies.

The predictive performance of liquidity risk

This paper assesses the explanatory power of the liquidity-risk-based pricing models relative to the Fama–French three-factor model (FF3) and the extensions to the FF3. We find that the liquidity-a...

The Impact of Herding on the Risk Pricing in the Egyptian Stock Exchange

We test the impact of herding behaviour on the risk pricing in the Egyptian Stock Exchange (EGX) by adding an additional risk factor reflecting herding behaviour to the Fama and French three-factor model. We construct a portfolio to mimic an additional risk factor related to herding behaviour, in addition to the original risk factors in the Fama and French three-factor model. The three-factor model will be tested in its original form and re-tested after adding the herding behaviour factor. The study is based on Hwang and Salmon methodology, in which the state space approach based on Kaman’s filter was used to measure herding behaviour. We used monthly excess stock returns of 50 stocks listed on the EGX from January 2014 to December 2018. The results do not support Fama and French model before and after adding the herding behaviour factor, therefore, there is no effect of herding behaviour on the risk pricing in the Egyptian Stock Exchange.

Empirical Test of Fama and French Three-Factor Model in the Egyptian Stock Exchange

We test the empirical validity of the three-factor model of Fama and French in the Egyptian Stock Exchange (EGX) using monthly excess stock returns of 50 stocks listed on the EGX from January 2014 to December 2018. Our findings do not support Fama and French three-factor model, where the coefficient of the beta was insignificant. The “SBM” coefficient and the “HML” coefficient were equal to zero and insignificant, which confirms the absence of the small firm effect and book-to-market ratio effect in the market. We conclude that there is no relation between expected return and Fama-French risk factors.

Fama-French Five-Factor Asset Pricing Model: Testing Validity for Borsa Istanbul and German Stock Exchange

Purpose – Fama and French (2015, 2017) proposed to expand Fama and French (1993) three-factor (portfolio & the overall market factor, firm size, and book-to-market equity) model building two new factors (profitability and investment) on, resulting in a five-factor model. This paper investigates the validity of the five-factor asset-pricing model (FF5F) in BIST30 index in Borsa Istanbul and DAX30 Index in Germany Stock Exchange. Design/methodology/approach – Static panel data analysis is employed by the fixed-effects withingroup estimator for the period 2009Q2-2018Q4 with two different types of market indices BIST30 Index and DAX30 Index in order to investigate the validity of the five-factor asset-pricing model (FF5F). Findings – In overall, results demonstrate that there i s n ot e nough e vidence to s uggest t he robustness of the five-factor model may be valid for stocks listed in DAX30 Index but provide evidence for two-factor model. As for, stocks listed in BIST30, we find enough empirical evidence to suggest that the four-factor model holds rather than the five-factor model. Discussion – Due to the differentiation of developed markets in terms of higher returns and different market dynamics it is therefore of utmost importance to assess the applicability of the FF5F model for developing countries. The findings of the present paper will assist a better evaluation of the risk factors faced by firms and investors.

Sustainable Funds’ Performance Evaluation

The purpose of this research is to consider if the growing popularity of sustainable investment does not create additional risks in investing. Different views on sustainable investments were analyzed to identify different approaches to the main risks. A quantitative analysis was carried out to investigate the possible benefits and advantages of sustainable investment. Without taking into account the social perks of investing in sustainable funds, this study evaluates the performance and economic returns of both sustainable and traditional funds. The research was carried out in two parts by comparing samples of 30 sustainable and 30 traditional funds. Firstly, such methods as annual returns, standard deviations, Sharpe ratios, skewness, and kurtosis were calculated and analyzed. The Capital Asset Pricing Model (CAPM), Fama–French three-factor model and Carhart four-factor model were used to value different market portfolios. The findings of this study suggest that sustainable funds are less risky than traditional funds. However, at the same time, we want to point to pay attention to the period of our analysis and to have in mind that an increasing demand of social responsible assets increases risks as well. However, no clear evidence was found to confirm that sustainable funds can generate higher returns compared to traditional piers or benchmark index. Moreover, after studying different methods the study reveals that the Fama–French three-factor model was the most suitable for explaining the traditional and sustainable funds’ results.

Has Idiosyncratic Volatility Increased? Not in Recent Times

This study successfully replicates the key findings of Campbell, Lettau, Malkiel, and Xu (2001). We document that aggregate idiosyncratic volatility increases over their sample period from 1962 to 1997. In out-of-sample analysis from 1926 to 1962 and 1998 to 2017, we find that idiosyncratic volatility (IV) decreases, suggesting that their finding is sample-specific. We compare their measure of IV with those obtained from models such as the Fama and French (1993) three-factor model and find that they are very similar. The Campbell et al. (2001) volatility measures can only be estimated at the aggregate level. An advantage of asset pricing model-based IVs is that they can be estimated at the stock level. Employing these stock-level IV measures, we examine trends in a variety of IV series and how IV relates to commonly analyzed firm characteristics. In doing so, we provide further insight into IV and its time-series trends.

Whale Optimization Algorithm for Multiconstraint Second-Order Stochastic Dominance Portfolio Optimization.

In the field of asset allocation, how to balance the returns of an investment portfolio and its fluctuations is the core issue. Capital asset pricing model, arbitrage pricing theory, and Fama–French three-factor model were used to quantify the price of individual stocks and portfolios. Based on the second-order stochastic dominance rule, the higher moments of return series, the Shannon entropy, and some other actual investment constraints, we construct a multiconstraint portfolio optimization model, aiming at comprehensively weighting the returns and risk of portfolios rather than blindly maximizing its returns. Furthermore, the whale optimization algorithm based on FTSE100 index data is used to optimize the above multiconstraint portfolio optimization model, which significantly improves the rate of return of the simple diversified buy-and-hold strategy or the FTSE100 index. Furthermore, extensive experiments validate the superiority of the whale optimization algorithm over the other four swarm intelligence optimization algorithms (gray wolf optimizer, fruit fly optimization algorithm, particle swarm optimization, and firefly algorithm) through various indicators of the results, especially under harsh constraints.

Is value premium sector-specific? Evidence from India

PurposeThis paper is an attempt to explore the fact that whether the literature-promised value premium has any sector orientation. The paper tests the relationship between the value premium and Indian sectors: fast-moving consumer goods (FMCG), financials, healthcare, information technology (IT), manufacturing and miscellaneous.Design/methodology/approachThe paper analyses around 210–480 companies listed on BSE-500 for the period of the recent 18 years ranging from March 1999 to March 2017. The paper employed Welch's ANOVA to examine whether the price-to-book market ratio is significantly different across sectors. Two prominent asset pricing models – single factor market model and Fama–French three-factor model – were used to examine the existence of value premium within sectors for full period and two sub-periods.FindingsThe empirical results of the paper suggest that the difference in the P/B ratio both between sectors and within sectors is statistically significant. The results further suggest that the value premium exists within the sectors irrespective of their value-growth orientation.Research limitations/implicationsThe paper is not free from certain limitations. Firstly, due to the non-availability of data in the public domain, the time period before 1999 could not be considered. Secondly, the study has used data pertaining to the Indian stock market only. To add to it, our study has concentrated on BSE-500 companies only; however, the future researchers can include both NSE and BSE companies.Practical implicationsThe paper has important implications for portfolio managers and retail investors following a top-down approach of investing. The portfolio manager can strategically build up the portfolios to concentrate more on the companies belonging to sectors like healthcare, manufacturing and FMCG. Investors following the top-down approach should avoid the underperforming growth stocks belonging to the growth sectors and allocate their funds to value stocks in the growth sector.Originality/valueThe paper is first of its kind to study the relationship between the value premium and Indian sectors. The paper contributes to portfolio management and asset pricing literature for an emerging market.

Information asymmetry and stock returns

PurposeThis study endeavours to examine the relationship between information asymmetry and expected stock returns at the National Stock Exchange (NSE) of India, with a sample of NIFTY 500 stocks for a period ranging from 1st April 2000 to 31st March 2018, by employing three different proxies of information asymmetry: number of transactions, institutional ownership and idiosyncratic volatility.Design/methodology/approachThe return differential amongst information-sorted decile portfolios has been assessed to understand the effect of information risk on stock returns by employing (1) traditional measures of performance evaluation like mean, Sharpe, Treynor and information ratios, (2) regression models like the capital asset pricing (CAPM), Fama and French three-factor, Carhart's four-factor, information-augmented CAPM, information-augmented Fama and French three-factor and information-augmented Carhart's four-factor models and (3) an autoregressive distributed lag (ARDL) model.FindingsThe empirical evidence indicated that as information asymmetry associated with portfolio increases, returns also expand to recompense investors for bearing information risk validating the existence of a significant positive relationship between information asymmetry and expected stock returns at the NSE. Amongst the various asset pricing models employed in this study, the information-augmented Fama and French three-factor model turned out to be the best in explaining cross-sectional variations in portfolio returns.Research limitations/implicationsStrong information premium was observed such that high information stocks outperformed low information stocks which have strong inference for investors and portfolio managers, who all continuously look out for investment strategies that can lend hand to beat the market.Originality/valueEasley and O'Hara (2004) proposed that stocks with more information asymmetry have higher expected returns. Very few studies have examined this relationship between information risk and stock returns that too restricted to the US market only, with a few on other emerging markets. No work has been conducted on the concerned issue in the Indian context. Therefore, it seems to be the first study to explore the relationship between information asymmetry and expected stock returns in the Indian securities market.

Heterogeneous beliefs and idiosyncratic volatility puzzle: evidence from China

PurposeThe purpose of our study is to explore the “idiosyncratic volatility puzzle” in Chinese stock market from the perspective of investors' heterogeneous beliefs. To delve into the relationship between idiosyncratic volatility and investors' heterogeneous beliefs, and uncover the ability of heterogeneous beliefs, as well as to explain the “idiosyncratic volatility puzzle”, we construct our study as follows.Design/methodology/approachOur study adopts the unexpected trading volume as proxies of heterogeneity, the residual of Fama–French three-factor model as proxies of idiosyncratic volatility. Portfolio strategies and Fama–MacBeth regression are used to investigate the relationship between the two proxies and stock returns in Chinese A-share market.FindingsInvestors' heterogeneous beliefs, as an intermediary variable, are positively correlated with idiosyncratic volatility. Meanwhile, it could better demonstrate the negative correlation between the idiosyncratic volatility and future stock returns. It is one of the economic mechanisms linking idiosyncratic volatility to subsequent stock returns, which can account for 11.28% of the puzzle.Originality/valueThe findings indicate that idiosyncratic volatility is significantly and positively correlated with heterogeneous beliefs and that heterogeneous beliefs are effective intervening variables to explain the “idiosyncratic volatility puzzle”.

Effects of Fintech on Stock Return: Evidence from Retail Banks Listed in Indonesia Stock Exchange

This study examines the effect of fintech on retail banks stock return listed in Indonesia Stock Exchange for the period of 2016-2018 as today's new technology lead to the emergence of fintech companies playing the same role as retail banks in the financial industry. This study is conducted quantitatively using monthly data from January 2016 to October 2018 and uses fintech as independent variable, proxied by fintech funding frequency and fintech funding value. Data transformation is conducted due to data volatility. The data of fintech funding, both frequency and value, is transformed into standardized fintech funding and growth of fintech funding. The data is obtained from Crunchbase, while the data of stock returns is obtained from Investing. This study further analyzes the data using Fama French Three-Factor Model and panel data regression. We found that fintech has no significant effect on retail banks' stock returns listed in Indonesia Stock Exchange for the period of 2016-2018. The findings of the study provide some useful insights in understanding fintech companies' current position to retail banks in Indonesia. This study also suggests banking institutions, fintech companies, policy-makers, and others to take advantageous steps in building inclusive financial sectors.

Dividend month premium in the Korean stock market

The dividend month premium is the phenomenon that firms have abnormal returns in predicted dividend month. This study aims to examine the dividend month premium in the Korean stock market, using common stocks listed on the KOSPI and KOSDAQ from January 1999 to December 2016. Abnormal returns are estimated using the following asset price models: capital asset pricing model, Fama–French three-factor model and the Fama–French–Carhart four-factor model. This study finds positive abnormal returns in predicted dividend months, and even for the within-firm portfolio that buys stocks in the predicted dividend months and sells the same stocks in other months. The price impact and the subsequent reversals are greater with lower liquidity and higher dividend yield, implying that the price pressure from dividend-seeking investors affects this dividend month premium. In addition, the anomalies with the pre-declaration stock are smaller than the post-declaration stock, suggesting the necessity to improve the cash dividend policy of post-declaration for market efficiency.

Foreign currency derivative usage and firm value in Bangladesh: comparative analysis between exporters and non-exporters under exchange rate movements

PurposeThe purpose of this paper is to investigate the effect of foreign currency derivative (FCD) usage on firm value. In specific, the authors study the significance of the relationship between FCD usage and firm value for exporters and non-exporters, respectively, with consideration of conditions of exchange rate movements.Design/methodology/approachAs the main empirical test, this paper utilizes the multivariate Tobin's Q model for a panel dataset of 125 non-financial firms, which have been continuously listed on the Dhaka Stock Exchange from 2010–2018. The authors divide the sample firms into two groups: exporters and non-exporters based on theoretical background and estimate the relationship between FCD usage and the firm value measured by Tobin's Q for each firm group. Also, as a complementary test, the Fama–French three-factor model is used to estimate the effect of FCD usage on the monthly portfolio returns of the firms when exchange rate levels and volatility are considered.FindingsFirst, the effect of FCD usage on firm value significantly exists in the Bangladeshi non-financial firms from 2010–2018. Specifically, the FCD effect on firm value is negative (hedging discount) for exporters, whereas the FCD effect is positive (hedging premium) for non-exporters. Second, the multivariate analyses suggest the hedging discount (premium) for exporters (non-exporters) is consistent only when the domestic currency appreciates (depreciates). Third, the FCD effect on firm value is consistently positive for non-exporters when exchange rate volatility is higher.Research limitations/implicationsFurther studies could be conducted with the detailed data of the firms' hedging performance, if they are available. Particularly, the cost and revenue data associated with hedging would help identify evident reasons for exporters' hedging discounts in Bangladesh. Moreover, the best hedging option for maximizing the Bangladeshi firm value could be analyzed with the detailed FCD type data, such as futures, options and swaps. Further refinement of these data would improve institutional capability for substantive growth in frontier markers.Practical implicationsThis paper provides practical implications for corporate managers in charge of managing foreign exchange risk in Bangladesh. First, closer accounting observation is much necessary for the firms to accurately evaluate whether the FCD usage is beneficial in their cash flows because the exporters come to have two large costs: entering foreign markets and carrying FCD program. Second, for better value from using FCDs, the exporters should learn how to utilize appropriate financial derivatives. FCD usage is beneficial when the exporters are fully aware of what their real risks are and the role of appropriate derivatives within its portfolio strategy.Social implicationsA policy reducing the costs of either foreign market entry or FCD usage would be helpful for lessening the FCD discount effect. Also, a long-term policy that enables the born-to-exporters to establish substantive positions in the home market would be helpful for enhancing the cash inflow capability, thereby causing the firm value structure to be strengthened.Originality/valueThe paper has originality because it bridges the gap in the literature. First, the authors find a new empirical result regarding the significant FCD effect on a frontier market, although the FCD effect deals with the small and secondary risk in the previous literatures. Second, finding the contrasting FCD effect between the exporters and non-exporters sheds lights on the importance of firm-specific characteristics for precisely evaluating the FCD effect on firm value. Third, we find that the significant FCD effect is prominent by condition of exchange rate movements, which has been overlooked in prior literature.

The role of efficiency in capital asset pricing: a research on Nasdaq technology sector

PurposeThe aim of this study is to investigate the role of efficiency in capital asset pricing. The paper explores the impact of a four-factor model that involves an efficiency factor on the returns of Nasdaq technology firms.Design/methodology/approachThe paper relies on data of 147 firms from July 2007 to June 2017 to examine the impact of efficiency on stock returns. The performances of the capital asset pricing model (CAPM), Fama–French three-factor model and the proposed four-factor model are evaluated based on the time series regression method. The parameters such as the GRS F-statistic and adjusted R² are used to compare the relative performances of all models.FindingsThe results show that all factors of the models are found to be valid in asset pricing. Also, the paper provides evidence that the explanatory power of the proposed four-factor model outperforms the explanatory power of the CAPM and Fama–French three-factor model.Originality/valueUnlike most asset pricing studies, this paper presents a new asset pricing model by adding the efficiency factor to the Fama–French three-factor model. It is documented that the efficiency factor increases the predictive ability of stock returns. Evidence implies that investors consider efficiency as one of the main factors in pricing their assets.