French Three-factor Model Research Articles

An Empirical Research on the Performance of Asset Pricing Models in the Chinese A-Share Market

Asset pricing remains a cornerstone of financial field, providing a framework to understand the anticipated returns of asset portfolios and individual assets. Its widespread application spans academic discourse and practical financial methodologies. This study conducts an empirical analysis of the Chinese A-share Market, utilizing transaction data from the A-share market spanning from 1994 to 2024. It examines the applicability of the traditional asset pricing models within the Chinese stock market. Through classic regression analyses of the CAPM, the Fama and French three-factor model (FF3), the Fama and French five-factor model (FF5), this study verifies that the FF5 provides a superior explanation of stock expectations for the A-share market during this period compared to other traditional asset pricing models. The conclusions of this study indicate that, among the CAPM, FF3, and FF5 models, the number of parameters taken into account by the model and its capacity to explain asset returns are positively correlated.

Renewable Energy Stocks’ Performance and Climate Risk: An Empirical Analysis

This article studies the relationship between renewable energy stocks’ performance and climate risk. It shows that publicly held renewable energy stocks underperform as a reaction to climate policy information releases, modeled by feed-in tariff (FIT) legislation announcements. The study examined stock price behaviors 2 days before and 30 days after FIT policy announcements. The stock sample used in the study has 3702 firm-day combinations, which included 180 cleantech firms and 32 events from 2007 to 2017. Based on the residual analysis of the sample’s abnormal return, it indicated that the FIT announcements are associated with significant declines in returns. The cumulative abnormal return until Day 18 was a significant −0.83%, while the average abnormal return on the day was −0.16% at normal levels. The study partially excluded the likelihood of a transitory result by varying the measurement horizon. It also adopted both the market model and the Fama–French three-factor models to rule out model misspecification when estimating abnormal returns and thus increased the robustness. In fact, the results were stable to changes in estimating the model’s specifications. In addition, the study compared the portfolio’s performance with mimicking portfolios in terms of size, book-to-market equity (BE/ME), and the firms’ geographic location. It demonstrated that the documented anomaly of the portfolio of renewable energy companies is robust.

A novel integration of the Fama–French and Black–Litterman models to enhance portfolio management

We propose a novel portfolio model integrating the Fama–French three-factor model into the Black–Litterman framework, enabling efficient investment strategies. The model surpasses traditional benchmarks, significantly increasing alpha, minimizing estimation error, and improving diversification. Performance improvements are shown by a tripled Sharpe ratio and doubled Certainty Equivalent Return compared to standard models. It maintains stability across different parameters and economic climates, leveraging improved weight adjustment to reduce estimation errors and withstand market volatility. It provides a new perspective for portfolio construction, leveraging long-term insights from asset pricing theory with significant implications.

Explaining the time series of stock returns

Abstract: 
 Objective: In this paper, we test and compare the explanatory power of the two asset pricing models: the conventional CAPM and the empirical Fama and French three-factor model (1993) in the Moroccan stock market.
 Method: According to the Fama and French (1993) methodology, we analyze monthly data covering the sample period from July 2012 to June 2020.
 Results: The main findings support the superiority of the Fama and French three-factor model. The mimic risk factors pertained to the size and the book-to-market ratio have a significant role in explaining the Moroccan returns. Moreover, results show the existence of weak value effect but significant size effect. Despite the preeminence of the Fama and French model in describing the time-series of sock returns, the model leaves an unexplained fraction of the variation of Moroccan stock returns.
 Originality/Relevance: Our study is the first to compare the two popular models in the financial literature in the Moroccan stock which is an emerging market. Thus, our study corroborates others studies conducted in emerging markets and confirms the hypothesis that the characteristics of those markets impact the explanatory power of asset pricing models.

Research on Optimizing Pension Planning Allocations

This article examines two ways of pension allocation, choosing the best opportunity mix based on Fama and the French three-factor model to maximize returns while satisfying each portfolio category and other investment conditions. The database used by the author is based on the excess returns of 8 different stocks from October 2018 to January 2022. This article studies the relationship between different stocks by calculating the variance, standard deviation and covariance of different stocks, and divides stocks into large-cap stocks, small-cap stocks, value stocks, and growth stocks. The author calculated the optimal Sharpe ratio. Empirical results show that the sharpe ratio value obtained from the investment portfolio can be concluded that when people live for more than 20 years after retirement, they can choose to receive pensions every year. If your life expectancy after retirement cannot reach 20 years, it is recommended to withdraw your pension in one lump sum. However, this article shows that results change when using different portfolio approaches because of data limitations.

Using the Capital Asset Pricing Model and the Fama–French Three-Factor and Five-Factor Models to Manage Stock and Bond Portfolios: Evidence from Timor-Leste

Timor-Leste is a new country still in the process of economic development and does not yet have a capital market for stock and bond investments. These two asset classes have been invested in international capital markets such as the US, the UK, Japan, and Europe. We examine the performance of the capital asset pricing model (CAPM) and the Fama–French three-factor and five-factor models on the excess returns of Timor-Leste’s equity and bond investments in the international market over the period 2006 to 2019. Our empirical results show that the market factor (MKT) is positively and significantly associated with the excess returns of the CAPM and the Fama–French three-factor and five-factor models. Moreover, the two variables Small Minus Big (SMB) as a size factor and High Minus Low (HML) as a value factor have a negative and significant effect on the excess returns in the Fama–French three-factor model and five-factor model. Further analysis revealed that the explanatory power of the Fama–French five-factor model is that the Robust Minus Weak (RMW) factor as a profitability factor is positively and significantly associated with excess returns, while the Conservative Minus Aggressive (CMA) factor as an investment factor is insignificant.

An Empirical Research of Asset Pricing Models in the US Market under COVID-19

Asset pricing theory has been a key area of research in finance. Since the in-troduction of CAPM, asset pricing models have been very widely used. Re-searchers have discovered many phenomena that cannot be explained by the CAPM model, so they have made many refinements to the asset pricing model and developed various improved versions that can better explain stock returns. The Fama and French three-factor model (FFTFM) and the five-factor model (FFFFM) are two of the most classic and most used asset pricing models. However, as time goes by and financial markets continue to evolve, many scholars have questioned whether traditional asset pricing models are still valid. Starting from the theoretical explanation of CAPM, FFTFM, and FFFFM factor selection, this paper uses the stock market data from 2000 to March 2023 to divide stocks into six portfolios based on their size and book value and conduct regressions according to the above three models respectively to evaluate and compare the recent performance of these models. In addition, this paper also performs separate regressions using data from the novel coronavirus epidemic period in particular to verify the robustness of the model to different market environments. According to the results of this paper, the FFFFM model has the best explanatory power. The role of the factors in the model on stock returns varies with portfolio selec-tion, i.e., firm size and book value, and the market environment also has an impact on the significance of the factors, leaving room for improvement in the model to cope with particular markets, but overall, FFFFM is still effec-tive in explaining present market stock prices.

Fama and French three and six-factor models: Evidence from Indian stock exchange

This study attempts to compare the performance of Fama–French three-factor model (FFTFM) and Fama and French six-factor model (FFSFM) in predicting the variations in expected returns of Nifty-100 listed stocks. Only 5/6 of the total listed companies are chosen, while the remaining 1/6 are ignored because they are not listed for the whole study period. The stocks are divided into two size groups and three groups based on B/M, OP, Inv and MOM using independent sorts to create 24 portfolios. The monthly average returns of the MC-MOM portfolios increase as momentum increases, in contrast to MC-B/M and MC-Inv portfolios. Almost all the portfolios with high returns are paired with significant risk, apart from the BM portfolio in size and profitability group. The findings prove that the FFSFM outperforms FFTFM on all the GRS test parameters. However, there is no significant improvement in explanatory power over the FFTFM.

Revisiting the relationship between idiosyncratic risk and stock returns: a quantile regression analysis in the context of an emerging market

PurposeThe relationship between idiosyncratic risk and stock return has been debated for decades; this study reexamined this relationship in the Pakistani stock market by using the quantile regression approach along with the prospect theory.Design/methodology/approachThe present study is quantitative, and secondary data obtained from an emerging market are used. The quantile regression method allows the estimates of idiosyncratic risk to vary across the entire distribution of stock returns, i.e. the dependent variable. In this study, the standard deviation of regression residuals from the Fama and French three-factor model was used to measure idiosyncratic risk. Convenience sampling is employed; the sample consists of 82 firms listed on the KSE-100 index, with 820 annual observations for the ten years from 2011 to 2020. After computing results by using quantile regression, the study's findings, ordinary least squares (OLS) and least sum of absolute deviation (LAD) regression techniques are also compared.FindingsThe quantile regression estimation results indicate that idiosyncratic risk is positively correlated with stock returns and that this relationship is contingent on whether prices are rising or falling. Consistent with the prospect theory, the finding suggests that stock investors tend to avoid risk when they anticipate a loss but are more willing to take risks when they anticipate a profit. The results of the OLS and LAD regressions indicate that the method typically employed in previous studies does not adequately describe the relationship between idiosyncratic risk and stock return at extreme points or across the entire distribution of stock return.Originality/valueThese empirical findings shed new light on the relationship between idiosyncratic risk and stock return in Pakistani stock market literature.

Empirical Asset Pricing Models: Evidence from the Chinese Stock Market

This study constructs conventional asset pricing models including the CAPM, the Fama and French three-factor model (FF3 hereafter), the Carhart four-factor model (FFC4 hereafter), and the Fama and French five-factor model (FF5 hereafter). Additionally, a six-factor model (FF5 model augments the Carhart momentum factor) is also constructed and it outperforms other conventional asset pricing models in the Chinese stock market while explaining the returns variation of cross-sectional indices and individual stocks. However, the explanatory power of models varies in explaining indices and individual stocks because of their own specificity. The models can capture most at 69.05% and least at 3.03% of the variation of the return in certain individual stocks. In light of indices, models account for the largest proportion of the variation of the return at 96.83% and the smallest proportion at 85.28%. Moreover, the predictive ability of the six-factor model is confirmed in this study, which implies the validity of constructed factors and the model.

Durable Consumption-Based Asset Pricing Model with Foreign Factors for the Korean Stock Market

This paper explores the implications of consumption heterogeneity between domestic and foreign investors on the cross-section of stock returns in a host country. We argue that foreign investors in a small open economy integrated into global financial markets may face consumption risk, which could result in risk premia being reflected in stock returns. To account for the potential influence of foreign investors on asset prices in a host country, we develop a two-country durable consumption model under market incompleteness, which extends the one-country durable consumption model. The proposed model includes both domestic and foreign pricing factors. We investigate the empirical performance of our model with Fama–French portfolios for Korea, taking U.S. investors as representative foreign investors. The empirical results advocate the two-country durable consumption model, confirming the significant role of foreign factors in the cross-section of domestic stock returns. Additionally, R2 tests conducted with different sets of test assets show that the explanatory power of our model is comparable to that of the Fama–French three-factor model.

Nonlinear dependencies in the Fama and French three-factor model

ABSTRACT This article addresses the topic of nonlinear dependencies in the Fama and French three-factor model. Five time-series models, including nonlinear terms, are assessed using US and European data and compared with a benchmark linear model. The analysis found that nonlinear dependencies in the modified Fama and French three-factor model were statistically significant and provided additional explanatory power for the underlying return-generating process. However, these nonlinear dependencies are of secondary importance in the economic sense.

The Empirical Explanatory Power of CAPM and the Fama and French Three-Five Factor Models in the Moroccan Stock Exchange

This study empirically tests and compares the performances of three famous financial asset valuation models in the Moroccan stock exchange: CAPM, the Fama and French three-factor model, and the Fama and French five-factor model. Our sample considers monthly data covering the sample period of July 2002 to June 2020. The main findings reveal that the GRS test typically rejects each of the examined model. On the basis of our analysis, we find that the value effect is more pronounced than the size effect. However, profitability and investment effects are almost absent. Regarding the factor spanning tests, the results show that the value factor was not redundant. Beyond this, the size and investment factors are the redundant factors. In Morocco, the market factor is the most powerful factor, perhaps assisted by value and profitability factors. Although the CAPM performs poorly in capturing the variation in Moroccan returns, the market factor continues to play an important role, even after adding other factors. Overall, all the tested models were improved slightly, but leave part of the variation in Moroccan stock returns unexplained.

Pricing Ability of Carhart Four-Factor and Fama–French Three-Factor Models: Empirical Evidence from Morocco

In this study, the reliability of the Fama–French Three-Factor model (FF3F) and the Carhart Four-Factor model (C4F) is examined thoroughly. In order to determine which of the asset pricing models is the best to explain portfolio returns on the Moroccan share market, these two models are indeed evaluated in the Moroccan market. Additionally, it is worth mentioning that five years of monthly data from the firms that listed on the Casablanca Stock Exchange are used in this research, as well over the period of nine years. The results of this inquiry show that these models barely have a partial hold on the Casablanca Stock Exchange (CSE), which limits their ability to predict the cross-sections of returns. In accordance with this, the C4F model has somewhat greater explanatory power than the FF3F Model. Moreover, our research adds to the body of knowledge by inserting two learned material asset pricing theories to the proof in the market, which is still evolving, and where distinctive anomalistic traits still exist (the CSE).

Research on interaction of innovation spillovers in the AI, Fin-Tech, and IoT industries: considering structural changes accelerated by COVID-19

This paper aims to probe the influence of innovation spillovers in the artificial intelligence (AI) and financial technology (Fin-tech) industries on the value of the internet of things (IoT) companies. Python was utilized to download public information from Yahoo Finance, and then the GARCH model was used to extract the fluctuations of cross-industry innovation spillovers. Next, the Fama–French three-factor model was used to explore the interactive changes between variables. The panel data regression analysis indicates that the more firms accept innovation spillovers from other industries, the better the excess return; however, this effect differs because of industrial attributes and the environmental changes induced by COVID-19. Additionally, this study finds that investing in large-cap growth stocks of IoT firms is more likely to yield excess returns. Finally, the study yields lessons for policy leverage to accelerate the upgrading and transformation of innovation-interactive industries by referring to the practices of Singapore and South Korea.

Variação do dividend-yield como critério de seleção de ativos em estratégias de momento de fundos de investimentos imobiliários brasileiros

ABSTRACT We aimed at showing the usage of the dividend-yield (DY) variation as a criterion for selecting Brazilian real estate investment trusts (BR-REITs) in momentum strategies. The identification of momentum in BR-REITs with this selection criterion is, to the best of our knowledge, new and gives rise to different strategies that seize abnormal returns. This study allows a new understanding of the dynamics between prices and dividend payments, which compose BR-REITs returns. It is of major importance, considering the relevance of the DY ratio for the asset class. The studied strategies delivered results above the industry’s index with expressive magnitude, are of simple elaboration, and can be applied by any individual or institutional investor. Portfolios’ performances were measured by Sharpe ratio (SR), alpha of the Fama and French three-factor model, and excess returns obtained in relation to the BR-REITs’ index. Statistical tests were applied to verify the significance of the results. This study showed that strategies around the momentum effect that buy (sell) BR-REITs with greater (smaller) DY variations in previous months tended to have superior performance to the industry’s index.

Contrarian Profits and the Overreaction Hypothesis: The Case of the Athens Stock Exchange

This paper investigates the existence of contrarian profits and their sources for the Athens Stock Exchange (ASE). The empirical analysis decomposes contrarian profits to sources due to common factor reactions, overreaction to firm-specific information, and profits not related to the previous two terms, as suggested by Jegadeesh and Titman (1995). Furthermore, in view of recent evidence that common stock returns are related to firm characteristics such as size and book-to-market equity, the paper decomposes contrarian profits to sources due to factors derived from the Fama and French (1993, 1996) three-factor model. For the empirical testing, size-sorted sub-samples that are rebalanced annually are employed, and in addition, adjustments for thin and infrequent trading are made to the data. The results indicate that serial correlation is present in equity returns and that it leads to significant short-run contrarian profits that persist even after we adjust for market frictions. Consistent with findings for the US market, contrarian profits decline as one moves from small stocks to large stocks, but only when market frictions are considered. Furthermore, the contribution to contrarian profits due to the overreaction to the firm-specific component appears larger than the underreaction to the common factors.

Portfolio Optimization for US. Stock with Mean-variance Model, CAPM, Fama French Three-factor Model

Applying modern investment theories to construct investment portfolios is a crucial way for investors to reduce risks and obtain high returns in the investment market. This paper selects eight stocks from eight industries of the US stock market and constructs a portfolio based on their historical return data over the past five years. This study uses the CAPM model and the Fama French three-factor model to estimate the expected returns of these eight stocks, and then applies the mean-variance model to construct the optimal risky portfolio under both expectations. Under the CAPM model, the expected monthly returns for these eight stocks are BKNG (1.05%), EQR (0.80%), MPC (1.38%), NTDOY (0.64%), ON (1.44%), PFE (0.68%), SBUX (0.86%) and FCX (1.60%) respectively. Under Fama-French three factor model, the expected monthly returns for these eight stocks are BKNG (1.21%), EQR (0.90%), MPC (2.06%), NTDOY (0.55%), ON (1.82%), PFE (0.60%), SBUX (0.82%) and FCX (1.96%) respectively. The optimal portfolio weights obtained by using CAPM model estimation results are BKNG (7.97%), EQR (23.72%), MPC (6.02%), NTDOY (11.61%), ON (8.24%), PFE (18.66%), SBUX (10.61%) and FCX (13.16%) respectively. Under Fama French three factor model, the weight distribution of the portfolio is as follows BKNG (3.01%), EQR (27.04%), MPC (33.89%), NTDOY (2.40%), ON (15.85%), PFE (4.98%), SBUX (0.00%) and FCX (12.83%). These results can provide a reference for investors who are willing to invest in US stock market, which will help them reduce investment risks and increase returns.

How to allocate portfolio weight based on the FF3F model

Selecting the correct stocks and funds is essential for portfolio management and allocation. In order to reduce the risk of the portfolio, it is better to diversify the assets and select the stocks within more than one sector. Another step would be setting the portfolio with the firefighter case or without it. The firefighter case illustrates that we suppose there is a firefighter who has 25 years of service as a firefighter who will be retired in Florida. The Florida government gives the retired firefighter two choices. He takes the lump-sum payout and invests his nest egg and the lump sum in supporting him throughout his retirement. Another one is that he takes the pension benefit and invests his nest egg in supplementing the pension benefit. In this case, we compared those two and finally selected the one in which he maintained the pension and made the pension weight precisely equal to 71%. The Sharpe ratio for this scenario is relatively higher than the another. Moreover, choosing the correct financial model. Comparing the pros and cons between the CAPM model and the Fama French Three-Factor model, we found that the Fama French Three-Factor model is more related to reality and includes the market risk, making the portfolios more accurate and reliable.

Representative Bias and Pairs Trade: Evidence From S&P 500 and Russell 2000 Indexes

This study tests whether pairs trade conditional on representative bias in the options and stock markets leads to abnormal returns. While previous literature on representativeness focuses on a single index, S&P 500 and Russell 2000 indexes are used to examine the extent to which representative bias arises due to a pattern of similar information shock in the three analyzed periods. The empirical results of the options market lend little support to the representativeness anomalies because Russell 2000 index, relative to S&P 500 index, does not adjust to a sequence of information shocks in the 2020 economic downturn inflicted by the coronavirus pandemic, despite the asymmetrical responsiveness to information shock over the sample period of 2004 to 2020, and during the 2008 global financial crisis. However, the empirical findings of the stock market verify, to some degree, the existence of representative bias during the sample period of 2004 to 2020. To examine whether asymmetrical representativeness in the options market or representativeness in the stock market yields abnormal returns, pairs trade is designed to exploit riskless profits via buying S&P 500 index and selling Russell 2000 index. Based on the Fama and French three-factor model, the empirical evidence is in support of market efficiency because the pairs trading strategy cannot generate positive abnormal returns in both options and stock markets.