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Academic literature on the topic 'Carhart's four-factor model'
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Journal articles on the topic "Carhart's four-factor model"
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Mohanty, Sunil K., and Mohan Nandha. "Oil Shocks and Equity Returns: An Empirical Analysis of the US Transportation Sector." Review of Pacific Basin Financial Markets and Policies 14, no. 01 (2011): 101–28. http://dx.doi.org/10.1142/s0219091511002159.
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The main purpose of this paper is to investigate the relation between oil price movements and stock returns in US transportation companies. We estimate oil price risk exposures of the US oil transport sector at the firm level as well as at the industry level over November 1999 to February 2008 period using the Fama–French–Carhart's (1997) four-factor asset pricing model augmented with oil price and interest rate factors. Overall, the results of our study suggest that oil price exposures of firms in the US transportation sector vary across firms and over time. The varying effects of oil shocks on stock returns may be attributed to several factors such as differences among firms' cost structure, financial policies, diversification activities, and hedging strategies.
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Sehgal, Sanjay, and Sonal Babbar. "Evaluating alternative performance benchmarks for Indian mutual fund industry." Journal of Advances in Management Research 14, no. 2 (2017): 222–50. http://dx.doi.org/10.1108/jamr-04-2016-0028.
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Purpose The purpose of this paper is to perform a relative assessment of performance benchmarks based on alternative asset pricing models to evaluate performance of mutual funds and suggest the best approach in Indian context. Design/methodology/approach Sample of 237 open-ended Indian equity (growth) schemes from April 2003 to March 2013 is used. Both unconditional and conditional versions of eight performance models are employed, namely, Jensen (1968) measure, three-moment asset pricing model, four-moment asset pricing model, Fama and French (1993) three-factor model, Carhart (1997) four-factor model, Elton et al. (1999) five-index model, Fama and French (2015) five-factor model and firm quality five-factor model. Findings Conditional version of Carhart (1997) model is found to be the most appropriate performance benchmark in the Indian context. Success of conditional models over unconditional models highlights that fund managers dynamically manage their portfolios. Practical implications A significant α generated over and above the return estimated using Carhart’s (1997) model reflects true stock-picking skills of fund managers and it is, therefore, worth paying an active management fee. Stock exchanges and credit rating agencies in India should construct indices incorporating size, value and momentum factors to be used for purpose of benchmarking. Originality/value The study adds new evidence as to applicability of established asset pricing models as performance benchmarks in emerging market India. It examines role of higher order moments in explaining mutual fund returns which is an under researched area.
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Khan, Muhammad Saifuddin, and Md Miad Uddin Fahim. "THE FOUR-FACTOR MODEL AND STOCK RETURNS IN BANGLADESH." International Journal of Accounting & Finance Review 6, no. 2 (2021): 133–49. http://dx.doi.org/10.46281/ijafr.v6i2.1122.
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For determining the expected return, and asset pricing, CAPM (Capital asset pricing model) is being used dominantly grounded on only the market (systematic) risk-factor though several anomalies have been revealed in this model. Fama and French (1993) have addressed those anomalies and developed the Three-factor model by combining size and value factors besides market factors. Over time, Carhart (1997) has further developed a model addressing momentum factor besides the three factors of Fama and French (1993) which is known as the Carhart four-factor model. Though several kinds of research have been conducted on the CAPM and three-factor model, little works have been accompanied by the Carhart four-factor model in an evolving market like Bangladesh. The goal of this work is to examine the validity of the Carhart four-factor model and examine the loftier explanatory power in Dhaka Stock Exchange (DSE). From the regression analysis of the Carhart model, we have found that market, size, value, and momentum explain the excess stock return. This study indicates that the Carhart model has the lowest GRS F-statistic, highest adjusted R-squared, and lowest Sharpe ratio in contrast to the CAPM and three-factor model which indicates the superior explanatory power and statistical validity of the Carhart model.
 JEL Classification Codes: G12, G13, G14.
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Boamah, Nicholas Addai. "Robustness of the Carhart four-factor and the Fama-French three-factor models on the South African stock market." Review of Accounting and Finance 14, no. 4 (2015): 413–30. http://dx.doi.org/10.1108/raf-01-2015-0009.
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Purpose – The purpose of this study is to explore the applicability of the Fama–French and Carhart models on the South African stock market (SASM). It examines the ability of the models to capture size, book-to-market (BM) and momentum effects on the SASM. The paper, additionally, explores the ability of the Fama–French–Carhart factors to predict the future growth of the South African economy. Design/methodology/approach – The paper relies on data of 848 firms from January 1996 to April 2012 to examine the size, BM and momentum effects on the SASM. The paper constructs the test assets from a 3 × 3 sort on size and BM and a 3 × 3 sort on size and momentum. The paper estimates momentum as the past six-months’ cumulative return. The momentum portfolios are monthly rebalanced. Additionally, the size and BM portfolios are formed annually at the end of each June. Findings – Evidence is provided that size, BM and momentum effects exist on the SASM; also, the small- and high-BM firm portfolios, respectively, appear riskier than the big- and low-BM firm portfolios. The paper provides evidence of past winners outperforming past losers aside from the small-firm group. Additionally, the models only partially capture the size and value effects on the SASM. The Carhart model partly captures the momentum effects, but the Fama–French model is unable to describe the returns to the momentum-sorted portfolios. The evidence shows that the models’ factors predict future gross domestic product growth. Originality/value – The models do not fully describe returns on the SASM; any application of the models on the SASM should be done with caution. The Carhart model better describes returns than the Fama–French model on the SASM. The Fama–French–Carhart factors may relate to the underlying economic risk of the South African economy.
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Kiymaz, Halil. "Factors influencing SRI fund performance." Journal of Capital Markets Studies 3, no. 1 (2019): 68–81. http://dx.doi.org/10.1108/jcms-04-2019-0016.
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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.
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Pandey, Asheesh, Sanjay Sehgal, Amiya Kumar Mohapatra, and Pradeepta Kumar Samanta. "Equity market anomalies in major European economies." Investment Management and Financial Innovations 18, no. 2 (2021): 245–60. http://dx.doi.org/10.21511/imfi.18(2).2021.20.
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This paper investigates five leading equity market anomalies – size, value, momentum, profitability, and asset growth, for four Western European markets, namely, Germany, France, Italy and Spain, from January 2002 to March 2018. The study tests whether these anomalies reverse under different macro-economic uncertainty conditions, and evaluates if strategies based on time diversification can be formed using these equity market anomalies. Market anomalies were tested using four major asset pricing models – the Capital Asset Pricing Model, the Fama-French three-factor model, the Carhart model, and the Fama-French five-factor model. Macro-economic uncertainty was tested using two proxies, namely VIX and default premiums. Time diversified strategies were examined by estimating Sharpe ratios of combined portfolios formed by combining winner univariate portfolios. Value effect in Germany, Size effect in France and Profitability effect in Italy and Spain provide the highest unadjusted returns on long side strategies. No significant reversal of these anomalies was found under different macroeconomic uncertainties. Asset pricing tests show that CAPM works well for Spain and Italy, while Carhart’s model explains returns in Germany. The Fama-French five factor model does not seem to be a good descriptor of asset pricing for data. No suitable model for explaining asset returns is identified for France. Finally, it is observed that some of the equity market anomalies seem to be countercyclical and therefore provide time diversification opportunities. The study has implications for academicians, investors, and policy makers by providing insights for developing profitable investment strategies and highlighting the efficacy of alternative models as performance benchmarks.
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Hassan, Abul, Abdelkader Chachi, and Mahfuzur Rahman Munshi. "Performance measurement of Islamic mutual funds using DEA method." Journal of Islamic Accounting and Business Research 11, no. 8 (2020): 1481–96. http://dx.doi.org/10.1108/jiabr-04-2018-0053.
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Purpose The purpose of this study is to update the investment literature by providing latest evidence of performance of Islamic mutual funds by using global sample mutual funds data to support with empirical facts. Design/methodology/approach This study analyzes the comparative performance of Islamic and conventional mutual funds by using capital asset pricing model, Fama & French’s three-factor model and Carhart’s four-factor model. Further, the study tested the coskenwness effect by using data envelopment analysis approach. Findings The authors find evidence that when size of the funds is controlled, Islamic investment underperform the conventional mutual funds in four out of six models. The size of underperformance varies from model to model: from 32 basis points in the Carhart’s four-factor model with the skewness factor to two basis points at the Fama and French’s three-factor model. Also the study finds that alpha(s) are only insignificant for conventional mutual funds when the skewness factor is included in the regression. While comparing the loading on Islamic mutual funds, results show that Islamic mutual funds are less risky than conventional mutual funds when they are controlled for skewness. Originality/value This study uses the different factor models of performance evolution which help in overcoming weakness of measuring the Islamic mutual funds’ performance.
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Candika, Yossy Imam. "TESTING THE EFFECTIVENESS OF THE CARHART MODEL FOUR FACTORS ON EXCESS RETURNS IN INDONESIA." TIJAB (The International Journal of Applied Business) 1, no. 1 (2019): 60. http://dx.doi.org/10.20473/tijab.v1.i1.2017.60-74.
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One crucial information for investor in making their investment decision is to estimate asset-pricing level. The basic principle would be high risk, high return. This research is using Carhart model (1997): market return, size, book to market, and momentum. The goal of this research is to test and analyze the influence of Carhart Four Factor Model toward Indonesian stock' excess return. Dependent variable used in this research is stock' excess return, while independent variable used are Carhart four factor model. Population used is all non-financial firms listed in Bursa Efek Indonesia from year 2010 to 2012. Total samples are 150 firms. To test the model in this research, we firstly create ten portfolio groups by combining size-book to market and size-momentum. We use multiple regression analysis by using 10 regression analysis model based on previously built 10 portfolio combinations. Statistical test on variable excess market return toward stock return on 10 portfolio shows that there exist positive significant relationship to all models. SMB is significantly impacting portfolio return to 5 models. HML is significantly impacting portfolio return to 6 models. UMD impacting positively significant toward portfolio return on 2 models. Keywords: stock excess return, Carhart four factor model, market return, size, book to market, momentum.
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Mahmud, Delvira. "Testing the Four Factors of the Carhart Model Against Excess Return of Shares in Companies Registered in the Kompas 100 Index for the 2014-2016 Period." Jambura Science of Management 1, no. 1 (2019): 16–20. http://dx.doi.org/10.37479/jsm.v1i1.1983.
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The researcher intends to test the four carhart factor model of stock excess return in companies incorporated in Kompas 100 for the 2014-2016 period. Regression analysis was performed on four carhart factor models, namely market returns, firm size, book to market, and momentum towards excess return. The results of this study indicate that in the partial hypothesis testing market return, firm size, and book to market equty variables significantly influence the excess return, while the momentum variable does not significantly influence the magnitude of excess return.Keywords: Four factors, market returns, firm size, book to market equity, momentum, excess stock returns
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Costa, Bruce A., Keith Jakob, Scott J. Niblock, and Elisabeth Sinnewe. "Australian Stock Indexes and the Four-Factor Model." Applied Finance Letters 3, no. 1 (2014): 10. http://dx.doi.org/10.24135/afl.v3i1.17.
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Stock indexes are passive ‘value-weighted’ portfolios and should not have alphas which are significantly different from zero. If an index produces an insignificant alpha, then significant alphas for equity funds using this index can be attributed solely to manager performance. However, recent literature suggests that US stock indexes can demonstrate significant alphas, which ultimately raise questions regarding equity fund manager performance in both the US and abroad. In this paper, we employ the Carhart four-factor model and newly available Asian-Pacific risk factors to generate alphas and risk factor loadings for eight Australian stock indexes from January 2004 to December 2012. We find that the initial full sample period analysis does not provide indication of significant alphas in the indexes examined. However, by carrying out 36-month rolling regressions, we discover at least four significant alphas in seven of the eight indexes and factor loading variability. As previously reported in the US, this paper confirms similar issues with the four-factor model using Australian stock indexes and performance benchmarking. In effectively measuring Australian equity fund manager performance, it is therefore essential to evaluate a fund’s alpha and risk factors relative to the alpha and risk factors of the appropriate benchmark index.