scholarly journals Profitability of Style based Investment Strategies: Evidence from India

2017 ◽  
Vol 9 (2) ◽  
pp. 1 ◽  
Author(s):  
Srividya Subramaniam ◽  
Gagan Sharma ◽  
Srishti Sehgal
Keyword(s):  
Factor Model ◽  
Explanatory Power ◽  
Investment Strategy ◽  
Investment Strategies ◽  
Price Momentum ◽  
Portfolio Managers ◽  
Earnings Momentum ◽  
Fama And French ◽  
Investment Styles ◽  
Three Factor

In this paper, we aim to identify profitable investment styles on the Indian stock market by using various combinations of important stock pricing anomalies consisting of. size, value, volume, profitability, earnings surprises, short term and long term prior returns. Using NSE200 stocks, three different investment styles viz. univariate, independent bivariate and conditional bivariate are constructed for the period July 2005-June 2016.Results show that on an absolute return basis, bivariate strategies do not seem to outperform univariate strategies. The unifactor CAPM is able to absorb 42% of the returns owing to the explanatory power of beta. After adjusting for risk using the three factor Fama and French (1993) model, 42% of the alphas are explained. However, additional risk factors from the Carhart (1997) model and Fama and French (2015) model do not provide any incremental explanatory power over the three factor model, recommending the use of the latter as a baseline to evaluate investment strategies in India. The highest supernormal returns of 1.1% per month are obtained from combining attributes and employing the conditional bivariate investment strategy viz.E2L1 (earnings momentum-Liquidity), M2S1 (price momentum-size), E2M3 (earnings momentum-price momentum). The findings are pertinent to portfolio managers, financial regulators and other stakeholders.

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

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhenyu Su ◽  
Paloma Taltavull
Keyword(s):  
Growth Rate ◽  
Factor Model ◽  
Explanatory Power ◽  
Gdp Growth ◽  
Size Factor ◽  
Content Type ◽  
Gdp Growth Rate ◽  
Fama And French ◽  
Three Factor

Purpose This 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/approach The autoregressive distributed lag model is used for the empirical analysis to test long-term stable relationships between variables. Findings The 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 implications The 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/value The paper uses standard techniques but applies them for the first time to the S-REIT market.

Overreaction evidence from large-cap stocks

2014 ◽  
Vol 13 (4) ◽  
pp. 310-325 ◽  
Author(s):  
Tibebe Abebe Assefa ◽  
Omar A. Esqueda ◽  
Emilios C. Galariotis
Keyword(s):  
Stock Returns ◽  
Factor Model ◽  
Investment Strategy ◽  
Past Performance ◽  
Content Type ◽  
Multifactor Models ◽  
Contrarian Strategy ◽  
Fama And French ◽  
Investment Portfolios ◽  
Three Factor

Purpose – The purpose of this paper is to assess the performance of a contrarian investment strategy focusing on frequently traded large-cap US stocks. Previous criticisms that losers’ gains are not due to overreaction but due to their tendency to be thinly traded and smaller-sized firms than winners are addressed. Design/methodology/approach – Portfolios based on past performance are constructed and it is examined whether contrarian returns exist. The Capital Asset Pricing Model (CAPM), Fama and French three-factor model and the Carhart’s (1997) momentum portfolio are used to test whether excess returns are feasible in a contrarian strategy. Findings – The results show an asymmetric performance following portfolio formation. Although both, winners and losers portfolios, have gains during holding periods, losers outperform winners at all times, and with a differential of up to 29.2 per cent 36 months after portfolio formation. Furthermore, the loser and the winner portfolios’ alphas are significant, suggesting that the CAPM and the multifactor models are unable to explain return differentials between winners and losers. Our evidence supports two main conclusions. First, stock market overreaction still holds for a sample of large firms. Second, this is robust to the Fama and French’s (1993, 1996) three-factor model and Carhart’s (1997) momentum portfolio. Findings emphasize the relevance of a contrarian strategy when rebalancing investment portfolios. Practical implications – Portfolio managers can improve stock returns by selling past winners and buying previous loser large-cap US stocks. Originality/value – This paper is the first, to the authors’ knowledge, to examine frequently traded large-cap US stocks to avoid infrequent trading and size concerns.

Investment styles and the multifactor analysis of market timing skill

2017 ◽  
Vol 13 (1) ◽  
pp. 21-35
Author(s):  
Jarkko Peltomäki
Keyword(s):  
Factor Model ◽  
Market Timing ◽  
Investment Strategy ◽  
Investment Strategies ◽  
Analysis Model ◽  
Content Type ◽  
Multifactor Models ◽  
Multifactor Model ◽  
Investment Style ◽  
Investment Styles

Purpose The purpose of this paper is to present and demonstrate how the use of a multifactor model in the analysis of market timing skill can be misleading because the use of a multifactor model does not suit all investment styles equally well. If the factors of the analysis model do not span the portfolio holdings of a fund with less conventional investment strategy, the use of a multifactor model may even deteriorate the overall inference in measuring the market timing skill of a large sample of funds. Design/methodology/approach This study investigates the limitations of multifactor models in the analysis of market timing skill by applying the traditional Treynor-Mazuy and Henriksson-Merton analysis models of market timing skill using a set of “placebo” funds which are “natural” passive market timers. Findings The results of the study show that the incorporation of the Carhart four-factor model into the analysis of market timing skill considerably reduces the percentage of significant market timing results. But, as expected, the reduction of bias is not equal for different investment styles, and it works best when the factors of the analysis model are related to the investment style of the placebo portfolio. Practical implications This style-related limitation of multifactor models in the analysis of market timing skill may result in detecting funds with less conventional investment strategies as market timers since the factors used in the analysis are not likely to span their investment styles. Originality/value This study shows that the use of a multifactor model may lead to inferring passive market timers with less conventional investment styles as market timers. In addition, the findings of the study leave option replication approaches as more preferable bias corrections than multifactor extensions.

Who is King in Factor Zoo? Case of the Chinese Stock Market

2020 ◽  
Vol 14 (2) ◽  
pp. 77-102
Author(s):  
Simon M. S. So
Keyword(s):  
Asset Pricing ◽  
Stock Market ◽  
Stock Returns ◽  
Factor Model ◽  
Five Factor Model ◽  
Investment Strategy ◽  
Capital Asset Pricing ◽  
Chinese Stock Market ◽  
Fama And French ◽  
Three Factor

This paper aimed to evaluate and compare individual performances and contributions of seven well-known factors, selected from four widely cited asset pricing models: (1) the capital asset pricing model of Sharpe (1964), (2) the three-factor model of Fama and French (1993) the augmented four-factor model of Carhart (1997), (3) the five-factor model of Fama and French (2015), and (4) the illiquidity model of Amihud, et al. (2015) in capturing the time-series variation of stock returns and absorbing the 12 prominent anomalies. The anomalies were constructed by forming long-short portfolios, and regressions were run to examine their monthly returns from 2000 to 2019. We found that there is no definite and absolute “king” in the factor zoo in the Chinese stock market, and size is the relative “king” that can absorb the maximum number of anomalies. Evidence also indicates that the three-factor model of Fama and French may still play an important role in pricing assets in the Chinese stock market. The results can provide investors with a reliable risk factor and help investors form an effective investment strategy. This paper contributes to asset pricing literature in the Chinese market.G1

scholarly journals THE FOUR-FACTOR MODEL AND STOCK RETURNS IN BANGLADESH

2021 ◽  
Vol 6 (2) ◽  
pp. 133-149
Author(s):  
Muhammad Saifuddin Khan ◽  
Md. Miad Uddin Fahim
Keyword(s):  
Asset Pricing ◽  
Stock Returns ◽  
Factor Model ◽  
Stock Exchange ◽  
Explanatory Power ◽  
Jel Classification ◽  
Expected Return ◽  
Market Factors ◽  
Fama And French ◽  
Three Factor

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.

scholarly journals Choosing Factors for the Vietnamese Stock Market

2021 ◽  
Vol 14 (3) ◽  
pp. 96
Author(s):  
Nina Ryan ◽  
Xinfeng Ruan ◽  
Jin E. Zhang ◽  
Jing A. Zhang
Keyword(s):  
Stock Returns ◽  
Factor Model ◽  
Five Factor Model ◽  
Explanatory Power ◽  
Factor Models ◽  
Marginal Contribution ◽  
Return On Equity ◽  
Factor Modeling ◽  
Three Factor ◽  
Better Than

In this paper, we test the applicability of different Fama–French (FF) factor models in Vietnam, we investigate the value factor redundancy and examine the choice of the profitability factor. Our empirical evidence shows that the FF five-factor model has more explanatory power than the FF three-factor model. The value factor remains important after the inclusion of profitability and investment factors. Operating profitability performs better than cash and return-on-equity (ROE) profitability as a proxy for the profitability factor in FF factor modeling. The value factor and operating profitability have the biggest marginal contribution to a maximum squared Sharpe ratio for the five-factor model factors, highlighting the value factor (HML) non-redundancy in describing stock returns in Vietnam.

scholarly journals HEDGE FUNDS: RISK AND PERFORMANCE

2018 ◽  
Vol 06 (01) ◽  
pp. 1850003
Author(s):  
SANGHEON SHIN ◽  
JAN SMOLARSKI ◽  
GÖKÇE SOYDEMIR
Keyword(s):  
Risk Factors ◽  
Hedge Funds ◽  
Factor Model ◽  
Explanatory Power ◽  
Hedge Fund ◽  
Investment Strategy ◽  
Time Varying ◽  
Asset Class ◽  
And Performance ◽  
Fund Portfolio

This paper models hedge fund exposure to risk factors and examines time-varying performance of hedge funds. From existing models such as asset-based style (ABS)-factor model, standard asset class (SAC)-factor model, and four-factor model, we extract the best six factors for each hedge fund portfolio by investment strategy. Then, we find combinations of risk factors that explain most of the variance in performance of each hedge fund portfolio based on investment strategy. The results show instability of coefficients in the performance attribution regression. Incorporating a time-varying factor exposure feature would be the best way to measure hedge fund performance. Furthermore, the optimal models with fewer factors exhibit greater explanatory power than existing models. Using rolling regressions, our customized investment strategy model shows how hedge funds are sensitive to risk factors according to market conditions.

PERBANDINGAN FAMA AND FRENCH THREE FACTOR . MODEL DENGAN CAPITAL ASSET PHCING MODEL

2008 ◽  
Vol 4 (2) ◽  
pp. 132
Author(s):  
Dede Irawan Saputra ◽  
Umi Murtini
Keyword(s):  
Factor Model ◽  
Market Size ◽  
Capital Asset ◽  
Fama And French ◽  
Three Factor

Penelitian ini bertujuan untuk menguji kemompuon Fama and Freneh three factor model dalom menjelaskan retum jortofolio dibandingkan dengan CAPM. Data yang digmakm pda penelitiot ini adatah d*a sekunder dari perusahaan yang masuk dalam LQ-45 dari periede Februari 2000 sampai Juli 2007- Sampel yang digunakan adaleh perusahaan yang selalu masuk datam Lg-45 selona periode penelitian- Hasil penelitian menwtjukkan batma betdasukmtnilai adjusted P dapat disimpulkan bahwa CAPM lebih mampu menjelaskot return partofolia dibandingkan dengan Fama and French three factor model Hal ini dryot dilihat dari nilai adjusted N CAPM yang lebih besar dibanding nilai adjusted,F Fama and Frqnch three factor modelKeywords: z Market, Size, BEIME, dan Adjusted R2

scholarly journals Analysis of the Spanish IBEX-35 Companies’ Returns Using Extensions of the Fama and French Factor Models

Symmetry ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 295 ◽  
Author(s):  
Francisco Jareño ◽  
María de la O González ◽  
Laura Munera
Keyword(s):  
Interest Rates ◽  
Factor Model ◽  
Five Factor Model ◽  
Explanatory Power ◽  
Factor Models ◽  
Final Conclusion ◽  
Economic Cycle ◽  
Explanatory Factors ◽  
Nominal Interest Rates ◽  
Fama And French

This paper studies in depth the sensitivity of Spanish companies’ returns to changes in several risk factors between January 2000 and December 2018 using the quantile regression approach. Concretely, this research applies extensions of the Fama and French three- and five-factor models (1993 and 2015), according to González and Jareño (2019), adding relevant explanatory factors, such as nominal interest rates, the Carhart (1997) risk factor for momentum and for momentum reversal and the Pastor and Stambaugh (2003) traded liquidity factor. Additionally, for robustness, this paper splits the entire sample period into three sub-sample periods (pre-crisis, crisis and post-crisis) to analyse the results according to the economic cycle. The main conclusions of this paper are fourfold: First, these two models have the greatest explanatory power in the extreme quantiles of the return distribution (0.1 and 0.9) and more specifically in the lowest quantile 0.1. Second, the second model, based on the Fama and French five-factor model, shows the highest explanatory power not only in the full period but also in the three sub-periods. Third, the bank BBVA is the company that shows the highest sensitivity to changes in the explanatory factors in most periods because its adjusted R2 is the highest. Fourth, the stage of the economy with the highest explanatory power is the crisis subperiod. Thus, the final conclusion of this paper is that the second model explains best variations in Spanish companies’ returns in crisis stages and low quantiles.

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