scholarly journals The contribution of corporate social responsibility to financial performance: a factor model of Canadian stocks

2021 ◽  
Author(s):  
Mohammad Behroyan
Keyword(s):  
Corporate Social Responsibility ◽  
Asset Pricing ◽  
Social Responsibility ◽  
Factor Model ◽  
Explanatory Power ◽  
Pricing Model ◽  
Asset Pricing Model ◽  
Factor I ◽  
Fama And French ◽  
Corporate Social

This paper studies the effect of corporate social responsibility (CSR) on the returns of Canadian stocks. It employs the 3-factor asset-pricing model created by Fama and French (1993) and adds a new CSR factor (2x3 sorts) to examine if the explanatory power of the model is improved by the CSR factor. I, also, introduce an alternative method to create a 4-factor model (2x2x2 sorts). The results of my tests show the CSR factor does not improve the explanatory power of the Fama French models. Furthermore, replacing HML by CSR captures no more excess returns and I conclude that corporate social responsibility is not a priced factor in Canadian capital markets. In addition, the 3-factor model (based on Rm-Rf, SMB, HML) generates the exactly same results as Fama-French (1993 and 2015) models. Finally, I find that large firms, especially big size-low BE/ME companies, tend to be more “ethical”.

scholarly journals The contribution of corporate social responsibility to financial performance: a factor model of Canadian stocks

2021 ◽  
Author(s):  
Mohammad Behroyan
Keyword(s):  
Corporate Social Responsibility ◽  
Asset Pricing ◽  
Social Responsibility ◽  
Factor Model ◽  
Explanatory Power ◽  
Pricing Model ◽  
Asset Pricing Model ◽  
Factor I ◽  
Fama And French ◽  
Corporate Social

This paper studies the effect of corporate social responsibility (CSR) on the returns of Canadian stocks. It employs the 3-factor asset-pricing model created by Fama and French (1993) and adds a new CSR factor (2x3 sorts) to examine if the explanatory power of the model is improved by the CSR factor. I, also, introduce an alternative method to create a 4-factor model (2x2x2 sorts). The results of my tests show the CSR factor does not improve the explanatory power of the Fama French models. Furthermore, replacing HML by CSR captures no more excess returns and I conclude that corporate social responsibility is not a priced factor in Canadian capital markets. In addition, the 3-factor model (based on Rm-Rf, SMB, HML) generates the exactly same results as Fama-French (1993 and 2015) models. Finally, I find that large firms, especially big size-low BE/ME companies, tend to be more “ethical”.

scholarly journals Empirical Test of Single Factor and Multi-Factor Asset Pricing Models: Evidence from Non Financial Firms on the Ghana Stock Exchange (GSE)

2015 ◽  
Vol 8 (1) ◽  
pp. 99
Author(s):  
Prince Acheampong ◽  
Sydney Kwesi Swanzy
Keyword(s):  
Asset Pricing ◽  
Factor Model ◽  
Stock Exchange ◽  
Explanatory Power ◽  
Pricing Model ◽  
Asset Pricing Model ◽  
Financial Firms ◽  
Portfolio Returns ◽  
Ghana Stock Exchange ◽  
Three Factor

<p>This paper examines the explanatory power of a uni-factor asset pricing model (CAPM) against a multi-factor model (The Fama-French three factor model) in explaining excess portfolio returns on non-financial firms on the Ghana Stock Exchange (GSE). Data covering the period January 2002 to December 2011 were used. A six Size- Book-to-Market (BTM) ratio portfolios were formed and used for the analysis. The paper revealed that, a uni-factor model like the (CAPM) could not predict satisfactorily, the excess portfolio returns on the Ghana Stock Exchange. By using the multi-factor asset pricing model, that is, the Fama-French Three Factor Model, excess portfolio returns were better explained. It is then conclusive enough that, the multi-factor asset pricing model introduced by Fama and French (1992) was a better asset pricing model to explain excess portfolio returns on the Ghana Stock Exchange than the Capital Assets Pricing Model (CAPM) and that there exist the firm size and BTM effects on the Ghanaian Stock market.</p>

scholarly journals A TEST OF THE FAMA-FRENCH FIVE FACTOR MODEL IN COMPARISON TO THE CAPITAL ASSET PRICING MODEL AT THE LUSAKA SECURITIES EXCHANGE

2018 ◽  
Vol 3 (1) ◽  
pp. 35
Author(s):  
Nsama Musawa ◽  
Prof. Sumbye Kapena ◽  
Dr . Chanda Shikaputo
Keyword(s):  
Asset Pricing ◽  
Stock Returns ◽  
Factor Model ◽  
Five Factor Model ◽  
Capital Asset Pricing Model ◽  
Capital Asset Pricing ◽  
Pricing Model ◽  
Capital Asset ◽  
Asset Pricing Model ◽  
Fama And French

Purpose: The capital asset pricing model (CAPM)  is one of  the basic models in the security price analysis.Many asset pricing models have been developed to improve the CAPM.Among such models is the latest  Fama and French five factor model which is being  empirically tested in various stock markets. This study tested the five factor model in comparison to the capital asset pricing model. Testing the Fama and French Five factor model in comparison to the CAPM was important because the CAPM is widely taken to be the basic model in the security price analysis. Methodology: The Fama and French methodology was used to test  the data from an emerging market, the Lusaka Securities Exchange. A deductive, quantitative research design and secondary data from the Lusaka Securities Exchange was used. Data was analyzed using multiple regression. Results: The results indicate that the Five Factor model is better than the CAPM in capturing variation in the stock returns. The Adjusted R-squared for the five factor model from all individual portfolio sorting was 0.9, while that for the CAPM was 0.13 Unique contribution to theory, practice and policy: This study has contributed to theory in that it has added a voice to the ongoing debt on the suitability of  the new Fama and French Five Factor model which is at the cutting hedge in finance theory.Further the study is from developing capital market. Keywords:, CAPM, Stock returns, Fama and French five factor model

New Evidence to Assess the Asset Pricing Model: An Empirical Investigation Based on Bayesian Network

2020 ◽  
Vol 23 (03) ◽  
pp. 2050021
Author(s):  
Fatma Hachicha ◽  
Sahar Charfi ◽  
Ahmed Hachicha
Keyword(s):  
Asset Pricing ◽  
Stock Market ◽  
Bayesian Network ◽  
Factor Model ◽  
Five Factor Model ◽  
Pricing Model ◽  
Stock Market Returns ◽  
Asset Pricing Model ◽  
Fama And French ◽  
Better Than

An extensive, in-depth study of risk factors seems to be of crucial importance in the research of the financial market in order to prevent (or reduce) the chance of developing this return. It represents market anomalies. This study confirms that the [Formula: see text]-factors model is better than the other traditional asset pricing models in explaining individual stock return in the US over the 2000–2017 period. The main focus of data analysis is, on the use of models, to discover and understand the relationships between different factors of risk market anomaly. Recently, Fama and French presented a five-factor model that captures the size, value, profitability, and investment patterns in average stock market returns better than their three-factor model presented previously in 1993. This paper explores a shred of new empirical evidence to assess the asset pricing model through an extension of Fama and French model and a report on applying Bayesian Network (BN) modeling to discover the relationships across different risk factor. Furthermore, the induced BN was used to make inference taking into account sensibility and the application of BN tools has led to the discovery of several direct and indirect relationships between different parameters. For this reason, we introduce additional factors that are related to behavioral finance such as investor’s sentiment to describe a behavior return, confidence index, and herding. It is worth noting that there is an interaction between these various factors, which implies that it is interesting to incorporate them into the model to give more effectiveness to the performance of the stock market return. Moreover, the implemented BN was used to make inferences, i.e., to predict new scenarios when different information was introduced.

scholarly journals The influence of the 2008 financial crisis on the predictiveness of risky asset pricing models in Brazil

2016 ◽  
Vol 27 (72) ◽  
pp. 408-420
Author(s):  
Adriana Bruscato Bortoluzzo ◽  
Maria Kelly Venezuela ◽  
Maurício Mesquita Bortoluzzo ◽  
Wilson Toshiro Nakamura
Keyword(s):  
Asset Pricing ◽  
Factor Model ◽  
Pricing Model ◽  
Pricing Models ◽  
Monthly Basis ◽  
Total Period ◽  
Risky Assets ◽  
Asset Pricing Model ◽  
Portfolio Returns ◽  
Fama And French

ABSTRACT This article examines three models for pricing risky assets, the capital asset pricing model (CAPM) from Sharpe and Lintner, the three factor model from Fama and French, and the four factor model from Carhart, in the Brazilian mark et for the period from 2002 to 2013. The data is composed of shares traded on the São Paulo Stock, Commodities, and Futures Exchange (BM&FBOVESPA) on a monthly basis, excluding financial sector shares, those with negative net equity, and those without consecutive monthly quotations. The proxy for market return is the Brazil Index (IBrX) and for riskless assets savings accounts are used. The 2008 crisis, an event of immense proportions and market losses, may have caused alterations in the relationship structure of risky assets, causing changes in pricing model results. Division of the total period into pre-crisis and post-crisis sub-periods is the strategy used in order to achieve the main objective: to analyze the effects of the crisis on asset pricing model results and their predictive power. It is verified that the factors considered are relevant in the Brazilian market in both periods, but between the periods, changes occur in the statistical relevance of sensitivities to the market premium and to the value factor. Moreover, the predictive ability of the pricing models is greater in the post-crisis period, especially for the multifactor models, with the four factor model able to improve predictions of portfolio returns in this period by up to 80%, when compared to the CAPM.

scholarly journals Is Human Capital the Sixth Factor? Evidence from US Data

2019 ◽  
Vol 8 (1) ◽  
pp. 21-55 ◽  
Author(s):  
Rahul Roy ◽  
Santhakumar Shijin
Keyword(s):  
Human Capital ◽  
Asset Pricing ◽  
Factor Model ◽  
Generalized Method Of Moments ◽  
Common Factors ◽  
Return Predictability ◽  
Pricing Model ◽  
Gmm Estimation ◽  
Asset Return ◽  
Asset Pricing Model

Problem/Relevance: Measuring the risk of an asset and the economic forces driving the price of the risk is a challengingtask that preoccupied the asset pricing literature for decades. However, there exists no consensus on the integrated asset pricing framework among the financial economists in the contemporaneous asset pricing literature. Thus, we consider and study this research problem that has greater relevance in pricing the risks of an asset. In this backdrop, we develop an integrated equilibrium asset pricing model in an intertemporal (ICAPM) framework. Research Objective/Questions: Broadly we have two research objectives. First, we examine the joint dynamics of the human capital component and common factors in approximating the variation in asset return predictability. Second, we test whether the human capital component is the unaccounted and the sixth pricing factor of FF five-factor asset pricing model. Additionally, we assess the economic and statistical significance of the equilibrium six-factor asset pricing model. Methodology: The human capital component, market portfolio, size, value, profitability, and investment are the pricing factors of the equilibrium six-factor asset pricing model. We use Fama-French (FF) portfolios of 2  3, 5  5, 10  10 sorts, 2  4  4 sorts, and the Industry portfolios to examine the equilibrium six-factor asset pricing model. The Generalized method of moments (GMM) estimation is used to estimate the parameters of variant asset pricing models and Gibbons-Ross-Shanken test is employed to evaluate the performance of the variant asset pricing frameworks. Major Findings: Our approaches led to three conclusions. First, the GMM estimation result infers that the human capital component of the six-factor asset pricing model significantly priced the variation in excess return on FF portfolios of variant sorts and the Industry portfolios. Further, the sensitivity to human capital component priced separately in the presence of the market portfolios and the common factors. Second, the six-factor asset pricing model outperforms the CAPM, FF three-factor model, and FF five-factor model, which indicates that the human capital component is a significant pricing factor in asset return predictability. Third, we argue that the human capital component is the unaccounted asset pricing factor and equally the sixth-factor of the FF five-factor asset pricing model. The additional robustness test result confirms that the parameter estimation of the six-factor asset pricing model is robust to the alternative definitions of the human capital component. Implications: The empirical results and findings equally pose the more significant effects for the decision-making process of the rational investor, institutional managers, portfolio managers, and fund managers in formulating the better investment strategies, which can help in diversifying the aggregate risks.

scholarly journals Responsible or Thematic? The True Nature of Sustainability-Themed Mutual Funds

2019 ◽  
Vol 11 (12) ◽  
pp. 3304 ◽  
Author(s):  
Federica Ielasi ◽  
Monica Rossolini
Keyword(s):  
Mutual Funds ◽  
Factor Model ◽  
Capital Asset Pricing ◽  
Pricing Model ◽  
Capital Asset ◽  
Socially Responsible ◽  
True Nature ◽  
Asset Pricing Model ◽  
Fama And French ◽  
Better Than

The aim of the paper is to compare the risk-adjusted performance of sustainability-themed funds with other categories of mutual funds: sustainable and responsible mutual funds that implement different approaches in portfolio selection and management, and thematic funds not committed to responsible investments. The study analyses a sample of about 1000 European mutual open-end funds where 302 are sustainability-themed funds, 358 are other responsible funds, and 341 other thematic funds. Risk-adjusted performance is analyzed for the period 2007–2017 using different methodologies: a single factor Capital Asset Pricing Model (CAPM), a Fama and French (1993) 3-factor model, and a Fama and French (2015) 5-factor model. Our main findings demonstrate that the risk-adjusted performance of ST funds is more closely related to their responsible nature than to their thematic approach. Sustainability-themed mutual funds are more similar to other socially responsible funds than to other thematic funds, as confirmed by performance analysis over time. They are also better than other thematic funds in overcoming financially turbulent periods and currently benefit from SRI regulation and disclosure.

Revisiting Fama–French’s asset pricing model with an MCB volatility risk factor

2020 ◽  
Vol 21 (3) ◽  
pp. 233-251
Author(s):  
Xiaoying Chen ◽  
Nicholas Ray-Wang Gao
Keyword(s):  
Risk Factor ◽  
Asset Pricing ◽  
Explanatory Power ◽  
Investor Sentiment ◽  
Size Factor ◽  
Pricing Model ◽  
Volatility Risk ◽  
Content Type ◽  
Asset Pricing Model ◽  
Market Factor

Purpose Since the introduction of VIX to measure the spot volatility in the stock market, VIX and its futures have been widely considered to be the standard of underlying investor sentiment. This study aims to examine how the magnitude of contango or backwardation (MCB volatility risk factor) derived from VIX and VIX3M may affect the pricing of assets. Design/methodology/approach This paper focuses on the statistical inference of three defined MCB risk factors when cross-examined with Fama–French’s five factors: the market factor Rm–Rf, the size factor SMB (small minus big), the value factor HML (high minus low B/M), the profitability factor RMW (robust minus weak) and the investing factor CMA (conservative minus aggressive). Robustness checks are performed with the revised HML-Dev factor, as well as with daily data sets. Findings The inclusions of the MCB volatility risk factor, either defined as a spread of monthly VIX3M/VIX and its monthly MA(20), or as a monthly net return of VIX3M/VIX, generally enhance the explanatory power of all factors in the Fama and French’s model, in particular the market factor Rm–Rf and the value factor HML, and the investing factor CMA also displays a significant and positive correlation with the MCB risk factor. When the more in-time adjusted HML-Dev factor, suggested by Asness (2014), replaces the original HML factor, results are generally better and more intuitive, with a higher R2 for the market factor and more explanatory power with HML-Dev. Originality/value This paper introduces the term structure of VIX to Fama–French’s asset pricing model. The MCB risk factor identifies underlying configurations of investor sentiment. The sensitivities to this timing indicator will significantly relate to returns across individual stocks or portfolios.

Evaluating alternative performance benchmarks for Indian mutual fund industry

2017 ◽  
Vol 14 (2) ◽  
pp. 222-250 ◽  
Author(s):  
Sanjay Sehgal ◽  
Sonal Babbar
Keyword(s):  
Asset Pricing ◽  
Mutual Fund ◽  
Factor Model ◽  
Five Factor Model ◽  
Content Type ◽  
Asset Pricing Model ◽  
Fund Managers ◽  
Asset Pricing Models ◽  
Performance Benchmarks ◽  
Fama And French

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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