Three Factor Model

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An Empirical Validation of Fama and French Three-Factor Model (1992, A) On Some US Indices

An Empirical Validation of Fama and French Three-Factor Model (1992, A) On Some US Indices

This study had two objectives: one explicit and the other implicit. The explicit is to test the relationship between the explanatory power of the Fama-French three-factor model and index size. Fama and French (1992a) and Fama and French (1993) used a uniform size of the considered index, one hundred stocks. However, world indices are different in size. Therefore we should absolutely study the impact of variation in index size on the relevance of the model. The implicit objective is to check market efficiency. Referring to the strong values, we could conclude that stock returns can be expected from HML and SMB portfolios returns and market returns. Therefore, the four studied indices are not efficient under a strong form. This result corroborates that of Cutler David et al. (1989) and Shiller Robert (1981).
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The Fama-French Three-Factor Model under uncertainty

The Fama-French Three-Factor Model under uncertainty

Therefore, based on the uncertainty of the distributions of error terms, this paper considers the improvement of the specific linear regression model—Fama-French three-factor model under the condition of uncertain distribution. Under the k-sample hypothesis, this paper uses upper expectation regression method and weighted expectation regression method to deal with the uncertain distribution, and gets its optimal solution thorough genetic algorithm. Furthermore, this paper gives the identification and asymptotic normality properties.
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Fama and French Three-Factor Model: Evidence from Istanbul Stock Exchange

Fama and French Three-Factor Model: Evidence from Istanbul Stock Exchange

The principal aim of this study is to test the validity of the Fama and French three- factor model on the ISE. This research adopts a methodology similar to that developed by Fama and French (1996). The ISE is the only stock exchange in Turkey. As of February 2012 the ISE has had a total capitalization of over 400 billion TRY and monthly volume of about 90 billion TRY. 1 In total, there are 365 stocks trading on ISE. The current study has a monthly- based test period from January 2003 to December 2010. Throughout this 96-month analysis period, firms included in this study should have been listed for at least 36 months prior to the portfolio formation date. This requirement aims to ensure that all companies have more than two years’ accounting data available. This time restriction contributes to the reliability of the data. Gaunt (2004) uses a similar strategy (18-month restriction) in his study. Thus, 274 stocks listed in ISE-all index are analyzed in the study. The Fama and French three-factor model regression equation is stated as:
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The Capital Asset Pricing Model And Fama-French Three Factor Model In An Emerging Market Environment

The Capital Asset Pricing Model And Fama-French Three Factor Model In An Emerging Market Environment

Griffin (2002), using monthly data from 1981 to 1995, tested the FF3FM in the United Kingdom, Canada and Japan and reported that the Size and Value premiums do indeed contribute significantly to the explanatory power of the model. Lam (2002), using data for 100 Stock Exchange of Hong Kong (SEHK) listed stocks also reported results to support Fama and French’s findings. Australian studies attributed to Faff (2001) and Gaunt (2004) report that the statistical significance, and parameter magnitudes, are comparable with Fama and French (1993, 1995) to a partial degree – noting a significant size effect with little evidence to suggest a significant book-to-market effect. This is in contrast to Kassimatis’s (2008) findings, which concluded that the FF3FM did not provide convincing evidence. More recently, Gregory and Michou (2009) applied the three-factor model on the UK stock market, in which the Size and Value factors were found to vary through time, and overall results were found to be similar, yet more explanatory compared with those of the CAPM.
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Validation of intercultural sensitivity three factor model in Malaysian context

Validation of intercultural sensitivity three factor model in Malaysian context

Therefore, the purpose of the present study is to extend previous work on IS by validating the three-factor model within Malaysian collectivistic context. This is done by addressing the limitations mentioned earlier. First, the three-factor model which was produced based on exploratory factor analysis (EFA) was subject to Confirmatory Factor Analysis (CFA). Second, data collection was carried out at multiple sites thus extending the generalisability of the findings. Third, the sample was undergraduate students who engaged in cross-national interactions; which means that intercultural sensitivity was measured based on respondents’ engagement in interactions with international students on campus.
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A Multiscale Pricing Model with the Wavelet Analysis Approach, Fama-French Three-Factor Model, and Nonliquidity in Tehran Stock Exchange

A Multiscale Pricing Model with the Wavelet Analysis Approach, Fama-French Three-Factor Model, and Nonliquidity in Tehran Stock Exchange

Czapkiewicz and Wojtowicz (2014), added another factor to tree-factor Fama-french model and studied the four-factor asset pricing model on the Warsaw Stock Exchange (WSE) which is one of the largest stock markets in Central and Eastern Europe. The empirical analysis is based on monthly data from the period April 2003–December 2012 which includes different stages of the business cycle. This article shows that momentum is a significant factor on the WSE and the four-factor model describes the returns variation much better than the three-factor model [6].
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Functioning of Fama French Three Factor Model in Emerging Stock Markets: An Empirical Study on Chittagong Stock Exchange, Bangladesh

Functioning of Fama French Three Factor Model in Emerging Stock Markets: An Empirical Study on Chittagong Stock Exchange, Bangladesh

DOI: 10.4236/jfrm.2017.64025 353 Journal of Financial Risk Management model so far developed can accurately explain the relation. The most universal and acceptable model in the current finance arena is the three-factor model in- strumented by Fama and French. This model assumes that the cross-section of average returns can be explained by three factors like the excess market return, size factor and book-to-market (B/M) equity factor. Fama and French in 1992 extended the original CAPM by introducing two additional factors viz., size and book to market which can explain the cross-section of stock returns. SMB, which stands for Small Minus Big, measures the additional returns which have histori- cally been received from investment in stocks of companies with comparatively small market capitalization. This additional return is known as the “size pre- mium”. HML, which stands for High Minus Low, measures the “value premium” given to investors for investing in companies having high book-to-market val- ues. SMB which measures “size risk” reflects the view that small companies supposed to be more sensitive to many risk factors as they are comparatively undiversified in nature and have little ability to undertake adverse financial situ- ations. HML factor advocates higher risk exposure for typical “value” stocks with high B/M and “growth” stocks with low B/M. This is quite rational because companies need to arrive at a minimum size in order to execute an Initial Public Offering. Companies with high B/M indicate that their public market value has dropped because of hard times or uncertainty regarding future earnings. For any given asset, particularly at the time of giving dividends, the objective of the company is to characterize the “reasonable” price or the set of “reasonable” prices. Reasonable price is characterized by quality and quantity of products or services, terms of payment, favorable delivery and availability at the right time. It is also known as an equilibrium price. An equilibrium price is found in two situ- ations, first, when supply is equal to demand for any asset, i.e. markets clear, and the second situation is when an investor is satisfied with his present position and the asset prices.
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Tests Of The Fama And French Three Factor Model In Iran

Tests Of The Fama And French Three Factor Model In Iran

ama and French (1992) found that beta has little or no ability in explaining cross-sectional variation in stock returns, but those variables such as size and the book-to-market ratio do. Since the time of the original publication of the Fama and French findings, Controversy and intense debate has emerged in the academic literature over the empirical performance of beta and the CAPM. This paper compare CAPM versus Fama and French three factors model and investigates the explanatory power of market beta, firm size, and book-to-market ratio, regarding the cross-sectional expected stock returns in Tehran stock exchange. The results indicate that Fama and French three factor model has strong explanatory power than CAPM and the explanatory power of market beta is significantly improved and successfully captures the cross-sectional variation in expected stock returns for the full sample period.
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Capital asset pricing model and the three factor model: empirical evidence from emerging African stock markets

Capital asset pricing model and the three factor model: empirical evidence from emerging African stock markets

Denotes the harmonic ordinates of the sample, T is the number of observations, and n  T  for 0    1 is the number of low frequency ordinates used in the regression. The evidence underpins long memory of returns in the Chinese stock markets (both Shanghai and Shenzhen). GARCH and EGARCH models were applied to attain the fitting sequence of conditional variances which in turn was used as volatility estimates. The findings render a potent support of time-varying volatility and demonstrate that the Chinese stock markets volatility is highly persistent and predictable. They further employ the GARCH-M to examine the relationship between expected returns and expected conditional variance (risk). Testing capital asset pricing theories using GARCH-M model improves the specification because it permits the conditional variance of returns to be used as a measure of risk. They found no evidence of existing relationship between expected returns and expected risk (volatility) as predicted by capital asset pricing models, suggesting that other than volatility other variables need to be considered when formulating expected returns in China. Finally they investigated the hypothesis that information flow to the market place influence volatility of returns. This was tested using trading volume as a proxy for information flow. Daily trading volume was selected to represent the amount of information that flows into the market and found no evidence that trading volume has any significant effect on the conditional variance (volatility) of daily returns.
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Development of a Three-Factor Model of Psychological Ownership of Country: Applications for Outgroup Attitudes and Citizenship Behaviors

Development of a Three-Factor Model of Psychological Ownership of Country: Applications for Outgroup Attitudes and Citizenship Behaviors

identification and negative outgroup attitudes may be through immersion, or one’s sense of national ingroup belonging and sense that one’s country belongs to the ingroup. While only occurring within the model sans control variables, it is interesting that efficacy was associated with more positive attitudes towards immigrants. This finding is counter- intuitive when juxtaposed with others (i.e., Brylka at al., 2005; Martinovic & Verkuyten, 2013; Study 1 within this manuscript). Perhaps strong feelings of control over one’s country and belief in the ability of one’s social group to influence policy results in less outgroup prejudice by reducing concerns about loss of control. In essence, if the ingroup believes itself to be in power and the outgroup does not reflect a threat to the ingroup’s control, high efficacy individuals may be inclined to view outsiders more positively. Both tests of the mediation effect of psychological ownership have been conducted on cross- sectional data. While cross-sectional data can provide information about the shared and unique variance across three (or more) variables and thus plausible models of mediation (Hayes, 2013; Jose, 2013), it cannot confirm theoretical causal pathways.
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Age and gender effect on alexithymia in large, Japanese community and clinical samples: a cross-validation study of the Toronto Alexithymia Scale (TAS-20)

Age and gender effect on alexithymia in large, Japanese community and clinical samples: a cross-validation study of the Toronto Alexithymia Scale (TAS-20)

In order to validate the factor structure of the Japanese ver- sion of the TAS-20 (corresponding to the three-factor model of alexithymia proposed and validated in earlier studies in English-speaking countries [4,8,9,31], we con- ducted maximum-likelihood confirmatory factor analysis (CFA) with the normative sample data set. The goodness- of-fit was evaluated by the following three criteria recom- mended by Cole and Marsh et al [32,33]: goodness-of-fit (GFI) > 0.85, adjusted goodness-of-fit (AGFI) > 0.80, and root-mean-square residual (RMSR) <0.10. However, the GFI, AGFI and RMSR are all dependent on sample size and tend to indicate a good fit in a large sample. Thus, a good fit might be obtained as an artifact of sample size, regard- less of the real fit, in the present study. We also calculated the Tucker-Lewis index (TLI) [34], comparative fit index (CFI), root mean square error of approximation (RMSEA) [30], and upper and lower end of the 90% confidence interval for the RMSEA to see if the interval includes the area of "close fit" at 0.05. TLI values of 0.95 or higher are recommended. However, Schumacker and Lomax [35] contend that values close to 0.90 reflect a good model fit. The global fit indices are also supported by a RMSEA > 0.08 (preferably close model fit of < 0.06) [30] and a CFI > 0.90.
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Validation of the Malay Version of the Parental Bonding Instrument among Malaysian Youths Using Exploratory
Factor Analysis

Validation of the Malay Version of the Parental Bonding Instrument among Malaysian Youths Using Exploratory Factor Analysis

The PBI is influenced by culture (5). Controversial issues surround the factorial structure of the PBI. A few studies have either confirmed the two-factor model (11,12) or suggested a three-factor model (8,13,14). Among Pakistani mothers, the PBI items loaded satisfactorily on the care and overprotection factors, with overprotection divided into encouragement of behavioural freedom and denial of psychological autonomy (8). Interestingly, when the PBI was tested on the Japanese and Chinese populations, instead of two- or three-factor models, the PBI produced a four-factor model (2,10). In these populations, the items for the care factor were further divided into care and indifference (or rejection), and the items for overprotection were further divided into autonomy and overprotection (2,10). The subdivision of the overprotection factor in the Japanese and Chinese populations was similar to that of the Pakistani population (2,8,10). Therefore, it is important to validate the PBI questionnaire among the Malaysian population because the PBI may perform differently due to the different cultural background.
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The Effect of Investor Sentiment on Betting Against Beta: A SEM Approach Towards Beta Anomaly

The Effect of Investor Sentiment on Betting Against Beta: A SEM Approach Towards Beta Anomaly

This context investigates the new stream in finance literature. By utilizing behavioral finance, or better still investor sentiment, researchers try to offer better understanding of BAB phenomenon. In the present study, four accepted models borrowed and developed to explain investor sentiment as well as its influences on monthly returns on BAB factor. BAB factor is market neutral self-financing portfolio that goes long low-beta stocks while shortselling high-beta stocks. In this way, CAPM, Three-factor model (Fama and French, 1993), Four-factor model (Carhart, 1997), and six-factor model (Pastor and Stambaugh, 2001; Pástor and Pietro, 2003) were adopted and investor sentiment factor was added into the model for the period from August 1965 to January 2012. The results of empirical analysis, using SEM-PLS show the direct and statistically significant effect of investor sentiment on BAB returns. As a matter of fact, this finding gives some highlights into the study of beta anomaly and the effect of investor sentiment.
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Comparisons of Asset Pricing Models in the Egyptian Stock Market

Comparisons of Asset Pricing Models in the Egyptian Stock Market

slightly worse than the Fama-French three factor model. Bartholdy and Peare (2005) compare the performance of the CAPM and the Fama-French three factor model. They conclude that Fama-French model does not do much better than the CAPM. Grauer and Janmaat (2010) explore that cross-sectional test results provide little or no support for either model. However, when size and book-to-market factors in the Fama-French framework are added to the CAPM, the performance improves. Rossi (2001) uses monthly data to compare Fama-French three factor model and CAPM in the Italian stock market and discerns that risk-return relationship cannot be described by beta, hence putting size and book-to-market ratio into market return leads to improved description of the returns. Gregory, Tharyan and Christidis (2013) follow new methodology to form factor portfolios using CPZ-style market capitalization weighting of SMB, HML and UMD to liken Fama-French three factor model to Cahart four-factor model in the London stock exchange. Their results do not strongly support value weighting and decomposing factors. Nguyen, Fafaa and Gharghgor (2009) depend on all securities in the Australian stock exchange during the period 1990 to 2005, aiming at testing GDP-augmented Fama-French three factor model. They conclude adding GDP to Fama-French three factor model does not make a significant difference. Trimech, Kortas, Benammou and Benammou (2009) investigate the ability of Fama-French three factor model to predict stock returns at multiple time scales in the French stock market. The more wavelet scale surges, the more predictability of the model explained. Tsuji (2012) argues incorporation of momentum and reversal factors in the Fama-French three factor model causes positive alpha in the Japanese stock market.
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General and specific components of depression and anxiety in an adolescent population

General and specific components of depression and anxiety in an adolescent population

structure of depression and anxiety symptoms as IRT- informed dimensional phenotypes using latent trait modelling principles and methods were compared. In our large sample of British 14-year-old adolescents a three-factor model was preferred over one or two factor solutions in initial EFA. The three-factor (first-order) model contained a depressed mood factor, consisting of affective and social-cognitive symptoms of depression, a worrying factor, as well as a somatic/information pro- cessing factor including psychomotor disturbance, irrit- ability, and thinking/decision-making difficulties. Under this model these factors can be viewed as distinct yet closely related constructs. Alternatively, a bifactor model representation also fitted the data well. This representa- tion is in line with recent theoretical developments and offers improved insights into specific factors.
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Environmentally Initiated, Self Confirming Alienation in the Workplace

Environmentally Initiated, Self Confirming Alienation in the Workplace

In this three factor model, burnout is indicated by high levels of emotional exhaustion, high levels of depersonalization, and low levels of personal accomplishment.. The advantage of th[r]

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Size, P/E Ratio and Equity Stock Returns of Pakistan

Size, P/E Ratio and Equity Stock Returns of Pakistan

This study examine the impact of size and price earning ratio on equity returns by using Fama and French (1992, 1993).Results demonstrate that market premium exist in Pakistani equity market and size factor found positive related to portfolio returns. Size premium does not explain the big portfolios returns. In the period of 2002 to 2011 and 2007 to 2011 HML better explains the low price earning stocks and price earning is a negative proxy for book to market. In addition this study also confirms that Fama and French three factor model is a better approach to explain the returns in Pakistani equity market.
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Behavioral Activation and Behavioral Inhibition Predict Perfectionism

Behavioral Activation and Behavioral Inhibition Predict Perfectionism

perfectionism. Similarly, Rasmussen, Elliot, and Carter (2012) investigated the role of RST-R and socially- prescribed perfectionism (an index of self-evaluative perfectionism) in predicting suicidal thinking, and found BIS but not BAS associated with socially-prescribed perfectionism (as expected). They also noted negative associations between BAS and suicidal thinking, hopelessness and depression. They did not report any findings for perfectionistic strivings perfectionism. Randles and colleagues (2010) also assessed the relationship between BAS, BIS and perfectionism. Essentially, using the three- factor model of perfectionism from Hewitt and Flett’s (1991) Multidimensional Perfectionism Scales, Randles and colleagues found that BAS and BIS sensitivity, assessed by the Carver and White (1994) BIS/BAS scales, were both associated with high perfectionistic strivings (self-oriented perfectionism). They further found that BIS was also associated with one’s perceptions of high expectations from others (socially-prescribed perfectionism) as well as trait rumination [16]. They also documented a modest correlation between socially-prescribed perfectionism and BAS Reward.
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Investment Value Evaluation of Hi Tech Industry: Based on Multi Factor Dynamic Model

Investment Value Evaluation of Hi Tech Industry: Based on Multi Factor Dynamic Model

High-tech enterprises have a non-traditional business operation that emphasis on intellectual capital and corpo- rate culture as well as high investments risk, which determines the hi-tech industry is characterized by a high degree of technology-intensive, high input, high risks and high expected returns. These features can be depicted by factor Model. In the framework of the no-arbitrage pricing, the basic idea of multi-factor model is to identify factors that affect the yield of stocks and expand CAPM into a multi-factor model. Three-factor model is the most famous multi-factor model, by building stock portfolios with different size and book-value ratio, Fama and French (1993) empirically prove ME (scale factor) and BE/ME (value factor) are risk factors in the US stock market which represent the fluctuations of the yield [1]. In addition, Campbell, Lettau, Malkiel and Xu (2001) proposed volatility decomposition model, the volatility of individual stocks decomposed into market volatility, sector volatility and the individual volatility, and applied this method to the study of the stock market in US, which found that industry factors have a significant impact on stocks [2]. Summarizing the literatures according pricing the investment value of high-tech industries, we recognize that in addition to market premium factor, other factors affecting the value of the investment industry can be divided into two categories: industry-specific factors which stand for the industry-specific risk; factors reflect the macro-economic conditions.
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Chiral anomaly transition form factor of γ → 3π in nonlocal quark model

Chiral anomaly transition form factor of γ → 3π in nonlocal quark model

Abstract. Chiral anomaly of gamma transition into three pions are studied in a framework of nonlocal chiral quark model. In the local limit the result is in agreement with chiral perturbative theory and reproduces Wess-Zumino-Witten anomaly. Transition form factor of gamma into three pions in nonlocal quark model has a correction which vanishes in local limit.

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