• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.513-521
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• 2020

In this paper, we have developed a Fama - French five factor model (FF5 model) from Fama & French (2015) by using concept of time-varying coefficient. For a data set, we have used monthly data form Kenneth R. French home page, it include Japan portfolios (classified by using size and book-to-market) and 5 factors from July 1990 to April 2020. The first analysis, we used Augmented Dickey-Fuller test (ADF test) for the stationary test, from the result, all Japan portfolios and 5 factors are stationary. Next analysis, we estimated a coefficient of Fama - French five factor model by using a generalized additive model with a thin-plate spline to create the time-varying coefficient Fama - French five factor model (TV-FF5 model). The benefit of this study is TV-FF5 model which can capture a different effect at different times of 5 factors but the traditional FF5 model can't do it. From the result, we can show a time-varying coefficient in all factors and in all portfolios, for time-varying coefficients of Rm-Rf, SMB, and HML are significant for all Japan portfolios, time-varying coefficients of RMW are positively significant for SM, and SH portfolio and time-varying coefficients of CMA are significant for SM, SH, and BM portfolio.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.717-729
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• 2021

This paper examines the efficacy of the default risk factor in an emerging market context using the Fama-French five-factor model. Our aim is to test whether the Fama-French five-factor model augmented with a default risk factor improves the predictability of returns of portfolios sorted on the firm's characteristics as well as on industry. The default risk factor is constructed by estimating the probability of default using a hybrid version of dynamic panel probit and artificial neural network (ANN) to proxy default risk. This study also provides evidence on the temporal stability of risk premiums obtained using the Fama-MacBeth approach. Using a sample of 3,806 firm-year observations on non-financial listed companies of Pakistan over 2006-2015 we found that the augmented model performed better when tested across size-investment-default sorted portfolios. The investment factor contains some default-related information, but default risk is independently priced and bears a significantly positive risk premium. The risk premiums are also found temporally stable over the full sample and more recent sample period 2010-2015 as evidence by the Fama-MacBeth regressions. The finding suggests that the default risk factor is not a useless factor and due to mispricing, default risk anomaly prevails in the Pakistani equity market.

• Health Policy and Management
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• v.4 no.2
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• pp.58-76
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• 1994

In order to study factors affecting the use of the ambulatory physician services. Andersen's model for health utilization was modified by adding the health behavior component and examined with three different approaches. Three different approaches were the multiople regression model, logistic regression model, and LISREL model. For multiple regression, dependent variable was reported illness-related visits to a physician during past one year and independent variables are variaous variables measuring predisposing factor, enabling factor, need factor and health behavior. For the logistic regression, dependent variable was visit or no-visit to a physician during past one year and independent variables were same as the multiple regression analysis. For the LISREL, five endogenous variables of health utiliztion, predisposing factor, enabling factor, need factor, and health behavior and 20 exogeneous variables which measures five endogenous variables were used. According to the multiple regression analysis, chronic illness, health status, perceived health status of the need factor; residence, sex, age, marital status, education of the predisposing factor ; health insurance, usual source for medical care of enabling factor were the siginificant exploratory variables for the health utilization. Out of the logistic regression analysis, health status, chronic illness, residence, marital status, education, drinking, use of health aid were found to be significant exploratory variables. From LISREL, need factor affect utilization most following by predisposing factor, enabling factor and health behavior. For LISREL model, age, education, and residence for predisposing factor; health status, chronic illess, and perceived health status for need factor; medical insurance for enabling factor; and doing any kind of health behavior for the health behavior were found as the significant observed variables for each theoretical variables.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.265-271
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• 2022

Social media is a form of communication based on the internet to share information through content and images. Their choice of profile images and type of image they post can be closely connected to their personality. The user posted images are designated as personality traits. The objective of this study is to predict five factor model personality dimensions from profile images by using deep learning and neural networks. Developed a deep learning framework-based neural network for personality prediction. The personality types of the Big Five Factor model can be quantified from user profile images. To measure the effectiveness, proposed two models using convolution Neural Networks to classify each personality of the user. Done performance analysis among two different models for efficiently predict personality traits from profile image. It was found that VGG-69 CNN models are best performing models for producing the classification accuracy of 91% to predict user personality traits.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.11
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• pp.1-10
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• 2021

This paper compares the performance of Fama-French three-factor and five-factor models using a dataset of 20 Pakistani commercial banks for the period 2011 to 2020. We focus on an emerging economy as the findings from earlier studies on developed countries cannot be generalized in emerging markets. For empirical analysis, twelve portfolios were developed based on size, market capitalization, investment strategy, and growth. Subsequently, we constructed five Fama-French factors namely, R_M, SMB, HML, RMW, and CMA. The OLS regression technique with robust standard errors was applied to compare the predictive power of both the Fama-French models. Further, we also compared the mean-variance efficiency of the Fama-French models through the GRS test. Our empirical analysis provides three unique and interesting findings. First, both asset pricing models have similar predictive power to explain the expected portfolio returns in most cases. Second, our results from the GRS test suggest that there is no noticeable difference in the mean-variance efficiency of one asset pricing model over the other. Third, we find that all factors of both Fama-French models are statistically significant and are important for explaining the volatility of expected commercial bank returns in the context of Pakistan.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.75-83
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• 2015

As the importance of realistic game character in order to cause the interest of player is increased, it is necessary to develop the character that acts like a man by applying the human characteristics in the step of game character design. Formerly, there is a limit to create the human-like character because there is no set the character's personality in the game developing level. In this paper, therefore, we propose the correlation between Five Factor Model and Ego-state for game character. Five Factor Model and Ego-state are theories about person's characteristic. Five Factor Model is personality description method. Ego-state has an emphasis on internal mental processes directly from observable behaviors. In this regard, these theories could be used to the character defined its personality and designed to act by personality. To do this, it needs to determine the relations between Five Factor Model and Ego-state. Therefore we seek for the relations between two theories using Adjective Check List(ACL) and analysis their results with surveys. In the future, it is expected to construct a personality model using these analysis results, and develop the character based on realistic behavior.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.615-626
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• 2020

The purpose of this study is to analyze the determinants of risk factor model for the Jordanian banking stocks from 2006 to 2018. This study employs the Five-factor Fama and French's (2015) methodology and uses the annual returns of all Jordanian banks including 2 Islamic and 13 commercial banks listed on the Amman Stock Exchange (ASE) over a period of 13 years. The results show that the factors of value and profitability have an important role in evaluating the expected return in Jordanian banking stocks. Moreover, the value HML and profitability RMW factors provide the highest cumulative returns among these five factors, while the investment CMA and size SMB factors are still around zero cumulative returns. For the market factor, it provides the least negative cumulative returns. The results showed that the largest correlation is between value and investment factors which means that banks with a high book to market value become banks with a conservative investment strategy. The result of the sub-periods confirmed the value and profitability results. The findings of this study suggest that the five-factor Fama and French model is the choice of building an investment portfolio, especially the factors of value and profitability.

• Asia-Pacific Journal of Business
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• v.15 no.1
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• pp.1-14
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• 2024

Purpose - We investigate whether a potential missing pricing factor plays a significant role in the idiosyncratic volatility puzzle. Design/methodology/approach - We theoretically show how a missing pricing factor can affect the idiosyncratic volatility puzzle, and also show how to get around the problem empirically. We adopt the Fama-French five factor model for the estimation of the idiosyncratic risk and use randomly constructed portfolios as test assets. Findings - We find that a missing factor does not drive the idiosyncratic volatility puzzle. Thus, we conclude that the idiosyncratic volatility does affect the risk premium of its stock. Research implications or Originality - The Fama-French five factor model does a pretty good job in explaining the risk premiums of stocks, and it can be used to reliably estimate idiosyncratic risk of stocks.

• Food Science of Animal Resources
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• v.43 no.2
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• pp.374-381
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• 2023

In a previous study, 'response surface methodology (RSM) using a fullest balanced model' was proposed to improve the optimization of food processing when a standard second-order model has a significant lack of fit. However, that methodology can be used when each factor of the experimental design has five levels. In response surface experiments for optimization, not only five-level designs, but also three-level designs are used. Therefore, the present study aimed to improve the optimization of food processing when the experimental factors have three levels through a new approach to RSM. This approach employs three-step modeling based on a second-order model, a balanced higher-order model, and a balanced highest-order model. The dataset from the experimental data in a three-level, two-factor central composite design in a previous research was used to illustrate three-step modeling and the subsequent optimization. The proposed approach to RSM predicted improved results of optimization, which are different from the predicted optimization results in the previous research.

• Anxiety and mood
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• v.8 no.2
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• pp.99-105
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• 2012

Objective : The aim of this study is to evaluate the five-factor model of personality in patients with obsessive-compulsive disorder (OCD) related to obsessive-compulsive symptom severity and the distinct symptom subgroups. Methods : We recruited 95 patients with OCD and 116 normal controls in the study. We used the short version of Revised NEO Personality Inventory and the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) for the assessment. Results : Patients with OCD showed significantly higher scores in neuroticism than normal controls. On multiple linear regression analysis, we found that agreeableness and conscientiousness were associated with the total Y-BOCS scores. On subscale analysis, agreeableness and neuroticism were associated with the obsession subscale scores and only conscientiousness was associated with the compulsion subscale scores. Furthermore, we found that patients who have contamination/cleaning or symmetry/ordering/counting/arranging as a main symptom presentation had significantly higher mean scores in conscientiousness than patients who have harm due to injury/violence/aggression as a main symptom presentation. Conclusion : In this study, we found that specific personality factors are associated with the obsessive-compulsive symptom severity. In addition, this is the first study to investigate the relationship between the personality factors in the five-factor model and the distinct symptom subgroups in OCD.