Capital asset pricing

Open Access Article

1 - Extraction of a Mathematical Capital Asset Pricing Model within the Framework of Mental Accounting
Mohammadreza Ola Hashem Nikoomaram Azita Jahanshad Zahra Pourzamani

Ordinary investors do not look to their portfolio as a whole. These investors consider their portfolio as a set of mental arithmetic. In mental accounting, the conventional issue of maximizing the expected return is faced with the constraint of maximum likelihood to fai More

Ordinary investors do not look to their portfolio as a whole. These investors consider their portfolio as a set of mental arithmetic. In mental accounting, the conventional issue of maximizing the expected return is faced with the constraint of maximum likelihood to fail in achieving the return threshold. The present study extracts the capital asset pricing model from Markowitz Mean-Variance Portfolio Model and risk-free asset entering the limitations of this model. Then, MA-CAPM model is extracted by creating a mathematical equivalence between the components of this model and the limitation of mental accounting. In this model, expected investment return for any purpose presented in the form of mental arithmetic is a function of the return on risk-free asset, beta and risk premium of mental arithmetic where the risk premium of mental arithmetic equals the difference between returns of each account and risk-free return on assets. Expected rate of return on assets in the MA-CAPM will be influenced by return threshold and likelihood to fail in reaching this threshold, i.e. mental arithmetic risk. Manuscript profile

Open Access Article

2 - Comparision Between R-Campand and Fama and French three- Factor Model in Predicting the Expected Return in Tehran Stock Exchange
Z. Amirhosseini M. Khosraviani

In this paper we examine two capital asset pricing in tehran stock exchange, R-CAPM and fama and french‘s model to find best model according to condtion of Tehran stock exchange . RCAPM has a higher explanatory power to predict expected return. In this paper we ex More

In this paper we examine two capital asset pricing in tehran stock exchange, R-CAPM and fama and french‘s model to find best model according to condtion of Tehran stock exchange . RCAPM has a higher explanatory power to predict expected return. In this paper we examine two models in three perspective 1- EXPECTED RETURN EQUALS ACCTUAL RETURN WITH LAG +1. 2- EXPECTED RETURN EQUALS SIMPLE AVERAGE OF PAST RETURNS 3-EXPECTED RETURN EQUALS GEOMETRIC AVERAGE OF PAST RETURNS We consider expected return in each perspective as dependent variable and betas obtained from two models as independent variable. Three methods have been implemented to test hypothesis from 3 aforesaid perspective include Pearson correlation test, regression analysis and forecasting adaptation analysis. After examination we understand R-CAPM has more explanatory power in predicting expected return with first perspective. Manuscript profile

Open Access Article

3 - A study of APT and Adj-CAPM Models for Forecasting Expected Return
Z. Amirhosseini S. Mohseni Behbahani

The question in a Securities of Iran is which one of models of pricinghave better and more precise result in financial science for pricing stocksof company. In this research the expected return will be explaining inAdj-CAPM on the basis of liquidity and in APT on the ba More

The question in a Securities of Iran is which one of models of pricinghave better and more precise result in financial science for pricing stocksof company. In this research the expected return will be explaining inAdj-CAPM on the basis of liquidity and in APT on the basis of set ofrisk«price of oil, price of gold, inflation, and rate of foreign exchange,rate of interest and index of stock exchange». The main purpose of thisresearch is the examination of ability explaining Arbitrage pricing theoryand Liquidity adjusted capital assets pricing model. For this purpose,first, the Betas have been computed, and then according to betas,expected return of two models will be computed. Therefore by usingRegression Analyzing and Pearson Correlation we will reach to this resultthat Arbitrage Pricing Theory has more performance and ability thanAdjusted Capital Asset Pricing Model. Manuscript profile

Open Access Article

4 - Evaluating stock returns using a combination of multi-factor pricing model for capital assets and the function of penalty in Tehran Stock Exchange market and its comparison with five factors Fama and French Model
Aliakbar Farzinfar

10.30495/jfksa.2023.21899

evaluating the return on investment is one of the main concerns of investors, which is conducted using different models including the single-factor model CAPM, three and five factors Fama and French, and six factors Roy and Shijin, etc. known as multifactorial models. I More

evaluating the return on investment is one of the main concerns of investors, which is conducted using different models including the single-factor model CAPM, three and five factors Fama and French, and six factors Roy and Shijin, etc. known as multifactorial models. In spite of the widespread use of the models, their main disadvantages include sensitivity to unexpected changes, sudden shocks, severe turbulence of price bubble, and so on. To solve the disadvantages, a multi-factor model is estimated based on the use of the penalty function method, instead of using the average method, which would act based on optimization and avoiding the impact of unusual changes and other factors affecting the capital market. It is possible to select effective factors and model to evaluate stock returns and present a model appropriate to the conditions prevailing in the Iranian capital market. In this article, the classification and estimation of the integrated model of penalty and multi-factor (P & PCA) was performed by forming investment portfolios and identifying the effective factors and refining it based on performance data over a period of time. The study results showed that the use of an extensive simulation algorithm for penalty function by estimation method (P & PCA) improves the efficiency of multifactorial methods in evaluating stock returns. The use of the finite and multi-factor combination algorithm has higher accuracy and explanatory power during the review period in estimating stock returns than the 5-factor Fama and French model. Manuscript profile

Open Access Article

5 - Review and Assessment of Capital Assets Pricing Models and Compare Them with the 5-Factor Model of Fama and French “Using Economic Variables Exchange; Rates, Inflation, Import and Liquidity”
Mohammad Hossein Ranjbar Hossein Badiee Maysam Mohebi

The present research tries to assess and compare the Capital Asset Pricing Models in stock exchange of Tehran. Financial data of 108 companies in stock market (2009-2014) are processed. The important issue is to use suitable patterns and models for evaluating and price More

The present research tries to assess and compare the Capital Asset Pricing Models in stock exchange of Tehran. Financial data of 108 companies in stock market (2009-2014) are processed. The important issue is to use suitable patterns and models for evaluating and price setting in stock market. These models must have the ability to predict the behavior of the prices and also can estimate the outcome and efficiency of the so-called investment. The models investigated in this research, include the traditional investment financial pricing, 3-factor model and FAMA and French 5-factor and consumption investment models. In order to analyze the data and to test the hypothesis, we used OLS model for time series models. In this study, models are investigated according to the models of significance lateral distance from the source (Jensen's Alpha). A model, of which efficiency is high, should have a zero intercept. Generally, FAMA and French 5-factor models that were developed in 2014, work more efficiently. Then comes the Capital Asset Pricing Model Manuscript profile

Open Access Article

6 - A meta-analysis on the capital asset pricing model
Saeed Fathi Farideh Tavakoli Iman Ostad

Capital asset pricing model is an equilibrium model to show the relationship between systematic risk and return of capital assets and indicate the pricing of assets due to their systematic risk. Abundance of empirical studies in testing standard and developed CAPM shows More

Capital asset pricing model is an equilibrium model to show the relationship between systematic risk and return of capital assets and indicate the pricing of assets due to their systematic risk. Abundance of empirical studies in testing standard and developed CAPM shows the importance of CAPM in estimating the price of financial assets. The meta-analytic approach of this paper creates a distinct realization to this context of finance by using of variance analysis, correlation test and means difference. So we use the statistical results of 418 CAPM tests during 1972 to 2016. The results show that time period of the test, type of portfolio ranking, country development grade, type of systematic risk and the type of CAPM test have a significant effect on the price of beta. Manuscript profile

Open Access Article

7 - Testing the application of inflows (outflows) of mutual funds in the assessment and prioritization of asset pricing models
Masoome Khermandar Hamid Reza Vakilifard Ghodrat Allah Talebnia Ramezan Ali Royaee

In this research, a new method based on quantitative variables, instead of price and return variables, has been presented to evaluate and prioritize capital asset pricing models. The present study, using capital inflows (outflows) of mutual funds (quantitative variable) More

In this research, a new method based on quantitative variables, instead of price and return variables, has been presented to evaluate and prioritize capital asset pricing models. The present study, using capital inflows (outflows) of mutual funds (quantitative variable), has determined the model of capital asset pricing models (CAPM, F-F, F-F-C, CCAPM) that is mostly used by investors to decide on a allocation of capital. This study uses the data of mutual funds in the capital market of Iran during the period 1392 to 1396, and with the implementation of ordinary least squares regression (OLS) this method has been presented. Manuscript profile

Open Access Article

8 - Explaining the Role of Investors' Sentiment in Capital Asset Pricing
Ali Kiamehr Mohammad Hassan Janani Mahmoud Hemmatfar

The purpose of this study was to explain the role of investors' emotional tendencies in pricing the capital assets of companies listed on the Tehran Stock Exchange. For this purpose, information of 150 companies from the financial reports of companies listed on the Tehr More

The purpose of this study was to explain the role of investors' emotional tendencies in pricing the capital assets of companies listed on the Tehran Stock Exchange. For this purpose, information of 150 companies from the financial reports of companies listed on the Tehran Stock Exchange have been collected and tested. Findings show that in all three capital asset pricing models (Fama and French three-factor model, (2001) Kahrat four-factor model and Fama and French five-factor model, (2014) investors' emotional tendencies in price The investment of capital assets has an effect and increases the sheer risk of the portfolio.The results also show that in all three pricing models, presenting a capital asset pricing model based on investors' emotional tendencies increases the predictive power of common capital asset pricing models. Manuscript profile

Open Access Article

9 - Performance Evaluation of risk premium measurement models: q-theory asset pricing model against three factor model of fama and french
Gholamreza kordestani Mozhde Ghasemi

Financial scholars have made valuable efforts to measure risk premium. Recently, Chen et al (2010) proposed a three factor model based on market factor, investment factor, and profitability factor for explaining stock return and called it q-theory model. Prior researche More

Financial scholars have made valuable efforts to measure risk premium. Recently, Chen et al (2010) proposed a three factor model based on market factor, investment factor, and profitability factor for explaining stock return and called it q-theory model. Prior researches have shown that this model reduces the magnitude of the abnormal returns of a wide range of anomalies. This research examines the performance of new model in explaining the risk premium of the individual stock and portfolio of stock, and compares it with the performance of CAPM and three factor model of Fama and French in stock exchange market. Sample under investigation consist of 72 listed companies for the period of 1386-1391. The results show that risk premium of stocks has a significant relationship with the sensitivity of its returns to investment and profitability factors. Furthermore, q-theory model significantly excel CAPM in explaining risk premium of firm size, book to market value and momentum portfolios. But it significantly excels three factor model of Fama and French just in explaining the risk premium of momentum portfolios. Manuscript profile

Open Access Article

10 - The Integration of Multi-Factor Model of Capital Asset Pricing and Penalty Function for Stock Return Evaluation
Aliakbar Farzinfar Hossein Jahangirnia Hasan Ghodrati Reza Jamkarani

10.22034/amfa.2019.584793.1180

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Open Access Article

11 - Higher moments portfolio Optimization with unequal weights based on Generalized Capital Asset pricing model with independent and identically asymmetric Power Distribution
Bahman Esmaeili Ali Souri Sayyed Mojtaba Mirlohi

10.22034/amfa.2020.1909590.1484

Manuscript profile

Open Access Article

12 - Studying the Expected Returns Based on Carhart Model Com-pared to CAPM Model and Implicit Capital Cost Model Based on Cash and Capital Flow of Growth and Value stocks
Akram Khani Farahani Majid Sheshmani Ali Mohades

10.22034/amfa.2017.536267

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Open Access Article

13 - The Effect of Capital Productivity Management on Capital Asset Pricing Models with a Focus on Life Cycle
ali alimohammadpour ali zabihi khosro Faghani Makrani

10.30495/qjopm.2020.671975

Capital productivity concerns the measurement of management power in making optimal use of capital as one of the important and limited company resources. In companies with highly efficient capital productivity, stocks are expected to offer higher returns and the explana More

Capital productivity concerns the measurement of management power in making optimal use of capital as one of the important and limited company resources. In companies with highly efficient capital productivity, stocks are expected to offer higher returns and the explanatory power of the models proposed to predict stock returns is assumed to increase. The purpose of this study was, thus, to examine the extent to which capital productivity might influence the explanatory power of stock market predictive models and to scrutinize this viable effect at various stages of corporate life cycle. The Operating Profit Ratio (ROIC) was used to operationalize Capital productivity, the Tripartite Factor Model (Fama & Franch, 1993) and the Pentagonal Factor Model (Fama & Franch, 2013) were employed to predict stock returns and corporate life cycle was categorized via the Dickinson Cash Flow (2011). The research sample comprised 110 companies with specific descriptive characteristics selected from among all those listed on the Tehran Stock Exchange during a ten-year period from 2005 to 1394. The results of the hypothesis testing analyses demonstrated that capital productivity affects the relationship between market factor and risk-free growth at all stages of the life cycle, but size was found significantly correlated with risk merely at the maturity stage of the life cycle. Manuscript profile

Open Access Article

14 - Comparison and analysis of stock futures return response to non-systematic risk torque measurement models(comparative prediction with neural network
roqaye talebi

Abstract The mean and variance of stock returns alone are not sufficient to describe the distribution of returns. , paying attention to higher torques such as skewness and kurtosisas a risk index instead of variance leads to more accurate results. Therefore, due to stu More

Abstract The mean and variance of stock returns alone are not sufficient to describe the distribution of returns. , paying attention to higher torques such as skewness and kurtosisas a risk index instead of variance leads to more accurate results. Therefore, due to study contradictions, the study of stock returns reaction to models for measuring non-systematic risk moments was significant. For this purpose, 152 companies were selected( In the realm of time between 2014to 2021 ) as a statistical sample from the companies listed on the Tehran Stock Exchange based on the systematic removal method (CAPM & FF3). Also, by determining the superior regression model, the power of the superior regression model was compared with the neural network model. results showed that by increasing the unsystematic risk torques calculated with the capital asset pricing model and the Fama and French tree-factor model reduce future stock returns; These results can be justified in line with the concepts of capital market efficiency theory.Other results indicate that the difference in expected non-systematic risk calculated with CAPM and FF3 models is significant. Therefore, the strength of the expected non-systematic risk torques calculated by the capital asset pricing model is less than the Fama and French three-factor model. By comparing the neural network model coefficient and linear regression, it can be said that the neural network-based model has a better performance in predicting future stock returns based on non-systematic risk moments than linear regression. Manuscript profile

Open Access Article

15 - A comparison between,CAPM,Fama and French,s models and artificial neural networks in predicting the Iranian stock Market
S.M Jafari جواد Misaghi میثم Ahmadvand

Comparison between the Capital Asset Pricing model,Fama and Ferench three factors model and Artificial Neural Network model in predicting Tehran stock Exchange returns is discussed in this research.the first two models are linear and the following are nonlinear.Four hyp More

Comparison between the Capital Asset Pricing model,Fama and Ferench three factors model and Artificial Neural Network model in predicting Tehran stock Exchange returns is discussed in this research.the first two models are linear and the following are nonlinear.Four hypotheses have been designed for this purpose.To examine these hypotheses,the expected return was calculated daily during 1383 to 1387 for 110 companies.companies in each quarter have divided to 6 portfolios by size and book to market value factors. Results showed that the performance of Fama &Ferench three factors model is better than Capital Asset pricing model.Also Univariable and Multyvariable Artificial Neural Network models have better performance in compare with their corresponding nonlinear models. Manuscript profile

Open Access Article

16 - Higher moments Portfolio Optimization based on Generalized CAPM with asymmetric power distribution and fat tail
Ali Souri Saeid Fallahpour Bahman Esmaeili

Every investor wants to select the optimal combination of return and risk in order to maximize their utility. In this study, an attempt was made to explain the optimal model for estimating returns and risk in cases where there is a financial crisis and the distribution More

Every investor wants to select the optimal combination of return and risk in order to maximize their utility. In this study, an attempt was made to explain the optimal model for estimating returns and risk in cases where there is a financial crisis and the distribution of return on assets does not follow the normal distribution.For this purpose, we use CAPM with independent and identically asymmetric power distribution (CAPM-IIAPD) and CAPM with independent identically saymmetric exponential power distribution with two tail parameters (CAPM-IAEPD) instead of traditional CAPM. When the assumption of normality is violated, higher moments are used to optimize the model. In the next step, using Polynomial Goal Programming, we calculate optimal portfolios with third and fourth moments.The time horizon of the research from 2011 to 2018 and the statistical population has been all the companies of Tehran Stock Exchange, among which 30 companies have been selected.The results show that CAPM-IIAPD Model is the best model among three models and the adjusted return on risk in optimized models with thirs and fourth moemnts in generalized CAPM models is significantly different from the traditional model and has a better performance. Manuscript profile

Open Access Article

17 - Energy Portfolio Returns Explanation Using Fama & French Five-Factor Model
Mohammad Yousefian Amiri Babak Shirazi Ali Tajdin Hossein Mohammadian Bisheh

Investing in the Iran Energy Exchange is one of the ways to achieve returns. Among the capital asset pricing models, one of the most important new tools for risk and return determination is the Fama and French five-factor model. In this study, we examined the power of e More

Investing in the Iran Energy Exchange is one of the ways to achieve returns. Among the capital asset pricing models, one of the most important new tools for risk and return determination is the Fama and French five-factor model. In this study, we examined the power of explaining the return on investment portfolio consisting of 40 companies operating in Iran Energy Bruce from 2009 to 2018 using the five-factor model of Fama and French. For this purpose, we have used F-Limer and Hausman statistical tests and multivariate regression analysis method in three-factor and five-factor models of Fama and French to explain the efficiency of energy portfolio returns. The results of this study show that by adding the two factors of profitability and investment to the three-factor model, the coefficient of determination increases from 0.85 to 0.96. Among these five factors, the value factor has the greatest impact on energy portfolio returns. Also, with the addition of market factors, the value and profitability of energy portfolio returns increased, but size and investment factors were inversely related to energy portfolio returns and reduced it. Manuscript profile

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