Ahmad Ahmadpoor; Amir Hosein Azimiyan Moez
Volume 12, Issue 46 , October 2012, , Pages 27-42
Abstract
Studying and quantifying the relationship between risk and return and identifying factors affecting the return have always been in the interest of researchers in the field of finance. Researches have shown that multi-factor models have higher power in explaining stock returns when compared with single ...
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Studying and quantifying the relationship between risk and return and identifying factors affecting the return have always been in the interest of researchers in the field of finance. Researches have shown that multi-factor models have higher power in explaining stock returns when compared with single factor models. Fama and French (1993) presented a three-factor model including market portfolio, size and the ratio of book value to market value to describe market return. The aim of this study is to add a new variable, assets growth, to this model and make a four-factor model to have a better analysis and to make a better prediction of stock market return in Tehran Stock Exchange. To accomplish this purpose, the impact of assets growth on stock return is considered under two different models which in one of them, it is not controlled for the effects of the two variables of size and the ratio of book value to market value, and in the other one, these variables are included in our model. The data are examined over a 10-year period (2000-2010) using Eviews software, and the results show that although assets growth independently does not have any significant impact on stock return, when it is added to a three-factor model that was introduced by Fama and French , it will have a negative impact on stock market return.
reza tehani; Shapur Mohammadi; Arash Mohamadalizadeh
Volume 11, Issue 41 , July 2011, , Pages 225-244
Abstract
This paper presents a new perspective on the Fisher hypothesis, which states a positiverelationship between nominal stock returns and inflation. The new approach is based on a waveletmultiscaling method that decomposes a given time series on a scale-by-scale basis. The time series of inflation and stock ...
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This paper presents a new perspective on the Fisher hypothesis, which states a positiverelationship between nominal stock returns and inflation. The new approach is based on a waveletmultiscaling method that decomposes a given time series on a scale-by-scale basis. The time series of inflation and stock return are decomposed into three wavelet details and one wavelet smooth. Empirical results show that there is a positive relationship between stock returns and inflation at 2month period and at 8-month period, while a negative relationship is shown 4-month period. Also,no significant relationship was revealed in one month time horizon. This indicates that the nominal return results are supportive of the Fisher hypothesis for risky Assets in d2 and s3 of the wavelet domain, while the stock returns do not play a role as an inflation hedge at one month and four month timescales.
Hmidreza Vakilifard; Alireza Zareie
Volume 9, Issue 34 , October 2009, , Pages 113-133
Abstract
According to the Arbitrage Pricing Theory (APT) actual returns depend on a variety of pervasive economic and financial risk factors ; as well as firm or industry specific influences. The sensitivity of an asset’s returns to unanticipated changes in the perspective risk factors reflects the security’s ...
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According to the Arbitrage Pricing Theory (APT) actual returns depend on a variety of pervasive economic and financial risk factors ; as well as firm or industry specific influences. The sensitivity of an asset’s returns to unanticipated changes in the perspective risk factors reflects the security’s measure of systematic risk. In equilibrium, the expected security return is a linear function of the sensitivities of actual security returns to unanticipated changes in the pervasive risk factors. The APT does not specify the number or the nature. Factor analysis of stock returns can be used to determine sensitivities of individual securities to pervasive risk factors without having to identify these risk factors. In this paper, we imperially tested following question; ‘Can we used traditional accounting risk measures from the current period to explain cross-sectional variations of the APT risk measures (sensitivities) in the next period? The empirical
analysis was carried out using a sample include 42 firms from Tehran Stock Exchange and covered 1999-2005. The dependent variables were the APT risk measures, derived from principal factor analysis of monthly stock returns. The set of independent variables was an extensive list of traditional accounting risk measures associated with a firm’s operating and financial activities. The accounting risk measures used in this study represented the firm’s liquidity, dept management, profitability and efficiency, business risk and market value (hybrid ratio), as well as the size of the company. Relying on predictive correlation and multiple regression analysis and application of panel data models, an association was established between independent and dependent variables. the model significance was tested by F statisticand observed significant association in case of accounting variables. Traditional accounting variables some deal can explain cross-sectional variations of the APT risk measures in next period.
Ahmad Yagoobnezhad
Volume 7, Issue 25 , July 2007, , Pages 253-277
Abstract
The study of the relationship between stock return and accounting earning is so critical for studying of the efficiency of capital market as well as for evaluating the usefulness of information on financial statements. Accounting earning is one of the most important items of the financial statements ...
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The study of the relationship between stock return and accounting earning is so critical for studying of the efficiency of capital market as well as for evaluating the usefulness of information on financial statements. Accounting earning is one of the most important items of the financial statements used by stakeholders as a basis for making decisions and predictions. By using six different models, this study attempted to investigate the relationship between the return and accounting earning. The results of this relationship, then, were compared with the cash flow model which studies the relationship between stock return and cash flow. Despite other studies, this study tried to evaluate the explanatory power of each of the proposed models in the long run. The researcher wanted to find an answer to the research question: "Which one of the variables of earning or cash flow is more powerful in explaining the long run return?" Moreover, the other important question was to discover: "Which model is more suitable for investigating the relationship between the variables mentioned in basic financial statements and stock return?" The results showed that in all models the correlation coefficient increased as the measurement interval was lengthened. However, there was not a significant difference among the correlation coefficients obtained from the different models. Accounting earning was the only variable which in all levels and in all models had a meaningful correlation with return. Furthermore, the results showed that there was a meaningful relation between the stock return and cash obtained from operational activities in a long interval. However, the explanatory power of earning models in the long run was more than the cash model.
