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Open Access Article
1 - The investigation of the affectivity of various types of cash flows in a diversified capital structure based on the type of strategy
Mehrdad Ghanbari Mahsa MoradiThe intensity of competition in business markets is to the extent that even the slightest strategic mistakes will lead to the failure of the organizations. The lack of knowledge and implementation of appropriate competitive strategies in such markets and, on the other h MoreThe intensity of competition in business markets is to the extent that even the slightest strategic mistakes will lead to the failure of the organizations. The lack of knowledge and implementation of appropriate competitive strategies in such markets and, on the other hand, the failure to review the effects of these strategies on the types of cash flows in diverse capital structures is no also an exception to this rule. The subject of this study is to design and explain the affectivity model of types of cash flows in a diversified capital structure based on the type of strategy. The present study is an applied one in terms of objective, a quantitative one in terms of data type and a descriptive survey one regarding how to conduct. The statistical population consisted of all companies listed on the Tehran Stock Exchange during 2013 to 2017, among which 139 companies were selected as the sample by systematic elimination method. The statistical method used is the panel data method and fitting the regression models has been conducted using the same data. The results indicated that there is no significant difference between the effect of the differentiation strategy on the cash flow of accounting and cash flows to equity in companies that have a debt-based capital structure with companies whose capital structure is based on equity. Manuscript profile -
Open Access Article
2 - Information Asymmetry with Emphasis on the Role of Financial and Managerial Criteria Based on Fuzzy Logic and Artificial Neural Networks
Mohammad Amir Golshani Mehrdad Ghanbari Babak Jamshidi Navid Forouzan Mohammadi YarijaniThis paper addresses the absence of a suitable criterion for measuring information asymmetry between managers forecasting earnings and analysts forecasting earnings through statistical methods. Besides, this paper aims to provide a model of information asymmetry, emphas MoreThis paper addresses the absence of a suitable criterion for measuring information asymmetry between managers forecasting earnings and analysts forecasting earnings through statistical methods. Besides, this paper aims to provide a model of information asymmetry, emphasizing the role of financial and managerial criteria. This is applied qualitative and quantitative research (mixed method). The library method is used to prepare and formulate theoretical bases. In addition, the field method is used for collecting data to measure and identify indices and modeling. Factor analysis was used to analyze the data, following identifying the dimensions and variables of financial and managerial criteria of information symmetry to eliminate extraneous factors and classify. The following five main dimensions were determined, including corporate profit forecast, corporate governance, capital market, capital return, and management characteristics of the company. Then, the modeling was done using fuzzy mathematics through triangular numbers, Mamdani implication, and center of gravity methods. The final results of the study of the company listed on the Tehran Stock Exchange show that the level of information symmetry in the range of zero to 100 equals 55.1, to predict the company's profit is 48.54; corporate governance is 56.95; the capital market is 1/59; capital return is 61.07, and managerial characteristics of the company are 67.84. Finally, we examined the factors affecting the information asymmetry obtained from fuzzy neural networks. The findings show a higher prediction accuracy of fuzzy neural network methods than other related prediction methods. Manuscript profile -
Open Access Article
3 - The role of aggregate cost stickiness in unemployment rate prediction
Naser Riyahinasab Babak Jamshidinavid Alireza Moradi Mehrdad GhanbariPredicting macroeconomic indicators is very important for policymakers and economists. Unemployment is one of the key indicators of macroeconomics that has adverse economic and social consequences. So far, many models have been proposed to predict this variable, but mod MorePredicting macroeconomic indicators is very important for policymakers and economists. Unemployment is one of the key indicators of macroeconomics that has adverse economic and social consequences. So far, many models have been proposed to predict this variable, but models in which accounting information was used to predict unemployment rate were ignored. The purpose of this paper is to investigate the relationship between aggregate cost stickiness, as one of the known variables in accounting, and unemployment rate. To this end, seasonal macro level time series data of Tehran Stock Exchange (TSE) and macroeconomic data are analyzed in two stages from 2008:2 to 2018:1. In the first stage, the relationship between these two variables is determined by specifying a linear regression model that is estimated using the OLS method. To investigate the predictive power of this model, the RMSE criterion was estimated in two scenarios with and without aggregate cost stickiness. Secondly, the reaction of the unemployment rate in response to a shock from aggregate cost stickiness is estimated by a Vector Autoregressive (VAR) model and the share of this variable is measured in the fluctuations of unemployment rate. The results show that aggregate cost stickiness improves the forecast of unemployment rate in the horizon previous. Also, the shock of aggregate cost stickiness explains about 6.5 percent of unemployment rate fluctuations. Manuscript profile -
Open Access Article
4 - The improved Semi-parametric Markov switching models for predicting Stocks Prices
Hossein Naderi Mehrdad Ghanbari Babak Jamshidi Navid Arash NademiThe modelling of strategies for buying and selling in Stock Market Investment have been the object of numerous advances and uses in economic studies, both theoretically and empirically. One of the popular models in economic studies is applying the Semi-parametric Markov MoreThe modelling of strategies for buying and selling in Stock Market Investment have been the object of numerous advances and uses in economic studies, both theoretically and empirically. One of the popular models in economic studies is applying the Semi-parametric Markov Switching models for forecasting the time series observations based on stock prices. The Semi-parametric Markov Switching models for these models are a class of popular methods that have been used extensively by researchers to increase the accuracy of fitting processes. The main part of these models is based on kernel and core functions. Despite of existence of many kernel and core functions that are capable in applications for forecasting the stock prices, there is a widely use of Gaussian kernel and exponential core function in these models. But there is a question if other types of kernel and core functions can be used in these models. This paper tries to introduce the other kernel and core functions can be offered for good fitting of the financial data. We first test three popular kernel and four core functions to find the best one and then offer the new strategy of buying and selling stocks by the best selection on these functions for real data. Manuscript profile -
Open Access Article
5 - The Improved Semi-Parametric Markov Switching Models for Predicting Stocks Prices
hossien naderi Mehrdad Ghanbari Babak Jamshidi Navid Arash NademiThe modeling of strategies for buying and selling in Stock Market Investment have been the object of numerous advances and uses in economic studies, both theoretically and empirically. One of the popular models in economic studies is applying the Semi-parametric Markov MoreThe modeling of strategies for buying and selling in Stock Market Investment have been the object of numerous advances and uses in economic studies, both theoretically and empirically. One of the popular models in economic studies is applying the Semi-parametric Markov Switching models for fore-casting the time series observations based on stock prices. The Semi-parametric Markov Switching models for these models are a class of popular methods that have been used extensively by researchers to increase the accu-racy of fitting processes. The main part of these models is based on kernel and core functions. Despite of existence of many kernel and core functions that are capable in applications for forecasting the stock prices, there is a widely use of Gaussian kernel and exponential core function in these mod-els. But there is a question if other types of kernel and core functions can be used in these models. This paper tries to introduce the other kernel and core functions can be offered for good fitting of the financial data. We first test three popular kernel and four core functions to find the best one and then offer the new strategy of buying and selling stocks by the best selection on these functions for real data. Manuscript profile
List of Articles مهرداد قنبری
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