فصلنامه دانش سرمایه گذاری
پیاپی 26 (تابستان 1397)

Several studies have confirmed with using criteria appropriate to the structure and characteristics of the data, the performance of the models significantly improved. The Copula function is one of the models in determining the relationship between variables has attracted a lot of attention. In this study, we investigated the portfolio of TSE industry indexes optimized to minimize the Conditional Value at Risk, simulated data based on Copula function and generalized Pareto distribution as input. The statistical analyzes implies portfolio performance improves significantly. Since the Copula functions are diverse, Compare the impact of any one risk reduction is recommended.

Among 37 methods to reduce transaction costs introduced by Cha (2007), we recursively choose the best method for next period's investment in each of three portfolio strategies: Mean-Variance Optimization, Mean-CVaR Optimization, and the equally-weighted market. We identify a few of the best methods and offer a framework by which additional methods can be considered. Within our framework, the best methods recapture a substantial amount of wealth and significantly improve risk-adjusted performance, both economically and statistically. We used prices and returns of the 10 most active firms of Tehran Stock Exchange market, from 1391 to 1394 on a monthly basis in this research. The transactions costs reduction methods will be applied on them and the best methods will be identified. Also, a framework will be offered for comparison and investigation of new methods.

The objective of this research is to study the necessary financial institutions for financing the infrastructure transport projects in Iran through the capital market. This study uses a mixed method. To prepare a primary framework, a systematic review was done and several half-structured interviews were undertaken with experts. To approve the primary framework, a survey of expert was done in a way that in the fields of roads, capital market and university, 42 questionnaires were filled, 28 interviews were carried out and 9 group meetings were held. Subsequently, the qualitative and quantitative results were compared and concluded according to the triangulation method. According to the experts consensus: undertaking some of securities charges, provision of emergency loans, guarantee syndication with banks, act as a reinsurer, support the formation of protection and indemnity association for the transportation industry, and issuance of insurance securities were proposed to be done by the Transport Development Fund. Furthermore doing the asset management of the Transport Development Fund by an expert institution and the development of Project infrastructure funds were emphasized.

In the present study,we examined the effect of the expected investment, expected profitability and the book to market ratio on the market expected returns.
Fama-French model(2006) was used To calculate the Expected profitability and the expected investment. expected return, market value and book to market ratio was calculated by conventional methods. with the aim of increasing comparability, the two growth variable number of shares and equity book value growth also has been used separately. study was conducted in two stages regression so that the first stage regressions to estimate the expected investment and profitability expected and second stage regressions also is used to examine the relationships between variables.
The results show that there is a significant positive relationship between the expected return and the expected profitability and book to market ratio. The relationship between the expected return and the expected investment is significant negative. The results confirmed all the hypotheses.

In this paper, effective factors, obstacles and various models of commercialization have been identified in ICT companies globally and Finally, has been proposed based on the PESTLE model, a native model for technology commercialization in domestic companies.
The results of this study showed that all six factors of PESTLE model are effective on technology commercialization; the most important effective factor is economics and the least effective factor is legislation. Also, sequentially, the most important factors affecting the commercialization of technology are specific laws in the IT industry, technology transfer and licensing, technological maturity,access to raw materials and energy, interest rates, consumer's attitude to goods and services, government allocation, outsourcing Technology, Immigration, Ethical Issues, New Product Development, Prospects for Future Policies, Income Distribution, Internal Economic Situation, and Intellectual Property Rights.

The main purpose of this research, The effect of transparency of information on the relationship between family ownership and cost of debt for companies in Tehran Stock Exchange. Statistical population consisted of 27 family and 76 nonfamily companies of the study period of 2009 to 2016 year-on behalf. In this study using a scores of ranking system of disclosure quality and information science Tehran Stock Exchange, for the separation of firms, the firms with low and high level of information disclosure. The statistical method, used in order to test the second research hypothesis, is panel data. The results of the first hypothesis of this research showed that there is a significant positive relationship between family ownership and cost of debt. In other words, the cost of debt in family firms is higher than nonfamily firms. Then, by examining the second hypothesis, it became clear that transparency of information on the relationship between family ownership and the cost of debt has a significant negative effect. This indicates the fact that the family enterprise-level higher information transparency, cost of debt decreases.

Algorithmic trading has become one of the main strategies in financial industry. This kind of trading involves trading strategies based on computer programs to decide whether to send their orders. Pairs trading strategy is one of the most popular and however, most understandable strategies in algorithmic trading. To implement a pairs trading strategy we can utilize several approaches or a combination of them. In this paper the distance approach has been considered. In this approach the two stocks that have least square distance between their normalized prices are being chosen for pairs trading. In this study, in order to implement this strategy, shares pair of metallic ores mining industry and price data in the year of 1395 have been selected. The strategies and the test, performance test trading strategies buy and hold strategy compared. In this paper all of stocks are selected from mining of metal ore industry during the first 9 months of the 1392 SH. Finally, the performance of pairs trading strategy is compared with buy and hold strategy and after that the favorable range of threshold and optimum threshold size is calculated.

In accordance with the objectives, qualitative and quantitative composition was operated. The strategy also phenomenography in qualitative section, in-depth semi-structured interviews conducted with experts capital market and analyzed using content analysis methods that eighteen components were identified. Whit this components the questionnaire of quantitative sectin was designed. A total of 400 questionnaires were distributed into available non random sampling and 275 completed questionnaires were collected. Data from the questionnaire using factor analysis to investigate and research the major issues such as cultural factors, cognitive, emotional, and personality were identified. Moreover, data through software SPSS and Amos Graphic using path analysis were analyzed. The results indicate that the most fundamental factor for the behavior of investors is culture. Cognitive bias etc. are precedence over emotional bias etc. (schema theory) alongside influence of personality, cause herding behaviors in the decision making private investors.

The aim of this study is to investigate the informational uncertainty as a criterion to explain stock returns by a behavioral approach to the companies listed on the Tehran Stock Exchange. The informational uncertainty criteria include the book value to market value (BV / MV), company age (Age), the size of the entity (MV), lowest price to the highest price of the stock ratio (LHR), the standard deviation of stock returns (STD) and the standard deviation of operating cash flow (CFVOLA). To investigate this issue a main hypothesis and four sub-hypotheses developed for this purpose and data of 99 companies of Tehran Stock Exchange was analyzed for the period 2007 to 2014. Results show that for all the variables except for STD (standard deviation of stock returns), by increasing the degree of informational uncertainty, stock returns trend increases for winning portfolios.

In this project, we study stock prices using behavioral financial methods to check stock prices of 50 companies from the Stock Exchange Organization during the years 2002-2013. We also want to compare the results of this method with the results of the methods of the stock price ratio to the Markov chain.
Behavioral financial-based research suggests that there are many exceptions to financial markets, and the results indicate that psychological phenomena play an important role in determining behavior in financial markets. It has been confirmed in studies that behavioral responses of investors can be considered as an important component in the market pricing process. A robust research that presents both reactive and non-reactive modes in the form of a model is Barbierz et al. In this model, investors estimate the possibility of returning to the average and the trend of prices using historical trend index and return to average, and based on that basis, they contribute to pricing, which is different from that of rational model.
Markov chain is also used for stock price analysis. In this regard, the stock dividend model is used to determine the inherent value of the stock in the Markov chain. The stock price review process converts to a linear system.
In addition, in the analytical method, the share price to profit (earning) ratio (P / E), is considered by analysts as a common practice in valuing stocks. The results showed that the P / E ratio was more stable with the help of different companies’ data. This ratio is used in the framework of the profit model from basic analysis.

The topic dividend policy is one of the most leading issues in modern corporate finance affecting the firm value. The results of linear methods and regression could not satisfy researchers in forecasting of financial issues such as dividend policy.
In this paper, we present a comparative analysis of the forecasting accuracy of univariate and multivariate Artificial Neural Network using a sample of 183 companies listed in the Tehran Stock Exchange through for the years 2011_2015.
This study shows that the application of the multivariate neural network model results in forecasts that are more accurate than Univariate neural network forecasting models. Our findings show that forecast of a multivariate ANN incorporating Marsh and Merton (1987) variables is more accurate than univariate ANNs. Therefore, based on the results of the study we suggest that shareholders, investors and other stakeholders use multivariate ANNs to predict dividend policy of companies listed in Tehran Stock Exchange.

The purpose of this study is to measuring the the effect of financing approaches on the total real rate of return of the Companies listed in Tehran stock exchange of listed companies in Tehran stock exchange. In this regard, we have tried to test some variables such as, cost of capital, Retained Earning, leverage, Profitability, firm’s Size to measure their impact on total real rate of return. In this study, at the first step there are 43 companies were studied in the field of producing companies and then there 39 companies were examined in the field of petrochemicals in the period from 1390 to 1394. At the next step, data is extracted from the financial statements of companies and then is analyzed by Eviews software and using panel data approach. The results show that research’s variables (incloading: cost of capital, Retained Earning, leverage, Profitability, firm’s Size) have positsve impact firm’s total real rate of return. It can be concluded that the relationship between financing approaches and independent variables. Finally, some recommendations are presented to inform shareholders and investors in this fims on how to use financing approaches.

The aim of this paper is to investigate and analyze the content of documents (including vision, mission, objective, ethic charter and fundamental values) of 36 bank and credit institution operating in the banking system without rabbis from the perspective of corporate governance in its categories and concepts. In this paper, after reviewing the literature of corporate governance and previous research on this subject , we review and analysis of documents Iranians banks and exploiting issues related to corporate governance, and assessing importance of this issue in Iranian banks and finally on this basis we ranking Iranian banks. Our research method is content analysis. The results suggest that attention to corporate governance and its implications in the documents Iranian banks is relatively low, Which reflects the significantly lower level of decision-making banks to corporate governance.

Fama and French (2015) with the addition of two more elements - operating profitability and investment - developed their three-factor model and offered a new five-factor model. This study aimed to test the Fama-French five-factor model compared with the three-factor and four-factor models.
For this purpose, a sample of 184 companies listed in Tehran Stock Exchange during the years 1380 to 1393 is examined. For testing the model, Portfolio analysis and test of Gibbons et al (1989) is used.
The results of this study revealed that operating profitability and investment are able to explain the return of portfolio. Fama-French five-factor model explains the excess return better than other models in Tehran Stock Exchange. Then four-factor model in different portfolios, depending on the factors made them, have better performance than three-factor models.

This study examines the characteristics of Financial Stress identified consistent with the literature research, including Uncertainty about Fundamental Value of Assets, Asymmetry of Information, Decreased Willingness to Hold Risky Assets and Decreased Willingness to Hold Illiquid Assets in four hypotheses. The research method is descriptive and correlational and to analyze the relation between independent and dependent variables, multiple regression statistical methods were used. Then, to test the research hypotheses, using data on firms listed in Tehran Stock Exchange, through the sampling cup, 95 companies were selected as samples. The present results confirm the hypothesis that show all the variables mentioned above are indicators of financial stress in the capital markets in Iran.

In this study, two models of intellectual capital and its relation to the market value of assets is measured. The statistical population included to participate in the period since 128 of 1,389th to 1393. The statistical methods used to analyze the data, multiple regression and correlation coefficients. For measuring intellectual capital in the study of the two methods is that one method mentioned by Palyk name (value added intellectual capital) proposed that the three components of effective physical capital, the efficiency of human capital efficiency and structural capital is the proposed approach to other Rostami lights criterion by which to measure intellectual capital by taking 4 performance (financial, economic, accounting, and Integration) is done, the firm size, leverage, and growth was considered as control variables. The overall conclusion regarding test performance on various measures of intellectual capital can be said is that the performance of the company (accounting practices, financial performance, economic performance, combined yield) were not significantly related to intellectual capital are the.

Being informed of capital market’s companies financial situation is one of the shareholders and economic analysts’ perturbation. Thus, financial market analysts and researchers were looking for methods to predict capital market’s company’s future conditions. This research is finding a model to predict bankruptcy of stock exchanges market’s companies with using the artificial neural network. In this research we used Zemijewski financial ratios with one macro – economic variable to predict companies’ bankruptcy. Population of study was selected from the accepted companies in Iran’s stock and exchanges organization. Financial ratios have been extracted from companies’ financial statement in a five years’ period between 2010 and 2014, finally we choose 84 companies that divided to salubrious and bankrupt equal number in each. We used multi-layer perceptron (MLP) with back propagation algorithm to create predictor model and data analysis. The network has been trained once with financial ratios and again with additional macro – economic variable to confirm that the accuracy of network model will increase by additional macro – economic variable. Ultimately the designed model in total mode has 92.95 percent of accuracy and 85 percent correct prediction of bankrupted companies for one year earlier of bankruptcy.

Price clustering is the tendency of prices to be round numbers. This phenomenon is studied in different countries and in various financial variables and several hypotheses have been put forth to explain that. In this study, existence of this price clustering and factors affecting on it is tested in Iran capital market. To this, high frequency data is used and by means of statistical tests, the existence of price clustering is observed in Iran capital market. Furthermore, among all variables, only size, price and a dummy variable to distinguish between Tehran stock exchange and Iran Farabourse exchange, were effective on the intensity of price clustering and despite the expectations, size variable has a positive coefficient. Results are corresponded to odd-pricing, price resolution (just for price variable and not for size) and negotiation hypothesis.