مجله راهبرد مدیریت مالی
سال هفتم شماره 4 (پیاپی 27، زمستان 1398)

Index tracking is an important issue in portfolio theory. Index tracking is a passive approach in the portfolio optimization problem based on which finite stock should be selected to track the benchmark index. Enhanced index tracking is a selection of the portfolio with limited stock so that its return is maximized and track error is minimized without buying all stock in benchmark portfolio. The main aim of this paper was to propose a two-stage mixed integer model for enhancing portfolio performance. In order to show the approach performance, top 50 companies were traced. Return, tracking error, excess return and information ratio were used as Portfolio performance measurement. Genetic Algorithm and Pattern Search Algorithm were also used to solve the models.  The findings showed that the two-stage model was better than one stage model. Likewise, pattern search enjoyed higher performance than Genetic Algorithm in the two-stage model. Therefore, two-stage model had higher performance during pattern search algorithm compared to one stage model or Genetic algorithm.

Modeling and evaluation of capital asset pricing is one of the most important branches in financial economics and economic growth. Consequently, development of countries’ stock market can play a significant role in optimal allocation of financial resources. The main purpose of this study was to modeling capital asset pricing in a quantitative general equilibrium model with growth options for intangible capital. This article was thus modeled based on the component of long run risk, intangible capital and with recursive preferences due to the failure in predicting conditional capital asset pricing models(C-CAPM). The framework thus explains the observed difference between the book-to-market ratios by intangible capital. In this model, growth stocks are of lower exposure to aggregate productivity risk than value stocks. This article also explains the dynamics of consumption and investment within the framework of the general equilibrium for Iran's economy. The findings show that young firms have idiosyncratic volatility more than older firms and the relationship between book-to-market ratio and aggregate productivity growth is negative. In other words, aggregate productivity growth has a different effect on firm heterogeneity at the firm age and capital age.

This study examines the importance of financial information properties for investors by estimating accruals quality and operating volatility criteria revealed from observed stock prices. The accruals quality parameters were measured based on model developed by Nikolaev (2018), which separates volatility of accounting error from volatility of accruals performance component. The research hypotheses were tested using a sample of 93 companies listed in Tehran Stock Exchange between 2002 and 2017 using multiple regression based on combined data technique. The results show that traditional accrual quality criteria such as Dechow & Dichev (2002) does not enable us to measure the effect of accruals quality on firm value. However, following Nikolaev (2018)’s model which decomposes total volatility of accruals to accounting error and performance component indicate that accruals quality have a statistically significant relationship with firm value. Furthermore, a 1% increase in the volatility of accounting error results in a 0.3% increase in the firm value and a 1% increase in the operating volatility results in a .43% decrease in the firm value.  Overall, findings suggest that effect of financial information quality on the firm value is affected by operating risk.

:This  research  addresses the identification and evaluation of management characteristics including management Optimism, management myopia, management Conservatism, management forecast accuracy, management structure and management ability on stock price crash risk  in the companies listed on Tehran Stock Exchange for the first time. In order to meet the research objective and to test the hypothesis, 165 companies listed during the years 2006-2017 were selected. The panel data set was analyzed based on a multi-variable regression. Findings showed that among the various management characteristics, two characteristics, namely managerial myopia and management forecast accuracy enjoyed the greatest impact on stock price crash in the listed companies. Furthermore, any increase in the management myopia gave rise to an exponential and significant increase at the level of stock price crash companies. Capital market has also shown a significant reaction to the management myopia of the company when the stock price crash increased. Other findings also indicated that the stock price crash is reduced with an increase in management forecast accuracy. Any increase in management optimism led to improving management structure. With an increase in management ability, the level of stock price crash companies reduced and the higher conservatism of managers was followed by increases in Stock Price Crash Risk though these results were not statistically significant

Overconfidence is the most obvious bias at the micro level of behavioral finance. This research studies the effect of manager's overconfidence based on capital expenditure and investment on risk indexes (stock returns deviation and operating cash flow deviation) and capital productivity in the listed companies in Tehran Stock Exchange. In this research, 132 companies were surveyed during 2012-2017. In order to test the hypotheses, the panel regression model has been used. The research findings show that manager’s overconfidence based on capital expenditure does not have any significant effect on stock returns. Rather, overconfidence based on investment has a significant direct effect on stock returns deviation. It means that overconfident managers meet risk and invest on risky projects .Themanager's overconfidence (based on capital expenditure and investment) does not have any significant effect on operating cash flow deviation and capital productivity.

Considering the possible restrictions on the provision of facilities, bank managers need to facilitate the decision-making process of allocating bank's funds in the form of Islamic facilities and contracts. It thus requires them to take into account the goals of optimizing the efficiency and minimizing default risk.   In this research, three nonlinear programming models (two objective functions and one objective function) and an ideal programming model were used to optimize the convenience portfolio of the Ansar bank. Given the number of constraints, the variables and the nature of the models, a genetic algorithm was used to solve the problem. In mathematical modeling, the problem of optimizing the loan portfolio of bank is considered to be policy limits, budget and capital adequacy. As the results showed, the optimal solution presented with the actual amount of the allocated facility to the bank's micro-banking group has difference in terms of profit and default risk. Also, these answers could improve the balance of facilities in the type of contracts and customer groups in relation to lending, along with other constraints. Among the models presented, a model that minimizes default risk in itself enjoyed the best performance compared to other introduced models

Companies face everlasting challenges to survive. Successful introduction to a market and competition is always with a high level of uncertainty and is limited in many ways. Thus, a huge number of companies especially the ones founded recently leave the capital market very soon. Theoretically embedded in Putang (2011)’s  model, this study is to develop a model for the survival of companies using the causative relationships between sustainability of accounting and survival of companies with an emphasis on moderating role of desirable market value, motivational commitment of employees and acceptance of prominent stakeholders.  The population in this study included a set of selected companies. The data were also collected using a standard questionnaire. Firstly, the reliability and validity tests were administered on sample data. Then, based on the model of Lineal Structural Relations, the data were analyzed. Findings revealed that that survival of companies is affected by acceptance of prominent stakeholders. In other words, recognition of the overt role of stockholders, responsibility toward welfare in society and ethical responsibilities increase the survival rate for companies. Furthermore, sustainability of accounting (awareness of accounting ethics, voluntary accounting activities, transparency of accounting ideology, divulging human capital and reporting social responsibility) significantly affect desirable market value, motivational commitment of employees and acceptance of prominent stakeholders.

The main objective of this study was to investigate whether searching firm's ticker symbol and name in Google can predict its future stock market activities. In so doing, the data related to firms' ticker symbol and firms' name were collected using Google Trend and stock market activity was measured using four proxies, namely abnormal return, return volatility, stock trading volume and stock trading count. In order to meet the main objective of the study, multiple regression and panel regression were used over13082 firm- month observation during the years between 2005 and 2018. The results showed that the future market activity, including return volatility, stock trading volume and stock trading count, increased with searching the firms' ticker and name in Google. However, there was no significant relationship between the future abnormal return and Google searches. Findings also showed that future market activity can be predicted using Google searches. In addition, there was a more significant relationship between the searched firms' ticker symbol than the searched firms' name and future market activity.