مجله مدیریت دارایی و تامین مالی
سال سوم شماره 1 (پیاپی 8، بهار 1394)

Evaluation of investment desicion has the decisive and key role in management discussions. Usually invest resources introduce methods such as accounting rate of return، payback period، internal rate of return and net present value (NPV) for decision making in this scope and describe the net present value as most reliable method. NPV and other traditional evaluation methods assume constant factors in investment and don’t consider uncertainty in decision making. The main objective of this study is to provide a model for evaluating investment decisions by using of system dynamics and real option. In this study، system dynamic method with Systemic approach was used to cover the weaknesses of traditional methods such as NPV that evaluate the investment decision one-dimensionally. Also، to considering the uncertainty in the investment project، real option was applied. At the final step، real option have been used as a scenario in designed model. Grounded Theory was applied for determining the affecting variables. Obtained results showed that investing about 3*1011 Rials to creating new production capacity about 300000 units per month with reducing product sale price from 1. 2 million Rials to 850000 Rials is most profitable state (scenario) of simulated model in specified time in software (end of tenth years). Also، expansion and contraction، two determined options were considered in a scenario and related results were obtained.

In this article، the fundamental signal analysis to evaluate the relative dominance of the winner-losser stocks based on investor’s preferences has been investigated. Therefore، based on factors related to the profitability، growth and variability the signals of information content of seven financial ratios are identified and based on winner-loser stock related to investr’s preferences identified. In this study، all the financial data of listed companies in TSE for the period 1380 to 1390 are used. The results indicated that the higher current and future return of winner stock related to losser stock one Period after portfolio formation. Also the further results indicate the second and third order of stochastic dominance of winner stocks relate to losser stocks and second and third order of stochastic dominance of losser stocks relate to winner stocks in the negative market conditions.

In this research، the relation of voluntary disclosure level and agency costs of listed companies of Tehran Stock Exchange is studied. In this regard، the effects of firm size، debt ratio، non-duty members of board and ownership concentration are considered either. In order to voluntary disclosure level measuring Botosan (1997) check list which has been adjusted by koshanipour and et al. (1388) and consists of 71 indices through six section of background information، the summery of important historical results، non-financial key statics، section data، anticipating information and managements’ analysis and discussion has been utilized. Moreover، operating expenses to sale ratio، the asset turnover ratio and Qtubin ratio are utilized as agency costs criteria. To main hypothesis testing multivariate regression with combined data has been used. Findings resulted from exploring 67 companies during period of 1382 to 1390 essay that although there are 1) a positive significant relation between operating expenses to sale ratio and voluntary disclosure level and 2) a negative significant relation between Qtubin ratio and voluntary disclosure level، there is no significant relation between assets turnover ratio and firms’ voluntary disclosure level.

Stock index as time series are non-stationary and highly noisy due to the fact that stock markets are affected by a variety of factors. It is regarded as one of the most challenging application of time series forecasting. Predicting stock index with the noisy data directly is usually subject to large errors. In this paper we compare forecasting the stock index via Wavelet De-noising-based Neural Network (WDNN) with forecasting stock index via single neural network. The daily Tehran Stock index from April 2006 to June 2013 are used to compare the application of the WDNN in predicting the stock index. Experimental results show that de-noising with wavelet transform outperforms the single neural network.

Presenting information which is useful for investors، creditors، and other current and potential users in decision makings related to investment and validating and other decisions is one of goals in financial reporting. The aim of this research is to study corporate governance mechanisms including managerial ownership، structure of board of directors، and board size on the relationship between institutional investors and inventory management in firms enlisted in Tehran Stock Exchange. To analyze data we have used a multiple variable regression by using generalized moments. Statistical sample in this research entails 47 companies which were enlisted in Stock Exchange during the time period between 2006 and 2011. Control variables in this research were firm growth، firm size، financial leverage، profitability، capital intensity، age، and private ownership. Results of analyzing data showed that managerial ownership affected the relationship between institutional investors and inventory management meaningfully. But structure and size of board of directors did not have any meaningful effects on the relationship between institutional investors and inventory management.

The aim of current research is to investigate the possible effect of capital structure on profit efficiency (comprehensive indicator of financial performance). This paper uses the Jensen and Meckling (1976) theory to assess the effect of financial leverage on agency costs and performance. Therefore، this study examines the effect of nonlinear effect of financial leverage on profit efficiency. The sample consists of 28 automotive and parts manufacturing companies listed on the Tehran Stock Exchange for the period of eight years from 1384 to 1391. Data envelopment analysis (DEA) method is used to calculate the profit efficiency and panel data regression is used to test the effect of financial leverage on profit efficiency. The results indicated that financial leverage has a nonlinear (inverted U-Shaped) impact on profit efficiency. Thus، in this industry، financial leverage growth plays a positive role in performance improvement because a reduction in the free cash flow in hands of manager and consequently، decreases agency costs. On the other hand، an increase of bankruptcy risk increases the agency costs of debt and consequently has a negative effect on performance. The findings also revealed that fixed assets have a negative and significant effect on profit efficiency، but firm size، intangible assets and growth ratio don’t have any effect on profit efficiency.

One of the interesting topics in economic issues is asset markets. According to the theory، if the asset market is efficient in information context and behave rationally، asset prices will reflect the information about the expected events. On the other hand، another important issue that is widely discussed in macroeconomics، is selection of appropriate policies and tools in order to eliminate the imbalances and instability of the economy. The aim of this study is to investigate the effects of government spending and income shocks on asset prices such as housing prices، stock prices، and exchange rate by using structural vector autoregressive model (SVAR) with 5 variables and quarterly data from 1369 to 1390. The results showed that government spending has a significant effect on housing prices، stock prices، and exchange rate، and is the most important variables to explain the volatility of these asset prices. BEKK approach in GARCH Models is used to estimate the dynamic relationship between the variables uncertainty. The estimated covariance between the variables، show the negative relationship between stock prices and government spending، and between exchange rate and government spending، but the positive relationship between housing prices and government spending is estimated.