فصلنامه دانش مالی تحلیل اوراق بهادار
سال هشتم شماره 26 (تابستان 1394)

Price volatility on gold and oil market is the top news all the time. Global economy is affected by those markets volatility. Because of the domestic investor tendency in gold market and feasibility of investing on oil by Energy Exchange in Iran, in this paper we focus on the volatility of gold and oil return. The implemented method is one-day ahead out of sample forecast by the conditional value at risk. The goal of this paper is to answer which of the models; GARCH, ECHARCH, and TARCH is best at forecasting the CVaR for gold and oil return. We estimate the value by assuming normal and t-student distribution. The results show that the TGARH(1,1) model specifications are good option for forecasting the CVaR in oil market by t-student distribution.

In this study, we estimated the parameters using the State Space model described in ARIMA form. We’ve also used the Monte Carlo Method for simulating the process in 10000 reputations. Then the estimated parameters and the Monte Carlo simulation method are used to forecast TEPIX index, including 739 observations as an in-sample data from 21th of January 2011 to 19th February 2014 and 59 observations from 20th February 2014 to 21th May 2014 as an out of sample data. Furthermore, For more investigation we’ve considered different horizons of forecasting, short-term (equal to 1 week), mid-term (equal to 1 month) and long term (equal to 3 month). The results showed that Tehran stock market data has enough efficiency to forecast them, and showed that the State Space in Form ARIMA model and the Monte Carlo simulation method can be used as a predictive algorithm for TEPIX index and other indices with similar nature.

Deciding about portfolio selection and composition are the main challenge of investment institutions. The nature of analysis and effective criteria in industry and company are different. They should rank the industry and companies options with regard to multiple and conflict criteria that they have different weights and priorities. This article seeks to provide two-stage approach for stock selection and portfolio composition. We enriched promethee (compensatory MCDM method) by weight of criteria. Then we used it in intended approach. The expert opinions and objective data used to criteria ranking. An ANP was used to determining weight of criteria that merge in promethee method. After designing we tried to validate our approach with real data. The results show we have 7% (simple mode) and 11% (enriched mode) return more than actual performance. Using of Porter five forces analysis for indentifying and verify industry criteria, to include some indices from corporate governance and technical analysis, weighting the criteria and integrate them in the promethee are our research novelty.

This paper examines the effects of monetary policy shocks on stock price index of Tehran Stock Exchange by using time series data of Iran over the period 1991-2010. In this regards, first we divided the money shocks into foreseen and unforeseen and the positive and negative monetary policy using hodrik-prescott filter, then regressed them on the stocks exchange index. The results showed asymmetric effects of money shocks on stock price index, so that the foreseen and unforeseen impulse of money affect it differently; the fluctuation of the stock price index arising from unforeseen impulse was higher than foreseen impulse. Also, result showed that the negative impulse on money (money decreasing) was affected the stock price index more than positive impulse.

In recent years, dividend policy, as a factor of influencing decision investment, draw lots of attention in financial literature. Many economic decisions are made based on information, which is taken from the accounting information systems. Due to the quality of information provided to users is necessary and increasing quality of data can be more efficient investment copmanneis and to maintain and develop their resousces. The aim of this study is the investigation effect of financial reporting quality on impact of dividend on investment decisions. Then, the impact of financial reporting quality on this relationship has been investigated. Also for evaluating the financial reporting quality, the working capital accruals quality model was used. Target sample includes 109 of listed companies in Tehran Stock Exchange(TSE) during 1385-1391.To analyze the data and hypothesis testing a multiple regression model based on compound data was used. The results of the study show that dividend have negative and significant effect on investment decisions. Also financial reporting quality mitigates the impact of dividend on investment decisions.

The aim of this thesis is identifying and modeling the risks of the power plant BOT projects. Main identified risks in this study are project financing risk(equity ratio risk) and the risk of revenue of project. In order to model the risks, we used the Martingale Variance Model (MVM) for the revenue risk and the Triangular distribution function for the equity ratio risk. We applicated the Monte Carlo simulations method for obtaining the probability distribution function and critical values of the decision index (Net Present Value, Internal Rate of Return, Debt Service Coverage Ratio). The one of thermal power plant projects data prepared by MAPNA, has been implemented in this study. The results of the simulation indicate that the risk of negative NPV of project is 13.41 percent and the risk of DSCR lower than 1.2 is 8.65 percent. Therefore, the sponsors suffering more risks than lenders in the studied project.

As previous researches have shown, investors in stock exchange market are affected by various factors. Therefore this research is aimed to identify and rank these influential factors. For this purpose a general model including macro (political and economical) and micro (enterprise information, market information and psychological variables) factors is introduced. Questionnaire was formed by a synthesis of existing constructs in relevant literature. Reliability tests and statistical analyses were performed to confirm scale validity and reliability and to answer the research questions. Structural equation model was applied for this purpose. Statistical analyses revealed that, except for scientific analysis (technical and fundamental) all the factors are positively and significantly related to investment motives. Also Friedman test showed that financial information, political factors and trade information are most influential factors in investor’s motive. It worth to mention that this general model has been used for the first time and previous studies have been considered a part of these variables.

Nowadays financial instruments play an important role in human lifestyle. By surveying the evidence on financial literacy levels around the world, results show that improving financial literacy level of individuals will effect on the financial deals as well as social welfare. In order to introduce, measure and represente new methods of improving financial literacy, comprehensive national initiatives and programs funded by the World Bank and other donors have sprung up around the world. In this survey we measured financial literacy level of Tehran households and its determinant factors by the use of questioner. 410 households were randomly selected to participate in the survey. The results indicate that financial literacy of selected individuals is not desirable although interested on using financial advice and having family financial advisor. Other factors (such as age, generation, education level, revenue level, wealth accumulation level, education field and location), surveyed as a separate assumption to the financial literacy of Tehran households. Their relation with financial literacy were confirmed and learning programs and introducing by mass Medias are our offers for the first step.