ECONOMIC RESEARCH REVIEW
Year:2010 | Volume:10 | Issue:7 (SUPPLEMENT)|Papers Count:9

One of the main features of international economic interaction among countries is Foreign Direct Investment (FDI). During the past few decades various researches have been done to shed light on demand and supply side of FDI. One of the main topics among these researches is determinants factors of Inward FDI. In this article we are to analyze these factors once more but in a cross country study by emphasizing on economic freedom. To do this 30 countries (including Iran) have been selected and divided in to three categories with respect to their income level. Our main model was run not only for all countries but for all the three categories through GLS technique for the period 1998-2004. The results imply that Openness and the situation of countries with respect to economic freedom have considerable effects on FDI inflow in all countries which can have good contribution in policy making in Iran. Also the results show that explanatory variables such as Government Subsidies, Tax system, Debt structure and... have significant impacts on FDI inflow up to income categories of countries.

This research tries to find out an answer to this question, whether investors can use technical analysis method in Iran capital market? For this purpose, simple moving average and relative strength index techniques have been used. This investigation has been done through testing trading rules of simple moving average and relative strength index on stock exchange prices.The results of this research show that simple moving average and relative strength index techniques have predictive capability and can identify price patterns to perform profitable trade. Usefulness of simple moving average and relative strength index rules would be useful for the next 3-7 days in future.

Even though now a days most of the financial markets are moving toward efficiency, but the be life in market predication has not reduced. The stock market as a complex and adaptive system is more consistent with what is known in other sciences, such as physics and biology, and appears to be more descriptive of actual markets activity. This theory is able to conclude some facts that predict the direction of market in the world. The best tools are the ones that could work, think, and decide like smart humans in this complex market environment. Artificial intelligent system is one of these systems that is designed and modeled according to human brain which is able to recognize, learn, decide, and predict very complex patterns.Stock markets, with all the internal and external events, are still predictable were formed in this research. With collection of all the monthly reports and resources from 2001 to 2005 which include: economical, financial, political variables and market behaviour, companies performance predication, substitution markets and monthly average index movement.All of which we could have put to neural networks (RBF) and neural fuzzy networks (ANFIS) to test. After the training of 550 inputs and then test with 50 inputs, the result of which showed that with the help (ANFIS) we could predict 98% of Iranian stock market.

One of the most important banks’ activities is to allocate the sources and the most important risk of this activity is lack of commitments from the ones who get the banking facilities. Thus, banks try to decrease this risk.That’s why the progressed banks are interested in investment project’s success along with their goals. Therefore, to identify all the factors affecting this success like the project presenter’s character, the appeal of the recommended project and the presenter’s organization can help the banks reaching their both goals.The literature review in this essay shows a complete conceptual framework of ranking the banks’ customers and to state the present situation in domestic banks and international ranking institutes which contains all the factors related to the project presenter, the presenter organization and the attraction of the project. To test this conceptual model, the view points of some of the experts have been asked by some questioners. Therefore in the final research model some factors like project presenter’s entrepreneurial character, his management skills, and themanagement’s characters of presenter’s organization are to be noticed as it was not considered in the traditional ranking system till now. This integrative model could be the base of the banking facility’s system.

If the crude oil future market is not efficient in the Fama sense, then profitable trading opportunities may exist. This paper uses a GMDH neural network model with moving average crossover inputs to predict price in the crude oil future market. The predictions of price are used to construct buying and selling signals for traders. Compared to those of benchmark models, cumulative returns, year-to-year returns, returns over a market cycle, and Sharpe ratios all favor the GMDH model by a large factor. The significant profitability of the GMDH model casts doubt on the efficiency of the oil future market.

In this paper, conditional model of downside capital asset pricing and conditional model of capital asset pricing in periods from 2001 to 2008 in Tehran stock exchange are compared. At first, the coefficients of b and negative b D, market rate of return of variables, risk premium in two models are calculated and next, the expected rate of return is estimated.Then rate of return of independent variable and expected rate of return of dependent variable are separated in two models in accordance to market risk premium positive or negative. By doing so, the initial data of main and secondary hypothesis are defined. Then by using statistical software and average difference regression test and least significant difference research hypothesis are confirmed or rejected. Results of this research show when the market risk premium is positive, the conditional model of D-CAPM is more efficient than the conditional model of CAPM and when the market risk premium is negative, the conditional model of D-CAPM is more efficient than conditional model of CAPM too. Also the conditional model of D-CAPM shows the relation between risk and return better than conditional model of CAPM and portfolio selected by this model is more efficient than conditional model of CAPM.

In this study, considering the high level of inflation in Iran, we develop an inflation-adjusted economic value added (EVA) metric. We investigate this claim that adjusted economic value added is superior to nominal economic value added for firm performance evaluation on the basis of stock return and price. For the investigation, we test two hypotheses and for testing each hypothesis two competing regression models are developed. For the purpose of estimating the research models, a sample of companies (374 years-firm) listed in Tehran Stock Exchange (TSE) for the time period of 2001-2006 is used.The results do not show that adjusted economic value added is superior to nominal economic value added for evaluating firm performance on the basis of stock return. Except for Cement, Metals and Metal products, and Pharmaceutical and Chemical industrial groups we found no evidence that adjusted EVA is superior to nominal EVA for firm performance evaluation on the basis of stock price. The over all results are ambiguous and do not provide strong evidence that show superiority of the adjusted EVA to the nominal EVA for evaluating firm performance.

In this Paper, we use Social Accounting Matrix (SAM) to analyze the socio- economic aspects within two kinds of economic policies. The former is visualized as a resource direction from production activities to growth and distribution, and the latter starts from current transfers of Government to households. The potential socio-economic impacts of the two economic policies are measured in terms of growth and distribution multipliers for the economies of Iran, Malaysia, Indonesia, India, China and Russia based on the following question: “With respects to the potential implementation of the two kinds of economic policies, economic structure of which countries are more flexible and what prospect can one visualize for the Iranian economy? ”. The overall results reveal that as compared to the other countries, the socio-economic impact of the former economic policy, gives a much better picture of growth and distribution than the latter.

The aim of this study is to investigate the efficiency of Cement Producing Firms Accepted on Tehran Stock Exchange. The survey population includes 23 firms using Tehran stock exchange data. Data envelopment analysis method (DEA) is one of the useful methods for this subject. This method is on the basis of linear programming. DEA requires some information to determine the efficiency or inefficiency of Decision Making Units (DMU). In this paper, inputs and outputs of DEA are determined through selecting the most important indexes. Inputs include: employees, materials, machines and equipment and energy. Outputs include: net sells, increasing (decreasing) finished products, increasing (decreasing) products in process, and the profits made by investments. On the basis of existing data the efficiency of each firm was calculated using DEAP2 software. At last, the most efficient firms were chosen introduced as patterns. Through comparison inefficient firms could try to come closer to efficient co. and reach to the efficient and required level.