فصلنامه دانش سرمایه گذاری
پیاپی 15 (پای ی ز 1394)

Interest rate of the securities with fixed-income in Iran which is determined in terms of policy and regulatory package of central bank, typically it is considered as fixed and interest rate of the county. Obviously, the interest rate should be floating and more than inflation rate. However, due to available mechanism for notifying the interest rate, there are not floating interest rate in Iran unlike most world countries and notified interest rate is not fair rate. On the other hand, according to high inflation, lake of flexibility, attractiveness of other parallel markets, redeem volume of increased and handling market securities is forced to high volume from unattractive securities. In this article, modern method for securities handling market is introduced with fixed-income. In this procedure, the securities price supplied to auction and or fair price method, is variable without amplitude and securities transactions into single-price auction during trading session and the handling marketer is obligated to import simultaneously sale and purchase orders. After describing possible and specific conditions model using a corner solutions and considering possible condition strongest and its efficiency is evaluated. With verifying the model efficiency can be expected to occur in the country the finding interest rate and reducing the financing with supplying the securities to the auction method, escrowing the handling market process to the market mechanism, discovering optimum price, increasing the efficiency and attractiveness, interest rate form the securities and reducing handling market.

In this study, relation between trading gain- loss and price logarithm as measure of utility examined by Prospect theory. With Ex post facto study in Field of behavioral finance and using of observational data of price and trading gain/loss, sample firms classified in two group and relationship between price logarithm and trading gain/loss is estimated. Results show that first, positive relation exists between trading gain and price logarithm, while this relation for trading loss is negative. Second, slope coefficient in loss side relative to gain side in terms of absolute value is larger that show investor have high sensitivity to loss relative to gain. In other words, investors are risk averse in gain side and loss averse in loss side. Thus, estimated models show that in accordance with Prospect Theory, when investors are in gain, they have risk aversion bias and when they are in loss, they have loss aversion bias. This result is not rejected by nonlinear estimation. Nonlinear results show slope coefficient decrease by increasing gain and loss.

Since 1980s by appearing behavioral finance literature, logically investment hypothesis and also efficient market ruined. The mentioned literature states that some biases cause on decision making while trading shares. This study investigates the effect of some behavioral elements on security investment. The aforesaid elements are Regret aversion, Disposition effect, Mental accounting, over confidence, Representativeness, Herding behavior, Conservatism and Endowment effect. In order to do the study, a sample of 385 investors in stock market was chosen and data was gathered through a questionnaire. Statistical tests examined the research hypotheses.
Results show that all factors have a significant effect on investors'' decision-making exclude over-confidence. Due to different affection, the elements were rated. Rating indicates that the sequence of them is as follow: 1-Mental accounting, 2-Disposition effect, 3- Conservatism, 4- Herding behavior, 5- Representativeness, 6-Endowment effect, 7- Regret aversion.

In this study, the effective method of asset allocation characterized by risk control, cost reduction and out-performance with respect to the market benchmark has been investigated. In this regard, the optimal asset allocation in the core and satellite portfolio including the degree of risk aversion were studied. The core component of the portfolio represents an index fund selected by the use of a heuristic genetic based algorithm, which assures the level of risk-return realization comparable to the market index. The satellite component is consisted of selected mutual fund investment units and is managed actively in order to beat the market index.
An EGARCH model was used in order to simulate the required data, and a multi goal objective function as maximizing the excess return and minimizing the variance relative to the index was implemented for the modeling of the core-satellite problem.
The results of the analysis implies on the direct relationship between the degree of risk aversion and the weight allocated to the core component. The calculations also indicate the out-performance of the constructed portfolio relative to the market index and its good tracking ability based on criteria such as correlation and root mean squared error using out of sample data.

The credit crisis in recent years has increased the focus on bank credit risk. This paper uses an agent based model (ABM) to investigate the impact of bankers’ credit decision actions on bank credit losses that are induced by lending to corporate clients. In this model, we assume one bank give credit to corporate clients and divide corporate in two sectores: small and medium corporates and large corporates. The results show that credit decision actions have substantial effects on bank credit losses, thus implying that regulators should consider organizational factors as a complement to bank assets when assigning capital requirements to banks. The study also aims to point to a new area of application of ABMs for both researchers and practitioners.

In emerging markets such as Tehran Stock Market, there is a gap between signals of changing the trend and the beginning of the movements which we can make profit by using a well-designed Algorithmic Trading System. Proposing a high-frequency trading system has advantages (taking advantage of intraday stock market volatility) and disadvantages (high amounts of transaction cost due to the high transaction volume) thus we can augment advantages and cotrol the disadvantages by designing the system elaborately. In this research, the “Local Traders” approach for predicting the future trend of stock has been utilized. According to the “Local Traders” approach, there is a local trader (an agent) for each stock which is expert on it. It predicts the future trend of its own stock based on stock’s intraday data and their technical indicators by determining how much it is good to buy, sell or hold. Results show that, the proposed model outperforms the Buy and Hold strategy in all kinds of markets (Normal, Ascending, Descending) even if there is no discount on Transaction Costs.

In this paper, we propose automatic stock trading system which combines technical analysis and adaptive neural fuzzy inference system to predict the stock price trend to increase return of investment. In this trading system, at first the optimal value of technical indicator's parameters is determined by using multi-objective particle swarm optimization and according to these parameters; technical indicators are calculated to predict stock price changes with the help of adaptive neural fuzzy inference system. We have chosen eight different stocks from Tehran stock exchange to test our trading system for two months. A computational experience is carried out in order to analyze the proposed algorithm and the obtained results are compared with usual conventional methods which have been proposed in previous researches. The computational results show our proposed method performs better than other previous methods and obtains superior results.

Stock market is a formal capital market which has an effective role in mobilization of financial and capital assets. Stock market is also a proper center of collecting of saving and cash in private sector to finance in long term investment projects. The development of financial markets, especially the stock market and its impact on corporate financing has dramatic impact on economic growth. Major determinants of financial development, include legal Origin; institutions; openness policy; and political factors. Among these determinants, political factors are important sources that are originated from implemented policies and legal institutional frameworks, which are effective to the development of the financial system. In fact, the dynamic political economy shows that economic institutions and legal traditions are effective to promote economic growth and financial development.
This study, firstly explain the concept of political risk and its theoretical relationship between financial development and political risk, and then analyzes the affect of political risk on stock market development, especially the depth and breadth of the market in selected countries for the period of 1384-1391. The evaluation of the modified model Yarty (2008), factor analysis to combine variables to create depth and breadth of the stock market and stock market development indicators and the dynamic panel generalized method of moments based on (GMM) were analyzed.
The results have declared that reduction of political risk has an effective role on depth and breadth of the stock market. According to the results of this thesis in developed country, political risk had more impact on stock market development indicators in Developed countries rather than developing countries.

Venture capital is an interesting area in banks financial decisions and because of its uncertainty, brings lots of challenges. Despite the increasing tendency for banks in this kind of investments, there is not any certain method to analyze the risk and return of ventures; thus it is neccessary to develop an effective research in this area. Recently, development of the studies about ventures, has facilated conditions for investors and increase the proportion of venture capital in commercial banks portfolio. This paper as a novel study, at first, consider the literature review of financing VC projects and their instruments, and then try to find the usablity of these methods in Iranian commercial banks in a comparative approach.

This study investigates the association of free float and liquidity of the stock. In addition to considering any reasonable investor in making an investment return and risk criteria should also consider liquidity to be able to determine the relationship between liquidity indicators (turnover, value of transactions, number of transactions, number of days of trading and turnover trading stock) Tehran Stock Exchange with a free float of 164 companies were investigated. For this purpose, trimester data were collected from the 1391- 1385 companies. Using the combined data (panel) regression models were estimated. The results showed that all of the free float and liquidity indicators, there is a significant relationship. Given the values ​​of the estimated coefficients, in order of most to least about trading stock turnover, number of days traded, turnover, number of trades, the trades are free float variable.

Risk and return of the firms are most important investing criteria in capital market so investors who have more pay attention to this criteria, are successful. Changing management company's cause different decisions in financial area of firms ,and therefore, it has an effective impact on risk and returns of the firms. In this study, the relationship between a company's management to change the default risk and capital market performance of companies in Tehran Stock Exchange for the period 1385 to 1390 was in total, 618 observation periods was used to measure the performance of three criteria: return on assets, return on equity, economic value added was. Statistical methods used in this study is multiple regression method. The results show that the change in corporate management with respect to default risk but there is a direct relationship between the change in corporate management with the three criteria to evaluate the performance efficiency of assets, return on equity economic value added, to reverse

Tanavar Co. has had problems in making strategic decisions, due to the lack of a systematic mechanism to manage risk events. Hence to facilitate the enterprise risk management (ERM) process, a decision support system which is able to support decision making at all stages of risk management process has been developed. This research introduces a methodology which supports decision making in the whole process of enterprise risk management and in addition applies multiple attribute decision making (MADM) tools such as weighing method based on eigenvalue approach and TOPSIS method, fuzzy inference system and also integer programming. Applying MADM models for using qualitative, quantitative and sometimes contradictory criteria, and also using experiences and opinions of experts, requires a decision support system. Thus for implementation and validation of recommended model, a software has been developed and applied in Tanavar Co. and specifically in Enghelab sport complex.