فصلنامه بورس اوراق بهادار
پیاپی 14 (تابستان 1390)

This paper empirically investigates and compares the capital asset pricing model (CAPM) and arbitrage pricing theory (APT) using 132 monthly market returns of TSE based on TSE main index (TEDPIX) and returns of 30 stocks listed on Tehran Stock Exchange (TSE) for the period of 2008-1997. Our results provide evidences in support of CAPM, inconsistent with previous papers of Bakhshandeh (1992), Hamadani, and Pirsalehi (1995), Shafie zadeh (1997), Hanifi (1998), Zariffard-Ghaemi (2003). However, some other Iranian researches Presents more than one economic factor effective on explanation of stock return consistent with APT but we did not experienced several factors effective on this issue.

Bonds are among the most important financial instruments in money and capital markets of the capitalist societies. They are used to finance corporate, municipals and ministries and also execute monetary policies through open market operations by the central banks. One of the obstacles in issuing bonds in Islamic countries is that they are Riba-based instruments. In accordance with Islamic school, Islamic researchers have tried to replace the bonds with new instruments such as, Musharekah sukuk. Surveying the performance of Musharekah sukuk in Iran shows that although the main goal of the researchers have been achieved to some extent, expanding more of such sukuk needs a comprehensive pathology. The present article is based on survey and AHP methodology and uses library based resources.

This paper using a Multivariate Generalized Autoregressive Conditional Hetroscedasticity (MGARCH) model has examined the nature of interaction between Iran, USA, Turkey and Malaysia Stock Markets. The results based on weekly data spanning from October 1997 to March 2010 indicate there are no significant effects between stock market in Iran and the other stock markets. Given a low degree of common time-varying co-volatility among these four countries, investors will be highly likely to benefit reduction of risk if they diversify their financial portfolio with stocks from these four countries.

Sentiment measurement is the core of attention in some researches in behavioral finance. Based on psychological and biological evidences, moon cycles affect human mood, behaviors, and then their judgment and decision making. Many researchers in the field of behavioral finance tend to investigate if there is a relationship between lunar phases and stock market returns. The main objection of this paper is to test lunar effect on Tehran Stock Exchange (TSE) market return. In this research, we use linear regression (OLS) and comparison of average return in new moon and full moon cycles. We have come out with the conclusion that lunar does not affect daily TSE market return. For acquiring further evidence, daily average market return in periods of 5, 7 and 15 days around the full and the new moon are compared. But, no significant difference is approved.

Although there are many researches about the impacts of trading suspension, its positive and negative effects remain unclear. Supporters of trading suspension claim that this mechanism will result in having more time for data assessment. Thus, no specific group can abuse the situation or utilize it unfairly just for their own benefits. They also claim that trading suspension can lead to a rise in information contents of dividends value and fall in uncertainty. These items can protect the investors from unreasonable volatility of stock value which results in better price discovery. On the other hand, the critics of trading suspension believe that this issue can delay the process of price discovery and impose extra cost on those investors who could not trade the mentioned dividend. This can also reduce the motivation of investors. In this research, like the investigations in other countries, the negative and positive effects of trading suspension on Tehran Stock Exchange have been investigated. Indeed, the purpose of this research is to understand the effects of trading suspension on trading volume and volatility of return and abnormal return. Sample population includes all companies in TSE. The data were collected from 41 companies, selected by Cochrane sampling method, between 1384 and 1388 (2005-2009) and analyzed using SPSS software. The results indicate that trading suspension has resulted in increase of trading volume and return volatility in abnormal period (near the trading suspension). Decrease in abnormal return after the suspension has resulted in price discovery.

This research investigates multifractality in the Tehran Stock-Exchange index TEPIX. By analyzing the TSE price index daily returns using MF-DFA method, it is found that there are two different types of sources for multifractality in time series, namely, fat-tailed probability distributions and log rang correlations. In the Tehran Stock Exchange, prices have a correlation and memory; therefore expert investors can achieve a more return.

This study proposes a portfolio optimization scheme for Enhanced index fund management. Enhanced index fund management has two basic goals in relation to passive and active management. Enhanced index fund aims to earn a higher return than the index while minimizing the risk of deviating from the index. This paper demonstrates how a genetic algorithm can be used to solve the enhanced index fund construction problem with constraints on the cardinality and with upper and lower limits on the included asset's weights. The sample period used is from May 1999 to May 2010 in the Tehran Stock Exchange (TSE). The experimental results have been compared with TEDPIX. The result of these comparisons shows that average return of enhanced index fund is statistically significant greater than return of TEDPIX.

Company decisions are made in the general meetings, but managing of company depends on director's decisions. Therefore, identification of general meetings depends on identification of every organs and institutions that make decisions. So, the position of general meetings will be distinct in the system of company decision making. In this study we have endeavored to survey relations of general meetings and board of directors as well as identification of general meetings law in Iran and Great Britain. Finally, it seems we need to distinguish decision making by the managing group with an emphasis on the supervisory role of general meetings. In this situation, it is required to authorize the control and management of the company to board of directors unless a law or articles of association limit the board of directors and we can accept the influence of general meetings on board of directors only in the framework of extraordinary decisions.

The subject of dividend policy is one of the most important issues in recent decades. Stock Dividend is considered as an effective factor for creating investment opportunities in investment companies. The more the dividend payout is, the more the external financing sources need for implementing investment projects. This factor can affect greatly on companies stock price in future. On the other hand, most company shareholders are interested to have cash dividend. Hence, the mangers always must establish equilibrium among the shareholder's different interests; because the investment desirable chances must not be lost and also approved cash dividend must be paid to shareholders. The present paper verified the relationship among free cash flow, profitability position and amount of stock dividend in Tehran Stocks Exchange during the period 1376-1387 (1997-2008). The data is collected by Rahavard Novin and Tadbirpardaz and are analyzed by using Fixed Effect panel data and Eviews 4. The results showed that there is a significant relationship between profitability position and stock dividend, but there is no significant relationship between free cash flow and the amount of stock dividend in Tehran Stock Exchange.

Analyzing XBRL projects around the world indicates that successful implementation of XBRL depends on some major criteria's such as reporting standards, organization and system architectures and custom requirements. However, the process of implementing XBRL is complicated and risky. These challenges lead to necessity of choosing a right scenario for implementing XBRL. In this study, by reviewing the most known XBRL implementation approaches such as "filling" and "web service" and also focusing on electronic data gathering infrastructures in Iran capital market, four scenarios have been shaped. Based on Analytical Hierarchy Process (AHP) technique these scenarios were ranked. Findings show that, for implementing XBRL in Iran capital market using the current electronic platform in conjunction with web service approach should be considered.

The aim of Corporate Social Responsibility is achieving sustainable economic development via improving the quality of the life of workers, their families and society in general. So, it seems that implementing CSR by companies has an important role in poverty alleviation and economic growth. This research, has investigated Corporate Social Responsibility and poverty alleviation and the role of incentive in implementing social performance indicators in relation with poverty alleviation. In this case, several social performance indicators were introduced and were investigated. The results of One-Sample T-test, Independent-Samples, T-test and F-test showed that companies prefer to implement these social responsibilities, also there was no significant difference in perception within gender, age, graduates, job category, years of engagement and income. However, providing incentives like tax allowances, cheap and easy financing and balancing the regulations can have an important role in implementing the social responsibilities that alleviate poverty.

The main objective of this study is to find out whether an Artificial Neural Network (ANN) will be useful to predict stock market price, which is highly non-linear and uncertain. Specifically, this study will focus on forecasting TSE Price Index (TEPIX) as the most significant index of Iran Stock Market. Many data have been used as inputs to the network. These data are observations of 2000 days for a period of 9 years from 02/29/2000 to 12/03/2008. Data are divided into two categories; fundamental and technical data. The fundamental data used here are principal economic values like Dollar/Rials Exchange Rate, Gold price and Oil price. The technical data used are technical indices such as Moving Average (MA), Moving Average Convergence/Divergence (MACD), Relative Strength Index (RSI), Rate of Change (ROC), Momentum (MOM) and daily trading volume of stocks. The selected data are divided into training set and test set, in order to be entered into the network and the remaining 10% was used as the testing set. Training set consists 90% of data. This classification uses 3 different approaches to assemble the training and test data, including random, deterministic and consecutive selection. Here, a feed-forward neural network (FFNN) with the most suitable algorithm for finance (i.e. Back Propagation algorithm) was used for the prediction. Predictions were made for the next day of TEPIX with a 3-4-1 topology and 1500 epochs. The performance of the ANN was evaluated by MSE. Finally, the results showed that ANN could properly recognize the relationships between fundamental and technical data and TEPIX, so that the prediction of the next day was quite possible.