INVESTMENT KNOWLEDGE
Year:2013 | Volume:2 | Issue:7|Papers Count:13

In this article, investigate between market return & stock return. The finding research show that, time series result, is significant.

Using various sciences in solving problems have been developed significantly in recent years. In 1979 Kahneman and Tversky proposed a new school premises known as behavioral finance. In behavioral finance, by using the combination of psychology and finance, a perspective is presented which is able to explain financial decisions. The purpose of this research is the study of neurofinance literature by using the psychological science. neurofinance is a very young discipline that attempts to relate the brain processes to behavior. In this study by providing the answers for 5 questions in 7 sections, the process of emergence of neurofinance, brain function in decision making, design, methodology and approach, the difference between behavioral and neuro finance, their applications, Criticisms in this area and the results of this study are investigated . The findings showed that human’s brain is similar to a black box. When an event occurs, the brain records every moment and therefore we can prevent mistakes by processing recorded features. By knowing this, decision makers can make optimum decisions.

Corporate managers present financial reports in order to reveal their performance and financial status of corporation and then financial analysts use financial statements as a basis of making investment suggestions. Obviously investors don’t have any role in managing companies directly and therefore they have to make their decisions trusting financial statements. In financial markets, financial analysts have to trust managers, even considering the fact that statements can be incorrect. Consequently, exploring influential factors in financial analysts’ trust to corporate managers seems necessary.As financial behavioral is a kind of newborn field of finance, it’s essential that future researches should be directed towards it and implementation of it should be checked in developing markets like Iran’s. Financial behavioral is presented against classical economic theory which is based on some simplifying hypothesizes.Main findings of this research are: 1. Qualification, honesty, competence, cultural factors and social factors are very influential in financial analysts’ trust to managers. 2. Integrity, benevolence and personal factors, have average influence in financial analysts’ trust to managers. 3. Being faithful to Islam has little influence in financial analysts’ trust to managers.On the basis of findings, it can be said that an organization which has a qualified, honest, competent, well-behaved (cultured) and sociable manager, will be trustable; that it can lead to a good atmosphere and can provide a necessary condition of efficient market.

This study examines the effect of economic and political news on Tehran Stock Exchange during the years 2001 to 2009. In order to investigate the investors’ behaviors, we used the total daily index of stock exchange. The investors’ reaction was evaluated from two perspectives of “Overreaction Hypothesis” and “Uncertain Information Hypothesis”. Results of this study indicate the existence of overreaction in investor’s behaviors in the time of announcing good and bad news in stock market. Also the results shows that the reaction of Tehran stock exchange’s investors to good news is faster than bad news, but changing stock price slope in good news is faster than bad news. Additionally, research results show that investment risk in days after publishing news (even good or bad) has more than normal days.

This paper is investigated the credit rating of manufacturing firms in Tehran Stock Exchange. In this regard, have been extracted financial ratios of public stock companies during the three years from the financial statements. This financial ratios indicates the ability to pay principal and interest of loan. Initially, 50 companies were selected and ranked by the TOPSIS method. Financial ratios are as a criterion and weight of the each criterion are determined by using Shannon entropy method. Then the ranking, companies are classified into four categories. The artificial neural network is trained to classify and after training the neural network are tested. Statistical results show robust classification of neural network. Then all the companies included in this study are classified by neural network.

Financial and monetary institutions and particularly the commercial banks, is important for direction and significant influence on economic and social development of countries. Thus it seems necessary and logical the model provides for feedback to improve performance in various branches of the organization and access tools to meet the needs of managers. In order to above requirements, this research intends to use the appropriate model for evaluating the performance of banks in the Tehran Stock Exchange, in order to identify the efficient and inefficient banks in exchange, and provide the competitors' strategies appropriate for to improve performance the inefficient banks and enhance more the performance efficient banks. In this study the experience of using the combination model of data envelopment analysis and fuzzy multi-attribute decision-making for assessing the performance of Bank adopted in the Tehran Stock Exchange, effort to using the technique of hierarchical fuzzy process to identify the final input and output for of The relative performance of bank adopted in the Tehran stock exchange, and then collect the relevant information, can be measured the efficiency of these units using data envelopment analysis models. While each of these cases, studiedthe sensitivity analysis of input and output and complete ranking of banks for each of the years using cross-efficiency evaluation method.

Aim of this research is the survey of role, amount and sort of relation between variables such as ratio of book value to market value, different returns and also study of difference between value stocks and growth stocks at Tehran stock exchange.Time period is 6 years, since 2007 to 2012, and 88 publicly traded companies were chosen.To test hypotheses, static panel data and generalized least squree were chosen. Results in minor group that, the relation between B/M ratio and cash return is negative, meanwhile the relation between aforementioned ratio and total return and also capital return are positive. In major group results show that, there is higher return for growth stock retun in comparison to value stock return. It also shows that the relations are similar to minor group.

One of the important issues in the financial markets topic is the relation between the prices of valuable commodities like oil and gold and the various exchange rates. Wavelets are mathematical functions for analyzing the time series into their components in various time scales. In this paper firstly the time series of oil price, various exchange rate & gold price are analysis to their components in various time scales by wavelet transform and then the correlation between these components are studied. The results showed that the correlation between these variants are different in the various time scales and also is different from the direct correlation of them. In the case that the direct correlation between the variants is not meaningful we can get valuable correlation in various time scales.

Nowadays artificial neural networks have found a special position among these methods. This study seeks to find a better method of building and training artificial neural networks which leads to more accurate predictions of bankruptcy. Meanwhile, three neural networks of radial basis function type were built and trained separately by Altman model (1983), Zmijewski model (1984) and combinatory models’ variables. After evaluating the ability of these three models of bankruptcy prediction, their accuracy has been compared. Generally, this study is based on these hypotheses: First, artificial neural network models can predict bankruptcy using Altman, Zmijewski, and combinatory variables. Second, Type I and Type II error rates are equal in the aforementioned artificial neural network models. Time span of 2004 to 2012 (eight years) has been used to select samples from the listed companies in Tehran Stock Exchange. Results show that all three models have the ability of predicting bankruptcy and the model trained with Altman Model’s variables is more accurate than the other two models in this regard.

Conflicts of interests may arise from managers’ lack of incentive for shareholders’ wealth maximization. For solving this problem and reducing agency costs motivational strategies should be used for managers. One of these strategies is management compensation plans and another strategy is ownership of management in company. This paper investigates the relation between free cash flows and Tobin’s Q ratio with Management compensation plans in companies listed in Tehran Stock Exchange.The purpose of this research is to answer this question that whether management compensation plans and their ownership in company leads to improvement of a company’s performance?Answering these questions helps companies and shareholders to find that whether these plans can increase their value and wealth or not.In this research free cash flows and Tobin’s Q ratio criteria are used for performance evaluation. For this purpose data of 112 companies listed in Tehran Stock Exchange from 2006 to 2011 was studied. Hypothesis testing analysis was conducted by the use of statistical methods of Pearson’s correlation analysis, regression and variance analysis. The findings show that there is a positive and significant relation between management compensation and both free cash flows and Tobin’s Q ratio. Therefore increase in management compensation leads to improvement of a company’s performance, but percentage of board of directors’share has no significant relation with none of Free cash flow and Tobin’s Q ratio.

In this Research New & Past Gird Models for portfolio select based on triener & sharp index do comparative.The research findings show that, sharp index better than triener index for growth portfolio.

Gas-oil is one of the most important energy carriers and the changes in its prices could have significant effects in economic decisions. The price of this carrier should not be more than 90 percent of F.O.B price of Persian Gulf, legislated in subsidizes regulation law in Iran. Time series models have been used to forecast various phenomena in many fields. In this paper we fit time series models to forecast the weekly gas-oil prices using ARIMA and ARFIMA models and make predictions of each category. Data used in this paperstarted with the first week of the year 2009 until the first week of 2012 for fitting the model and the second week of 2012 until 13th week of 2012 for predicting the values, are extracted from the OPEC website. Our results indicate that the ARFIMA (0.0.-19, 1) model appear to be the better model than ARIMA (1, 1, 0) and the error criterions RMSE, MSE and MAPE for the forecasted amounts is given after the predictions, respectively.