فصلنامه دانش سرمایه گذاری
پیاپی 14 (تابستان 1394)

This research offers proper models to calculate the rate of return and spillover of research & development in 7 selected industry in Iran including: chemical industry¡ petroleum products¡ basic metals¡ computers and electronics¡ pharmaceuticals¡ automotive¡ cement¡ through developing of Cobb Douglas function based on data derived from 1999 to 2006.
The results indicate that in these industries¡ R & D intensity as an explanatory variable has a high correlation with the growth of Total Factor Productivity (TFP).
Total estimated rate of return on R & D and its spillovers are about 13-23% respectively. These rates are much lower than developed countries.
Findings also indicate that R & D spillover''s effect on productivity growth in these industries are much lower than in developed economies. Therefore¡ to accelerate the growth of the economy in addition to increase the R & D expenditures¡ the overextension of effects of the R & D spillover in domestic industries are so important and should seriously follow in development programs of IR.IRAN.

Determination and prediction of housing price in urban areas plays a significant role for governments, public and private enterprises, and financial evaluators. An accurate estimation of the housing price can be employed for future planning and decision making in many urban and regional policies. However, the growth of the housing sector has a profound impact on gross national product, resulting in a significant increase in employment. On the other hand, an increase in loan for purchasing house leads to a rise in liquidity and inflation rate. This means that the gap between the income and housing price is increased. Therefore, it is necessary to develop new models for making decisions in order to prevent the increase in the inflation rate and housing price. According to the key importance of housing price, a number of models have been developed to formulate the price behavior with regard to its effective components. In this study, a novel model based on the ARIMA method for forecasting and formulating the housing price has been developed. The results show that the model proposed has a high potential (with a determination coefficient of 99.7%) to foresee the housing prices in the city of Tehran.

The emergence of the knowledge economy, cause of the increasing importance of intellectual capital as an intangible asset and source of competitive advantage. purpose of this study was firstly to investigate the relationship between intellectual capital with performance and value superior of companies listed in 1390  Using Value Added Intellectual Coefficient Ante Pulic (2000) and the multiple regression model is. In the second stage, these companies using principal component analysis (PCA) based on intellectual capital indicators are ranked and finally using Spearman's rank correlation coefficient , Their ranking of position intellectual capital with the ranking they based stock indexes are compared . The software used for data analysis are Eviews7 is. The results of the research indicates that there is a significant correlation between the intellectual capital with the worth of the company's financial performance and market superior stocks, , but there is not a significant correlation between the ranking of those companies based on index and ranking them based on intellectual capital index. as well as the results of the research show that among the constituent elements of intellectual capital, the capital employed efficiency has created the most influence is the superior companies EPS and human capital efficiency has not a significant impact on the financial performance and market value of the superior companies.

Regarding to the requirement of making decisions related to buy or invest in new economic institutions along with correct and detailed information about their status and economic development circumstances, the estimated potential investment identifies its role and implication ever better. Recognizing the effectiveness created by the financing strategy on organizational values, alongside the factors playing a key role in the process of evaluating the financial structure are urgent elements lead to the success of such an scheme. This research aims to draw a series of mathematical models which could be used as instruments for defining the quantification of the impacts generated by the financial structure on the companies’ value based on a sample consisted of 75 companies quoted in Tehran Stock Exchange regarding to the weight of their activities in gaining Gross Domestic Product (GDP) in 1391(solar year). Simultaneously, this study tries to determine the internal factors that are specific to the company and characterize the feature of the financial structure and intensity of their performance upon financial leverage as well. For getting results, methods of data analysis were used such as: ratio technique, linear regression analysis or alternative independent variables, ANCOVA type. Data processing was accomplished using SPSS21 and AMOS20 statistical software. The results represent that there is a positive relation between the ratio of financial self-independence and dividend ratio of the company value in one hand, and negative relationship between debt ratios and value of the firm in the other hand. Also, increased ratio of financial self-independence and the cash ratio decrease financial leverage, while, increased return of assets and the ratio of intangible fixed assets will increase financial one.

Financial scholars have made valuable efforts to measure risk premium. Recently, Chen et al (2010) proposed a three factor model based on market factor, investment factor, and profitability factor for explaining stock return and called it q-theory model. Prior researches have shown that this model reduces the magnitude of the abnormal returns of a wide range of anomalies. This research examines the performance of new model in explaining the risk premium of the individual stock and portfolio of stock, and compares it with the performance of CAPM and three factor model of Fama and French in stock exchange market. Sample under investigation consist of 72 listed companies for the period of 1386-1391. The results show that risk premium of stocks has a significant relationship with the sensitivity of its returns to investment and profitability factors. Furthermore, q-theory model significantly excel CAPM in explaining risk premium of firm size, book to market value and momentum portfolios. But it significantly excels three factor model of Fama and French just in explaining the risk premium of momentum portfolios.

During the last decade crucial part of the analyzing the time series has devoted to the long memory. Existence of long memory in output of possession has significant application for investing in efficiency of market, Pricing the differential paper, and selecting the possessions basket. In our research the effect of long memory dependence structure between the dollar exchange rate and oil products in the Tehran stock exchange index. First the existence of long memory ARFIMA test review and continue to understand the impact of long memory on the dependence structure of two types, raw data and filtered data (Dollar exchange rate variability data and index Petroleum for the period from 2009-2013) have been used. The result showed that the raw data has a long memory, than the tail dependent data are filtered.

Overreaction and underreaction phenomena in financial markets reflect it’s inefficiently. Different methods are suggested for evaluation of overreaction and under reaction in researches. One of these methods is measurement of the securities price adjustment speed. Speed of price adjustment securities is time duration that information absorbed in stock prices and reach stock price to their intrinsic values. At this article, is classified several researches to three approaches and described different models and then presented their results. Also the determinants for delayed Stock price adjustment is described and finally is explored Iran capital market specifications and propose some practical suggestions for increasing the stocks adjustment speed improving capital market efficiently.

Expected return on equity is an important variable in the analysis of financial firms. Accurate measurement of this variable and its determinants is one of the most important issues in financial research. Due to inefficient estimates of the expected return on realized returns, accounting and financial studies have suggested an alternative approach to estimating expected returns. This approach implied cost of capital (ICC) called on the firm's internal rate of return that the firm's stock price equals the present value of future cash flows expected return. The main objective of this paper is to investigate the determinants of expected returns estimated based on implied cost of capital for listed companies in Tehran Stock Exchange is 89. The determinants of expected returns in previous research, several factors as independent variables and controls included liquidity, long-term return on investment, growth potential, the level of stock prices, value companies, financial leverage, firm size and systematic risk in was used. Multivariate statistical methods to test the hypotheses were used. The results indicate that the liquidity, growth potential, the level of stock prices, firm size and firm value estimated in accordance with the expected returns implied cost of capital models, positive significant relationship exists. Also, a significant negative relationship between long-term reversal of capital, financial leverage and systemic risk with expected return implied cost of capital estimates are based on the reverse.

Fluctuations in crude oil prices in addition to affect the economy of the exporting countries, is one of the sources of disruption in oil-dependent economy. Always predict the price and volatility has been of the challenges facing traders in oil markets and price forecast is raised as an imperative and functional however, should be noted forecasts that will take place in more accurate and less error than the observed actual results. In order to predict the weekly price of Brent crude oil as an oil indicator given the difficulty of accurately identifying linear and nonlinear models in economic and financial time series from combining Autoregressive Integrated Moving Average models (ARIMA) by the assumption that the time series have a linear pattern and support vector machine (SVM) which has great potential in modeling nonlinear model is used to enhance the accuracy of prediction. Given two paired comparison performance criteria of root mean square error test (RMSE) and the mean absolute magnitude percentage error (MDAPE) which are resulting from the predicted values ​​and actual values ​​for each model, this indicates that in most cases the hybrid model provide smaller errors in predicting the future price of crude oil as compared to the individual applications of autoregressive integrated moving average models and the support vector machine.

In the following research, investors’ overreaction to accruals is investigated in Tehran Stock Exchange through the years of 1384 to 1390. In order to analyze investors’ overreaction, we use the relation between current year accruals and the successive year abnormal returns. In measurement of accruals, Sloan model for working capital have been used. Abnormal return is calculated by the difference between actual return of each year and average of two past years return. Results of this study show that in Tehran stock exchange, investors overreact to accrulas and this betoken as accruals anomaly. Accruals anomaly is categorized in market inefficiency studies, because it shows the ability of gaining abnormal return if someone gobble up information.