نشریه چشم انداز مدیریت مالی
پیاپی 26 (تابستان 1398)

The Trade-off theory states that firms have a target (or an optimal) capital structure that maximizes the firm’s value and any deviation can decrease the firm’s value. Following the existing literature, this paper selects the capital structure determinants and using them calculates the deviation of firms’ actual capital structure from their target level, and finanlly investigates the effect of deviation from target capital structure on firms’ value. To this end, this papes uses data from 148 firms listed in Tehran Stock Exchange during 2007-2017 and also applies panel data approach and the approach to control the industry and year effects. The results indicate that an increase in deviation from the target capital structure decreases the firm’s value. The results of complementary analyses in over and under levered firms and also, the results of complementary analyses using an alternative set of capital structure determinant to calculate the capital structure deviation are consistent with the research primary results. The research results are consistent with the notions presented in Trade-off theory

One of the economic development challenges in recent years is financing problems. In the present circumstance, where banks and financing institutions face many problems in financing businesses and projects, investigating the stock market development factors seems to be necessary. Present research aims at simulating scenarios in the context of factors affecting stock market development in the comparison with banking system. The system dynamics approach has been used in order to develop a dynamic model to simulate the effect of GDP growth rate and interest rate on market capitalization (quantitative scenarios), and also investigate the effect of market efficiency, investing culture and knowledge, and market manipulation (structural scenarios). Using Vensim DSS to simulate the scenarios, the validity of the model has been tested under systemic and statistical tests. The results show that increasing GDP growth rate, increase the market capitalization over research time horizon, while increasing interest rate results in the decrease of stock market capitalization. +3% and -3% change in GDP growth rate results in +13.6% and -12.2% change in market capitalization. +10% and -10% change in interest rate results in -27% and +44% in market capitalization. Changing the endogenous variables by 10% in the demanded way will 80% increase the market capitalization in the comparison with base run simulation values. The results of sensitivity analysis shows that market capitalization is more sensitive to changes of endogenous variables than macroeconomic variables.

 The purpose of this study is to investigate the Logical Behavior of the Tehran stock exchange Based on the simultaneous failure of increasing and decreasing Long-term and short-term trends of performance criteria (including earnings per share, operating profit per share, operating cash flows of each share and Net growth of assets of per share adjusted by inflation( and Corporate Dividend. for this purpose, According to different financial theories, Six hypotheses are developed and data on 301 companies listed in Tehran Stock Exchange for the period between the years 1993 to 2017 are analyzed. The research method using Panel data method with fixed effects approach and using comparative tests reviewed and tested. The results showed that for the main hypothesis of the first and second, with the exception of the functional criterion, the net changes in the assets of each share, the information content of future performance and market reaction on the basis of the failure of long-term and short-term trends are increasing and decreasing for bad news is more than good news. In addition, for four main thirty to sixth hypotheses, the results show that the information content of future performance and market reaction do not follow reasonable and theoretical behavior to compare long-run and short-term patterns of failure of the performance criteria and Dividend, and Displays conflicting results. As a result, these four main hypotheses have been rejected

This study aims to investigate the effect of firm-specific characteristics predicting stock return on future idiosyncratic volatility. The sample of the study comprises of 100 listed firms on Tehran Stock Exchange during the period 2010 to 2017. The decile portfolio analysis approach has been used to determine the specific characteristics of stock return predictors. Also, the time series of the CAPM model and the EGARCH model are applied to extract conditional and unconditional idiosyncratic volatility on individual securities. In addition, a multivariate regression with a combination of data was used to examine the quality of the relationship between the firm-specific characteristics predicting stock return and the future idiosyncratic volatility of individual securities in the conditional and unconditional framework. The results of the portfolio analysis show that cross-sectional return variations of firms are associated with firms-specific characteristics such as firm size, book-to-market ratio, liquidity, momentum, and cash flow-to-price ratio. Also, the results show that the reverse and significant impact of the firm size and the cash flow-to-price ratio as well as the direct and significant impact of the book-to-market ratio and liquidity on the future idiosyncratic volatility.

 Behavioral Finance is a new paradigm in financial markets that recently and in response to problems, that modern financial paradigm is facing, try to explain anomalies events in financial area. Pricing anomalies in pricing models are reported in asset pricing literature as well as in behavioral finance literature. The purpose of this research is examining some other behavioral factors like herding and momentum returns at the industry-level at Tehran Stock Exchange and Iran Fara bourse. By using portfolio methodology at industry-level, and price data of listed companies at Tehran Stock Exchange and Iran Fara bourse during 12/07/2008 to 11/13/2018, herding and momentum returns are calculated for 24 industries that had at least five companies. At the first stage, preliminary results show the existence herding and momentum returns. At the second stage, pooled regression analysis shows that short-term subsequent return (1 month), medium-term  subsequent return (2 month) and long-term subsequent return (3 month), have a significant relationship with herding and momentum returns. At last, Portfolio Study Methodology is used for making stock portfolio based on herding and then momentum and premium subsequent returns of portfolios is calculated. Again, the findings indicate that portfolio with herding and momentum factors has higher return in comparison with the portfolio without mentioned factors, and herding factor result to higher return or momentum portfolios