Iranian Journal of Finance

Abstract foreign investments have always been welcome and policy makers always do their best in order to attract more and more capital into their area; But a question which gave rise to a series of studies is that is FDI always beneficial for the recipient and does it under all circumstances help the growth in the host economy? In order to answer this question, we first examined whether or not FDI, by itself, has any significant impact on growth and the results proved that FDI affects growth positively in our full sample. We then show that FDI’s effect on growth is different in developed and non-developed countries. A surprising finding in our study is that in developed countries foreign flows of investment do not affect economic growth where this effect in non-developed countries is relatively high and significant. Three different stock market indicators (market capitalization, value traded and turnover ratio) are then introduced and it is tested whether the differences in FDI’s impact in developed and non-developed countries is due to their stock-market-related financial absorptive capacities. Our key contribution in this paper, along with our other novel findings, is that we introduce cut-off levels for these three indicators which successfully split our sample into one sub-sample in which FDI strongly affects growth and one in which FDI’s effect on growth diminishes.     

Abstract Nowadays, predicting the financial behavior of investors plays a crucial role in decision-making and the financial policy-making process. This study is aimed at providing a paradigm to predict the financial behavior of investors in Iran’s stock market. 24 experts were interviewed to identify the variables, and 24 variables were identified. The interpretive structural paradigming was carried out using a self-interaction matrix based on the experts’ opinions. The MICMAC analysis has been used to identify the types of the variables. As findings of the study, a five-level paradigm was determined, in which environmental factors and the background of financial behavior on the fifth level were the most influential variables and also arbitrage, bias, and the perceptual mistake were the most impressible variables of the paradigm on the first level. MICMAC analysis of this study suggested that the variable of environmental factors had low dependence and high efficacy. Furthermore, psychological projection, perceptual mistake, arbitrage, and bias are dependent variables with high dependence and low efficacy. Other variables are mediator variables with high dependence and effectiveness.

Abstract The stock exchange is considered to be an important establishment to finance long term projects, on one hand, and to collect savings and finance of private section. The stock exchange can be a safe and secure place to invest surplus funds to purchase corporate stocks. As recession and prosperity in this market can have a great role in stockholders` decision-making, it becomes vital to predict these cycles. In this paper, using model MSMH(4)AR(2), we extract the financial cycles of the market. Then, using the ant colony algorithm, we determine the most significant predictors and predict the market financial cycles using neural networks. The results show that the PNN model performs better in predicting the future market with respect to the criteria of mean squared error, the root mean squared error, the model accuracy and kappa coefficient.

Abstract One of the most important effective elements in economic growth is the efficiency of manufacturing units. Therefore, measuring the efficiency of firms is necessary in order to increase efficiency in future planning courses. In the current research, using Stochastic Frontier Production Function, the efficiency of firms in Tehran Stock Exchange has been measured. In the above method, the efficient frontier is determined by using the Trans log production function, and the efficiency of each firm measured by the efficient frontier. The most important superiority of Stochastic Frontier Production Function is to specify the role of random and environmental elements (out of firm authorities) and inter-organizational elements (in-firm authorities) to assess the inefficiency of firms as compared to other methods. Thus, 105 firms were selected using maximum likelihood method in 2008-2017 to evaluate the research model. Results indicated that the minerals industry and cement industry with the averages of 53% and 90% had the least and most efficiency values, respectively. Separating the inefficiency values showed that the food industry and chemicals industry had the least and most inefficiency resulting from the firm authorities as 33.6% and 95.2%, respectively. According to research results, financial analysts and investors are recommended to rank the efficiency and assess the performance based on the firm authorities. Due to the importance of efficiency measurement in operational auditing, the auditors are recommended to use the current research model to assess the firm’s efficiency. Also, Organization of Industries and Mines is suggested to tackle the obstacles after identifying the elements out of firm authorities which affect the inefficiency in the firms.

Abstract The mutual relationship between monetary and fiscal policies and value at risk is one of the most important topics in the financial economics literature and accounts for the vast majority of empirical studies. Therefore, the main objective of this paper is to investigate the effects of monetary and fiscal policies on conditional value at risk in the financial sectors of the stock exchange, bank and insurance during the years 1995-2017. For this purpose, by quantile regression method and in the form of Adrian and Brunnermeier approach, the conditional value at risk of these three financial sectors is estimated and then by using the seemingly unrelated regression equation approach in panel data evaluated the effect of liquidity money variables. The interest rate on facility payments, the real exchange rate, the government's budget deficit, real GDP growth, and the degree of economic openness are subject to conditional risk. The results of the model estimation indicate the significance of the effect of liquidity money, interest rate on facility payments and real exchange rate variables on conditional value at risk in each of three relevant equations, and real GDP growth variable in the model, Exposure to the conditional value at risk of the insurance sector has a negative and significant effect. Also, the degree of openness of the economy in any of the three estimated equations has no significant effect on the conditional value at risk. 

Abstract This study postulates the relationships between earning quality and investment efficiency among Tehran Stock Exchange-listed companies with an emphasis on the moderating role of board characteristics including independence, the duality of executives and the financial expertise of members. The research is applied in terms of purpose and takes a correlative-descriptive approach. The statistical population is comprised of TSE listed companies from 2008 to 2018 and, the final sample consisting of 78 companies was selected using systematic (purposeful) elimination. To test the hypotheses, two regression models were estimated using Ordinary Least Squares method through Eviews software. The empirical results revealed a positive and significant relationship between the quality of earning and investment efficiency in TSE publicly-traded companies. As well as, the board members' independence and financial background can significantly exaggerate such a relationship. Based on our findings, capital market legislators, regulators, and policymakers may reinforce the governance role of the board of directors in monitoring the behavior of firms, and as a result, increase the efficiency of allocating capital among companies listed in TSE and also in macroeconomic levels. The findings can persuade corporate shareholders to pay more attention to the degree of independence and expertise of their board of directors to gain more return on their investment opportunities.

Abstract One of the main concepts in finance is portfolio diversification and optimization. Typically, investors use the risk and return approach to diversify their portfolios. However, risk spillovers and market connectivity should also be considered when making investment decisions, especially during times of crisis. The TVP-VAR approach is used in this study to analyze risk spillovers and connectivity between the S&P 500 index, green bond, real estate, oil market, and dollar index in the USA from 2016 to July 2022. The TVP-VAR model is a time-varying model that may consider current political and economic circumstances. As a result, investors can choose wisely when it comes to their portfolios. According to comparisons with other markets, the S&P 500 index and the real estate market are the two most significant sources of volatility in the system. In fact, they not only transmit greater volatility, but they also take it in more. After 2020, there will likely be a significant increase in the volatility of the real estate market and the S&P 500 index due to the COVID-19 epidemic. Additionally, as anticipated, other markets have an impact on the green bond market. It does not, however, transmit them.

Abstract This study aims to present a model for predicting corporate default among Tehran Stock Exchange’s selected industries. To do this, corporate default drivers were identified and selected by referring to previous research findings and using experts’ opinions. These drivers were divided into five categories: accounting ratios, market variables, macroeconomic indicators, nonfinancial factors, and earnings quality measures. Structural equation modeling (SEM) technique was used to derive the prediction model. In this technique, corporate default drivers were used as latent independent variables, and their constituent factors were considered as observable indicators of the above variables. In addition, corporate default, as the latent dependent variable, was calculated by a measure based on the Black-Scholes-Merton (BSM) option pricing model. After implementing structural equation modeling (SEM) technique by use of Smart PLS software, a prediction model that contains influential drivers of corporate default was derived and presented for each of the selected industries.

Abstract In this research, we use a pair trading strategy to make a profit in an emerging market. This is a statistical arbitrage strategy used for similar assets with dissimilar valuations. In the present study, smooth transition heteroskedastic models are used with the second-order logistic function for producing thresholds as trading entry and exit signals. For generating upper and lower bounds, we apply the rolling window approach and one-step-ahead quantile forecasting. Markov chain Monte Carlo sampling method is used for optimizing the parameters. Also, passive strategy in the out-of-sample period is used to compare the profits. The population consists of 36 daily stock returns in Tehran Stock Exchange. Then, we select ten pairs from these stocks and use Minimum Square Distance method, and five pairs from one industrial sector. Finally, we see strategy1 and 2 have positive returns in the out-of-sample period, and they produce higher returns than passive strategy.

Abstract Increased government revenues and improved economic efficiency are the main goals of implementing privatization and regime switch in Iran. Information efficiency in the capital market can also be considered as a milestone for increased government revenues and improved economic efficiency. In this study, according to the results of regime switching GARCH models, it is determined that stock returns have had different regimes during the study period (2000-2015). According to the results of the estimation of the three-regime GARCH model, the most important events of the Article 44 of the Constitution in the direction of privatization in Iran's economy and its implementation during the study period have been effective in switching the regimes of the fluctuating process of efficiency. Market risk has also been identified as a factor affecting regime switching in the stock return process, which is due to the behavior of stockholders in low-fluctuation regimes compared to high-fluctuation regimes and liquidity. Also, according to the Kalman filter model, poor performance has been established in Tehran Stock Exchange, which indicates that privatization policy has been effective in improving the efficiency of this marketplace. Using the technique related to the detection of structural failure in the liquidity variable as one of the signs of the stock market depth, the failure of this series was detected by virtue of the implementation of privatization, and it was discovered that privatization increased market liquidity as one of the principles of market development.

Abstract The aim of this paper is to analyze the multiscale pricing model with the wavelet analysis approach, Fama-French three-factor model, and nonliquidity in Tehran Stock Exchange. It was also desirable to figure out how stock returns, Fama-French factors, and nonliquidity were related in different intervals. According to the results, various outcomes were obtained at different intervals. Stock returns had significant relationships with  (the ratio of book value to market value) and nonliquidity in the long term. Stock returns had significant relationships with the beta,  , and company size in the midterm, too. There was also a significant relationship between stock returns and the company size in the short term. The proposed methodology suggests that investors should employ dynamic portfolio management strategy and multiscale risk-return evaluation to seize investment opportunities.

Abstract This study investigates the effect of market inefficiency and environmental uncertainty on CEO risk taking. Prior research, however, have struggled to establish this relation empirically; moreover, some evidence points to the possibility that the CEO risk appetite is lower for firms active in inefficient markets. The opportunistic approach of managers leads to decisions about personal interests and imposing costs on shareholders by decreasing risk taking. In order to investigate the issue, data on companies listed in Tehran Stock Exchange, from 2008 to 2018, were extracted and a panel regression model was used to test the research hypotheses. Consistent with expected relation between market inefficiency, environmental uncertainty and CEO risk taking, the managers' risk taking decreases with respect to market inefficiency and environmental uncertainty. Managers may benefit from increased fluctuations in risk orientation, but are more sensitive than shareholders and have less restrictive choice that avoids higher risk.

Abstract According to accounting literature, value relevance of earnings is caused by the relationship between earnings and return. Had the earning response related to negative returns exceeds positive ones, it can be concluded that management has in fact revealed the bad news via conservative methods; this influences the relationship between earnings and return, which increases the amount of value relevance of earnings. Researches show that disclosing policies (the relationship between earnings and return) of business firms are sensitive to business cycles, thus it can be argued that if the business cycle faced contraction or expansion, the reaction of earnings against negative returns would differ comparing to positive returns. The aim of this research is to assess accounting conservatism and value relevance of earnings in business cycles. The samples of this study are 100 companies listed in TSE; their information for the period of 2007 to 2016 were tested. The results from regression test demonstrate that accounting conservatism and value relevance of earnings is much higher in contractionary economic cycles comparing to any other economic cycles. This result is pursuant to Jenkins et al (2009) research

Abstract The investment decisions of managers of investment funds (especially equity investment funds) have an impression on the returns of individuals who have deposited their capital in these funds. Therefore, the issue of evaluating the performance of investment funds and their managers is imperative for investors. The research aims to investigate the effect of cross-sectional alpha dispersion on investors' evaluation of the performance of investment funds. We extract data regarding 31 equity investment funds from 2012 till 2022 and calculate the interquartile ratio of Jensen's alpha called "IQR" and "Performance-Flow Sensitivity" along with control variables. Then, the hypothesis test model was fitted using the multivariate regression analysis using the Generalized Least Squares method. Empirical findings show a negative and significant connection between the alpha dispersion of investment funds and performance-flow sensitivity. Based on the results, one credit increase in the standard deviation of alpha dispersion leads to a decrease of about 0.4% in the ratio of performance-flow sensitivity. Environments with high alpha dispersion of investment funds will targeted by unskilled managers to introduce themselves as successful and skilled managers to investors and mislead them. Therefore, when the alpha of investment funds has a higher dispersion, the type I error possibility investors will face increases. Individuals may consider an inefficient manager to be competent and skilled. We will provide some suggestions in this regard.

Abstract Cash flow is one of the critical resources in the economic unit and the balance between available cash and cash needs is the most important factor in economic health. Since judgments of many stakeholders such as investors and shareholders about the position of the economic unit are based on liquidity situation, so predicting future cash flow is crucial. In this research, the impact of cash and accrual items on cash flow forecasts has been studied. Providing a proper model to predict operating cash flows and review some important characteristics of cash flow forecasting regression models, using a multilayer perceptron and determining the best model by using accrual regression model variables for predicting cash flows. For this purpose, 287 firms listed in Tehran Stock Exchange during 2008 to 2017 were studied; Linear and nonlinear regression, correlation coefficient and artificial neural network statistical methods have been used for data analysis and predictive power of powers was compared by using the sum of squared prediction error and coefficient of determination. Results showed that the accrual regression model can predict future cash flows better than other tested models and among corporate characteristics, the highest correlation belongs to sales volatility and firm size with accrual regression models. On the other hand, results of fitting different neural network models indicate that two structures with 8 and 11 hidden nodes are the best models to predict cash flows.

Abstract Asset-liability management (ALM) helps managers achieve their respective objectives by surveilling and controlling the ways through which resources are obtained and allocated. Furthermore, with the help of liquidity management, which sets the required cash by banks for fulfilling costs and other needs (e.g. the cash requested by depositors), ALM controls the risk. In addition, ALM helps managers realize profitability and efficiency of the bank through the application of goal programming (GP) whereby multiple objectives are simultaneously considered when making decisions.
In the present research, upon collecting the required data and information, acquiring opinions of experts at a sample bank, and investigating balance sheet of the bank while considering respective constraints, orders of priority of objectives were determined. The results indicated consistency of some items in the balance sheet, such as cash inventory and liability to Central Bank with those set by the model. On the other hand, when it came to some other items, including receivables from the government and credited facilities to public sector, the observed growth was in line with that anticipated by the model. In the meantime, for most items of the balance sheet, including termed deposits and other deposits, investments, and joint activities, the model suggested variable yet positive growths; the growth was higher in demand deposits which are known as less expensive resources, indicating facts about Iranian banking system and Iranian economy where communities are making greater deals of effort to attract this sort of resource.

Abstract Simultaneous understanding of volatilities and changes in financial markets is very important to optimize the portfolio and risk management methods. The 2008 financial crisis led into devaluation of most assets, increased volatilities and endangered several institutional investors' survival. When the stock market' correlation is highly enhanced, risk and return management with the classic portfolio theory becomes severely challenging. In this study, to manage systematic and non-systematic risks by investors and policymakers in case of similar financial crises, the Effect of global financial crisis contagion is examined through the path of S&P500 global index, and DFM regional index of different industries of Iran Stock Market is examined using DFGM contagion test and stochastic Ornstein Uhlenbech process. The results show that Dubai Stock Market has an important role in crisis expansion into different sectors of Iran Stock Markets so that the fundamental contagion effects are channelled via this direction. Also, according to the results, the starting point of the global financial crisis contagion was the basic metals industry, and the contagin happened in metal ores and petroleum products sectors with different rates. Finally, the global financial crisis is spread into different industries of Iran Stock Market via financial links and not trough commercial ones. Identifying the direction of contagion of financial crisis provides an opportunity for investors to apply hedging and asset allocation strategies optimally.

Abstract In recent financial scandals, related parties transactions (RPTs) have been as one of the major concerns, so that the targeted use of these transactions and lack of their disclosure or insufficient disclosure are some of the factors in the failure of the corporates. In RPTs, there is a risk that the related party may be favoured with terms that could harm the interests of the company’s shareholders. The purpose of this study was to investigate the effects of different types of related parties transactions on the firm value with the moderating role of the audit committee incorporates listed in Tehran Stock Exchange. The research statistical sample consists of 100 listed firms in the Tehran Stock Exchange in 6 years of 2013-2018. This research, based on the nature and content, is a descriptive/ correlational research. Using Panel data and multiple regression, the results of the research show that there is a negative relationship between RPTs and the firm value. The findings also show that there is a positive relationship between the audit committee and the firm value. Also, the findings show that different types of RPTs have a different effect on the firm value. The results also show that the audit committee does not affect the relationship between RPTs and the firm value. 

Abstract Identifying the causal relations between trading volume and stock returns and between trading volume and return volatility plays a vital role in identifying profitable investment opportunities. In this study, the Granger causality test was conducted to analyze the causal relationships between the mentioned variables in Tehran Stock Exchange. Consequently, the Vector Auto Regression (VAR) model was employed to determine the conditional mean equations of returns and volume. Moreover, the bivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model was used to model the conditional variance equation, stating the relationship between volume and return volatility. According to the results, no bilateral causal relationship can be ascertained between returns, volume, and return volatility. In other words, return and return volatility could barely predict volume; therefore, volume cannot be the Granger causality of the other two variables. However, stock returns were found to have an important role in determining the volume. Likewise, return volatility can be used to predict volume accurately. In fact, stock returns and the return volatility were both the Granger causalities of the volume.

Abstract Working capital should be available to any company to have the sufficient funds to cover short-term commitments and operating costs in the future. This guarantees the continuity of the company’s activities. Given the significance of the role of working capital management (WCM) in the companies, the study analyzed the content of texts and studies done in this field, presented three main hypotheses and examined the effect of most of the variables affecting WCM (both external and internal factors of the company), as well as the consequences of WCM in 161 companies listed in Tehran Stock Exchange (TSE) during a seven-year period from 2011 to 2017. The purpose of the study was to determine the most important factor affecting WCM and its consequences.
The hypotheses were tested using multivariate regression and Granger causality test. The hypothesis testing indicated that extra-organizational factors such as gross domestic product (GDP), inflation rate and exchange rate have the greatest effect on WCM. Moreover, hypothesis testing indicated that some intra-organizational factors, such as current ratio, capital expenditures, financial leverage, return on assets, operating cycle, operating profit return, institutional shareholders ownership-percentage, and independence of board of directors affect WCM. Finally, hypothesis testing showed that optimal capital management improves the firms’ performance.

Abstract The purpose of this paper is to analyze the relationship between default risk and momentum effect using data from companies listed on Tehran Stock Exchange.To calculate default risk,we used Black-Scholes-Merton (BSM) option pricing model. To describe momentum effect, by determining the formation period to be 6 months, and the holding period to be 3,6, or 12 months, we firstlyexamined the profitability of short term (3/6), midterm (6/6), and long term (12/6) momentum strategies and found that during 2010-2015 time period, only midterm momentum strategy is profitable.Then,we showedthere is no relationship between default risk andmomentum effect.

Abstract In this research, we use jump beta and continuous beta as indicators of financial sector companies systematic risk and study their determinants in banking, insurance and investment industry. In result, the value of jump beta is higher than continuous beta. Jump beta of Banking industry and Investment industry is considerably lower than average. We found some negative and positive effects of firm characteristics on jump beta and continuous beta. In insurance companies, the supremacy of jump beta is influenced by firm characteristics. Size has positive effect on aggressiveness of both continuous and jump betas in investment companies. Current ratio has positive effect and debt ratio has negative effect on aggressiveness of insurance companies. Firm characteristic has some positive and negative effects on continuous industry beta deviation, but no effect on jumpy one. Inflation has negative effect on continuous beta but has no considerable effect on jump beta. Inversely, exchange rate has negative effect on jump beta but has no sensible effect on continuous beta. Influence of growth rate is strong positive for all industries of financial sector but weak positive for banking and insurance companies

Abstract Behavioral finance is a new issue raised by some financial intellectuals over the past two decades and has been quickly addressed by professors, experts, and students throughout the world. Investigating the factors affecting investment decisions is carried out in the field of behavioral finance; in other words, the focus of behavioral finance is on the specific charac-teristics of human behavior and applying them in asset pricing. Empirically, pricing models rarely include psychological factors, but the noticeable point is that nowadays, researchers have found behavioral factors influencing empirical asset pricing models that can manipulate returns on asset mispricing. Behavioral asset pricing is the result of applying behavioral finance theories within traditional asset pricing theories. Thus, despite the existence of many asset pricing models, due to their weaknesses and lack of comprehensiveness, as well as the necessity of reviewing behavioral factors, this study aims to model asset pricing through behavioral models. Using the data from 141 listed firms in Tehran Stock Exchange over the years 2008 to 2017 and multivariate regression, this study is an attempts to model asset pric-ing through employing behavioral models and Fama-French approach. Using Fama-French approach, the results showed that accounting information risk, investors’ trading behavior, and investors' sentiment have a direct and significant impact on asset pricing.

Abstract one of the most important financial and investment issues is Portfolio selection, that seeks to allocate a predetermined capital (wealth) over one or multiple periods between assets and stocks in such a way that the wealth of investor (portfolio owner) is maximized and, Simultaneously, its risk minimized. In the paper, we first propose a mathematical programming model for Portfolio selection to maximize the minimum amount of Sharpe ratios of the portfolio in all periods (max-min problem). Then, due to the uncertain property of the input parameters of such a problem, a robust possibilistic programming model (based on necessity theory) has been developed, which is capable of adjusting the robust degree of output decisions to the uncertainty of the parameters. The proposed model was tested on 27 companies active in the Tehran stock market. In the end, the results of the model demonstrated the good performance of the robust possibilistic programming model. 

Abstract Earnings management has a negative effect on earnings quality and it may weaken validity of financial reports. The main focus of researches about earnings management is why companies manipulate earnings. Pricing power of companies can potentially affect earnings management. Since the relation between product pricing power and earnings management has not been studied in Tehran Stock Exchange, this research tries to find a relation between product pricing power and earnings management and a relation between existing competition in industries and earnings management in Tehran Stock Exchange.
The results show that there is not a significant relation between pricing power and earnings management. This is due to the mandatory nature of rules and regulations of product pricing in many internal industries. Also, those companies in more competitive industries may manage earnings in order to limit their competitors in obtaining precise information. The results of the present research show that there is a significant relation between existing competition of industries and earnings management in industries such as vehicle & parts, cement, gypsum & lime, chemicals, main metals, tile & ceramic, machinery & equipment, and pharmaceuticals. On the other hand, the results from the research model indicate no direct relation between the competitive pressure and earnings management.