ali ebrahimnejad

This Evaluation of fuzzy networks with imprecise data is crucial. In this article, we propose fuzzy two-stage network models based on the structure of central resource allocation models. Firstly, we obtain the target for the fuzzy decision-making units in the two-stage network by using central resource allocation models, with a maximum of one two-phase model in each stage of the network. Then, we determine the overall target for the network. The probability function approach is used in the two-stage fuzzy network models to rephrase the proposed models and find the target. In conclusion, we calculate the target for Iranian airlines using fuzzy data and the proposed model.

Considering intermediate data, two-stage networks eliminate the possibility of evaluating the performance of decision-making units in Black box mode. In this article, based on the structure of two-stage networks, Central Resource Allocation (CRA) models with fuzzy data are proposed. Then, two-stage network models are proposed in the form of combining data envelopment analysis and Raito analysis. In general, the models of this article using the CRA structure, Target introduce the decision-making units under the assumption of constant return to scale. CRA models in the two-stage network structure in DEA-R provide the possibility of finding suitable targets for decision-making units by solving a linear programming model instead of solving n linear programming problems (for n decision-making units). In conclusion, the models are proposed based on a practical study on 16 Iranian airlines.

This study aims to explore the dynamics of financial contracting in Iranian startups and high-tech companies, with a particular focus on the challenges posed by information asymmetry between investors and entrepreneurs. We collected and analyzed data from 123 Iranian Shareholder Agreements (ShAs). We employed a range of descriptive statistics to provide a comprehensive summary of the data. Also, to explore the relationships between our variables, we utilized Ordinary Least Squares (OLS) regression. The terms and conditions of these contracts were examined to understand the diversity and influence of these terms and how they are applied in the real world in the context of Iran. We also investigated Iranian venture capitalists' behavior in obtaining cash flow rights and control rights, and a complete description is presented through various factors, including components of cash flow rights and control rights. Our analysis revealed a limited diversity in the terms and conditions of the contracts, suggesting a potential emulation of U.S. ShAs. We found that Iranian venture capitalists tend to secure maximum cash flow and control rights, exceeding their U.S. counterparts. Preferred stocks emerged as the primary choice for investing in startup companies. However, a detailed examination of the relationship between cash flow rights and control rights indicated a lack of a unified and coherent approach in contract design, reflecting a highly conservative stance among investors. This study contributes to understanding financial contracting dynamics in emerging markets like Iran. It highlights the gap between theoretical frameworks and real-world practices, shedding light on how these factors shape the relationships between investors and entrepreneurs.

To improve the classic Hestense-Stiefel conjugate gradient method, Shengwei et al. proposed an efficient conjugate gradient method which possesses the sufficient descent property when the line search fulfills the strong Wolfe conditions (by restricting the line search parameters). Inspired by the scaled extension of the Hestense-Stiefel method which is recently presented by Dong et al., a scaled modification of the conjugate gradient method of Shengwei et al. is proposed which satisfies the sufficient descent condition independent of the line search technique as well as the convexity assumption of the objective function. Furthermore, the global convergence of the suggested method is discussed based on standard suppositions. In addition, a smooth approximation for the compressed sensing optimization problem is put forward. Numerical experiments are done on a set of classical problems of the CUTEr library as well as in solving compressed sensing problem. Results of the comparisons illustrate the superiority of the proposed approach.

We examine the behavior of institutional investors in response to extreme market fluctuations in the Iranian stock market. Specifically, we examine whether institutional investors engage in herding and follow the market, or are contrarian traders and provide liquidity during market turmoil. We examine the relationship between institutional investors' ownership percentage, stock returns, and volume in severe market fluctuations. We also explore the relationship between institutional ownership and stock returns for different types of institutional investors, including insurance, mutual fund, and investment companies. Using the daily data of listed companies from 2009 to 2019, we find that institutional investors trade against the direction of the market during market turmoil and provide liquidity for stocks in which they are a blockholder or the controlling owner. We find no evidence of herd behavior among institutional investors.

Pyramidal and network ownership structures, which give ultimate owners greater control rights over companies than cash flow rights, are prevalent in the Iranian stock market. Given the complex shareholding networks and significant changes in the ownership structures of large Iranian firms over the past two decades, this study aims to examine the relationship between ownership structure and company performance. Four measures are used to analyze ownership structure: cash flow right of the largest shareholder, wedge between control right and cash flow right of the largest shareholder, difference in cash flow rights of the two largest shareholders, and type of ownership. The study investigates their relationship with the performance and stock returns of 261 listed companies during the period of 2015 to 2020. The results indicate a positive and significant association between the cash flow right of the largest shareholder and firm performance, but only when the largest shareholder owns at least 15% of the company's shares. For firms with only one owner and less than 50% in control rights, there is no significant correlation between the cash flow right of the largest shareholder and performance. The study also reveals that ownership by insurance companies has a positive correlation with firm performance, while quasi-governmental ownerships have a negative correlation with performance.

In traditional optimization models, classical computers have been used to solve mathematical linear or non-linear models. In addition, by data envelopment analysis (DEA) models one can evaluate the relative efficiency of the decision-making units originally in the form of mathematical non-linear models. In this paper, a new attitude is presented in which quantum computers and quantum algorithms can be used to solve DEA models by two different methods. This suggested attitude is worthy to mention as this subject is new and will attract researchers to discuss and improve it.

Between 1387 and 1396, mutual funds experienced a significant growth in terms of capital under their management, so that during this period, the volume of their available capital has reached about 800 billion tomans. Over the period, however, the return on these funds was less than both the stock market index and the fixed income funds. This research aims to address the question of whether, despite their poor long-term performance, individual and institutional investors are able to earn higher returns by predicting high-return funds and proper timing of their buys and sells. In technical terms, is money smart in the mutual funds market? To test the ability of investors in these funds, we construct hypothetical portfolios based on fund flows and compare the average monthly return on inflows with outflows and the average fund. The results show that funds with more inflows perform better than the average fund which is consistent with the smart money hypothesis. Comparing the performance of individual and institutional investors separately also shows that individuals and institutional investors, on average, identify funds with higher and lower returns, but there is no evidence that one performs better than the other.

Daily liquidity to investors is promised by mutual funds, which allows them to redeem their money based on the prevailing Net Asset Value (NAV). A number of factors like trading suspension and daily price limits can cause redeemed NAV to deviate from the intrinsic values of fund units. Such “staleness” in prices can create arbitrage opportunities for the investors, who can invest or redeem their money at the expense of other passive investors. Using hand-collected data from quarterly mutual fund holdings, we documented significant deviations between the announced and “true” NAVs of Iranian mutual funds. We found that the investors reacted to and took advantage of such deviations. The wealth transfer between the fund investors was estimated to be approximately 1.3% of Total Net Asset (TNA), which was 4 times larger than the wealth transfer documented in the previous studies.

Iranian mutual funds’ average turnover rate stood at 330% in the years from 2001 to 2007. Such a high rate could lead to excessive trading costs for investors without necessarily bringing in high returns. The goal of this paper is to estimate transaction costs and examine their effect on the performance of the funds.

In addition to the explicit costs of trading such as transaction taxes and commissions, there are other, implicit, components such as bid-ask spread and price impact which are harder to compute and less recognized by investors. This paper used high frequency (tick-by-tick) trade and limit order book data, as well as the hand-collected quarterly holding and trading data for a sample of Iranian equity mutual funds to estimate the aforementioned trading costs. Then, the effect of trading costs on the risk-adjusted fund returns was examined using the four-factor alpha as our proxy.

Funds understudy spend on average 11% of their AUM annually on trading costs which is a considerable amount in comparison to their return (15.6%), during the sample period. The present study found no significant effect of trading costs on the funds’ performance in the sample. However, during the subperiod of 2013-2014, a negative and significant relationship was discovered between them.

As the obtained results of the present study proved, more trading activities of the Iranian fund managers’ do not lead to higher returns; accordingly a high trading volume generates only enough excess return to offset the associated transactions costs.

In classical data envelopment analysis models, a production system for measuring performance is considered as a black box and no attention is paid to the internal structure of decision-making units in the process of evaluation performance. However, it is important to consider the internal structure of the units to identify sources of inefficiency to calculate efficiency. On the other hands, the observed values of input and output data in real world problems are sometimes imprecise and vague. Therefore, in this paper, the network data envelopment analysis model is used in order to evaluate the performance of decision-making units with a two-stage structure in a fuzzy environment in which input and output values are displayed in terms of triangular fuzzy numbers.

To solve the fuzzy two-stage data envelopment analysis model, the fuzzy arithmetic approach is used and a lexicographic optimization method for calculating the fuzzy efficiency of processes and the fuzzy efficiency of the system is proposed.

The main advantage of the proposed approach over the exsiting approaches is that it solves fewer models for finding fuzzy efficiency.

The application of the proposed model is explained by evaluating the performance of 24 insurance companies.

In the present world, there are many two-stage systems which provide information of inputs, outputs and intermediate measures which are imprecise, such as, (stochastic, fuzzy, interval etc). In these conditions, a two-stage data envelopment analysis or a (two-stage DEA method) cannot evaluate the efficiencies of these systems. In several two-stage systems, the simultaneous presence of stages is necessary for the final product. Hence, in this paper, we shall propose the stochas- tic multiplicative model and the deterministic equivalent, to measure the efficiencies of these systems, primarily, in the presence of stochastic data, under the constant returns to scale (CRS) assumption, by using the non-compensatory property of the multiplication operator.Then, we will use the reparative property of the additive operation to propose the additive models as well as the deterministic equivalents, to calculate the efficiencies of two-stage systems, in presence of stochastic data, under the constant returns to scale (CRS) and variable returns to scale (VRS) assumptions. This is to illustrate that a simultaneous presence of the stages is not necessary for the final product and one stage compen- sates the shortcomings of another stage. Likewise, we shall convert each of these deterministic equivalents to quadratic programming prob- lems. Based on the proposed stochastic models, the whole system is efficient if and only if, the first and the second stages are efficient. Ul- timately, in the proposed multiplicative model, we will illustrate the proposed multiplicative model, by employing the data of the Taiwanese non-life insurance companies, which has been extracted from the extant literature.

In this study, we examine market reaction to the asset revaluation of companies listed on the Tehran Stock Exchange. To do so, we first estimate the market reaction to asset revaluation announcement. We then explore potential explanations for the market reaction to the revaluation. Asset revaluation can improve firm's access to financing by improving financial ratios; On the other hand, the increase in firm's capital from the revaluation is accompanied by stock split and, as a result, a decrease in the theoretical share price. This apparent drop in theoretical share prices could induce shareholders' interest as a result of money illusion. To investigate these alternative explanations, we run a cross-sectional regression of the cumulative abnormal return on proxies of each factor. To further explore the driver of market reaction, we examine whether firms that have re-evaluated their assets experience improvement in their access to finance or a reduction in their financing costs. For this purpose, we study a panel of listed companies between and for their access to finance, financing cost, investment, and financial leverage, controlling for firm and year fixed effects. Our results are more consistent with the theoretical price reductions causing the market reaction. We do not find evidence of asset revaluations leading to the firm's better access to financing.

An extensive literature going back to De Long et al. (1990) views individual investors as noise traders with low information and behavioral biases, who can move prices away from the intrinsic value. The goal of this study was to assess the interaction between individual investors and stock returns in the Iranian stock market along the following dimensions: First, the relation between the individuals’ intensive trading and the past returns was evaluated to see whether those investors were momentum or contrarian traders. Second, the predictability of subsequent short-term returns by the individual investors’ intensive trading was investigated. The individuals were found to have reacted to high past returns with more trading in the consecutive weeks. More specifically, the short-term returns of stocks could predict the eruption in the individuals’ intensive trading, but not necessarily their directions (buying or selling). However, contrary to some studies, no relation was found between the short-term returns and the individual investors’ intensive trading.

Data envelopment analysis (DEA) is a mathematical technique based on linear programming applied to evaluate the efficiency of decision-making units dealing with multiple inputs and outputs. In classical DEA models, it is assumed that input and output data are accurate though real-world applications require considering inaccurate and ambiguous data. Moreover, linguistic forms may be intuitionistic in nature rather than fuzzy. We propose a novel approach to solve DEA models characterized by intuitionistic fuzzy data. The model is transformed into a linear programming problem with an intuitionistic fuzzy objective function, and an alphabetical technique is applied to solve it. The proposed approach is easy to implement, involving a lower number of calculations than more computationally demanding techniques introduced in the literature. It also provides a set of ranking results that are significantly correlated with those derived from the implementation of more complex techniques. Its applicability would allow to extend the analysis of intricate evaluation scenarios common to the standard DEA literature into intuitionistic fuzzy environments.

This paper aims to estimate the influence of managers, including CEOs and members of the board, on changing the firms’ policies and performances. To this end, we first assemble a hand-collected database on the composition of the boards of directors and CEOs across 488 firms listed on the Tehran Stock Exchange and Iran Fara Bourse Co. for the period 2010-2018. We attempt to provide an overview of the characteristics of the top executives of the Iranian firms for the first time. Correspondingly, some of the findings point out an average of two-year tenure for managers in companies, the presence of the majority of the board members in only one company over our sample period, the inverse relationship between the managers’ tenure and their level of education, and low participation of women as managers Having combined these data with the data from the financial statements, we ran a set of regressions on a sample period of 2010-2016 to identify whether managers have significant effects on the firms’ behavior and performance. The results show a significant increase in the adjusted  for the regressions of the firms’ performance - in contrast to the regressions of the firms’ policies - after adding managers fixed effects. Meanwhile, only a small fraction of managers have significant effects in the regressions, and for a small fraction of them the magnitude of the effects is large.

The disposition effect refers to the tendency of selling stocks that have appreciated at price and holding stocks whose price is lower than the purchase price. Although an extensive literature has examined and confirmed the existence of the disposition effect among individual investors, there is no consensus in the literature as to whether institutional investors are also subject to similar behavioral biases or not. We test for the presence of the disposition effect among a sample of Iranian mutual funds.

We measure the disposition effect both at the aggregate and fund level, using hand-collected quarterly transactions data for a sample of Iranian mutual funds from 2010 to 2017. Our data has two unique features compared to similar studies; first, we know the exact buying price of stocks held in mutual funds' portfolios, whereas most studies need to estimate the buying price by making assumptions about purchase timing and using the prevailing market prices as a proxy. Second, unlike most studied markets, there are no capital gains taxes on the Tehran Stock Exchange and tax-motivated trading does not affect our findings.

We find that Iranian mutual funds tend to sell winning stocks more quickly than losing stocks. To be specific, the probability of selling a winning stock is approximately 1.46 times the probability that a losing stock be sold. Excluding taxes and commissions in calculating the realized profit on the sold stocks, the ratio grows to 1.51. The measured disposition effect is not driven by the effect of tax-motivated selling, since there are no capital gains taxes on the Tehran Stock Exchange. The documented disposition effect cannot be explained by funds’ internal portfolio rebalancing regulations nor by the potentially higher trading cost of selling low-priced stocks. The disposition effect exhibits a mild downward trend line throughout the sample period; however, the downward trend is not statistically significant. Partitioning the data based on the fund's portfolio value shows that both more skilled and less skilled fund managers – as proxied by fund size - are prone to the disposition effect.

Our study finds strong support for the disposition effect among mutual funds. Our results are relevant for both mutual fund managers and policy-makers.

Open limit order book can be used as a tool to enhance transparency and price discovery in financial markets by showing the offered volumes and prices of buy and sell orders. In this study, we aim to answer two questions by examining the limit order book on  Tehran Stock Exchange: 1) Does the information in the limit order book have the predictive power for stock price movements in the short-term?; 2) Can increasing the public disclosure of the limit order book from three to five levels enhance price discovery?

For this purpose, three different regressions areused, each of which measures the volume and price information of the two sides of supply and demand in a different way and examines the ability to predict short-term behavior of stock price by this information.

The results show that the limit order book contains information about future short-term returns. Our results also indicate that increasing the public disclosure of the limit order book from three to five levels can enhance transparency and price discovery but it causes the marginal predictive power of additional levels to decrease.

Itradayn patterns of trading volume, size, return, and volatility in the Tehran Stock Exchange (TSE) have been investigated using high frequency data from 2008 to 2015.

First, the daily patterns of the four variables namely, trade volume, trade value, price volatility range, and returns in stocks have been investigated using high-frequency data. Then, the role of insider information in formation of the given patterns has been examined.

Our results indicate that trading value and volume follow a J-Shaped pattern , whereas absolute return exhibits an L-Shaped behavior . Our findings are consistent with the existing studies which document an increase in trading value and volume as well as absolute return. However, unlike the existing literature, we do not find a U-Shaped pattern in returns, and no statistically significant difference in returns is found throughout the trading hours. To examine the behavior of informed traders, we examine midsize trades and, consistent with the predictions of Barclay and Warner’s (1993) stealth-trading hypothesis, we find that they have higher price impact compared to other trade sizes. However, our findings do not support the intraday stealth trading pattern, as insiders prefer to trade in low and medium trade size to avoid revealing their information. This may be due to the low liquidity of the TSE.

The findings of this study may show policymakers and planners in the Iranian capital market that halts in the stock market can directly affect traders and increase their transaction risks. Meanwhile, traders who are planning to buy or sell stock in large volumes can use the patterns provided in this paper to understand when the price effect is at its lowest point, and this can help them execute their transactions more efficiently.

An architecture shows to what extent a system meets the needs of the stakeholders, so designing a desired architecture produces very high-quality software tailored to the needs of the stakeholders. Thus, finding a software architecture model is quite critical, and to achieve this goal, a suitable architecture style model must be used. In this regard, attempts are made to deploy the behavior of the candidate software styles as well as the stakeholders’ desired model as functions graphs, so that the desired architecture style model graphs, which meet the maximum needs of the stakeholders, are selected by comparison. Fuzzy Cubic Spline is used in the structure of the proposed algorithm, which requires turning qualitative data into quantitative data. To evaluate the proposed approach, a controlled experiment is also conducted. The proposed approach is compared with an analytic hierarchy process-based approach (AHP), TOPSIS and PTFG (Prioritizing using tensor and fuzzy graphs) in the experiment. The results analysis demonstrates that our approach needs to less time complexity and is much easier to use and highly accurate.

Pyramidal ownership structures and cross-ownership are common phenomena in developing economies. These structures result in a divergence between voting rights and cash flow rights on the one hand, and create internal capital markets through which firms can raise capital internally instead of going to the public market when they need additional financing. In the present study, the effects of firm interlock and stock price synchronicity in Iran Stock Market was investigated. We used a unique data set containing stock ownership and directors of all companies listed on the Tehran Stock Exchange considering three definitions of management, stockholding, and ownership and examined interlock through both equity ties and interlocking directors. We found that over 40 percent of all listed companies belong to networks of interconnected companies and there was a significantly positive relationship between being a member in each of these networks and the profitability of the firm alongside other colleagues. We also documented a complex set of networks among listed and unlisted companies, which have not been previously documented. We further find that pairwise interlocks through equity ties – either direct ownership or common owner – are correlated with higher stock price synchronicity, whereas common directorship is not linked to return co-movement. We can also claim that the effect is decreasing as firms become farther away from each other within a network. The results show that firm interlock, particularly through cross holdings and common ownership, can increase stock price synchronicity.

An extensive literature examines managers’ incentives to smooth reported earnings using accruals in order to reduce price fluctuation of stocks in markets. Banks have additional incentives to engage in earnings management for a number of reasons, including tighter regulatory environment. They also have the ability to manage earnings using loan loss provisions (LLP). This paper examines earnings management using accruals – in particular, LLP - as the main accrual item in financial reporting of banks in the Iranian banking industry from 2005 to 2016. From previous studies, we expect that for banks with good (poor) current performance and expected poor (good) future performance, managers will save income for (borrow income from) the future by reducing (increasing) current income through LLP, especially discretionary LLP (DLLP). We also examine the effect of external financing, availability of other methods of earnings management like increasing (decreasing) non-operating income and capital requirements and also the relation of DLLP with risk. Our results indicate that bank managers do save earnings through DLLP in good times and borrow earnings using DLLP in bad times. We also find that bank risk is negatively associated with discretionary accruals.

The Iranian pension system has faced multiple challenges and significant deficits over the past years. This has made the pension system reform a top priority and improving the governance of pension funds is increasingly recognized as an important element of such reform . This paper highlights the main differences between the effectiveness of internal and external corporate governance mechanisms in corporations and pension funds . We argue that the typical external governance mechanisms that help align the interest of managers and main stakeholders , namely shareholders , in corporations , are not applicable in the context of pension funds . As a result , the governance of pension funds mostly relies on internal governance mechanisms and , in particular , the board of trustees . We offer tentative thoughts and solutions about the structure of the board of trustees and other internal governance mechanisms including transparency and information disclosure .

In an efficient market, prices should reflect all information available to investors. In reality, several frictions can prevent prices from incorporating the information immediately after disclosure. This can cause delays in the incorporation of information into prices and increase the premium investors require for investing in stocks. Using an empirical measure of price delays, we examine the effect of these frictions and the resulting price delays on the cross-section of expected returns on Tehran Stock Exchange. The delay measure is defined as a function of contemporaneous and lagged systematic information that is impounded into prices. If frictions prevent information from impacting prices contemporaneously, lagged information should have explanatory power for stock returns. We find that stocks with higher price delays tend to have a premium that is not explained by known risk factors of market risk, size, value, momentum and liquidity. Our results are robust to a number of empirical specifications, namely the zero-investment portfolio returns and Fama-Macbeth regressions

In analyzing mutual funds’ performance, the funds’ return is typically deemed as a performance measure and this measure is not necessarily discriminated by the virtually investors’ realized return. This is despite the fact that depending on the investors’ timing strategy and the amount they decide to invest, the actually realized return may likely be different with the announced return by the fund, which is normally based on the buy and hold strategy. In the present study, we are going to answer how investors’ timing decisions in mutual funds may affect their returns and eventually their behavior. To do so, we have exploited the registered mutual funds’ cash flow turn over over 1390 to 1395 (2011-2016) and finally come up with conclusion that inefficient market timing by mutual funds investors’ have culminated in diminishing 2.2 % their monthly return (30 % annually). This considerable negative effect can significantly alleviate the investors realized return even in outperforming mutual funds