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Abstract In dealing with the real-world optimization problems, a decision-maker has to frequently face the ambiguity and hesitancy due to various uncontrollable circumstances. Rough set theory has emerged as an indispensable tool for representing this ambiguity because of its characteristic of incorporating agreement and understanding of all the involved specialists and producing more realistic conclusions. This paper studies an application of the rough set theory for a multi-objective non-linear programming problem that originates for the management of solid wastes. Municipal solid waste management is a global problem that affects every country. Because of the poor waste management system in many nations, the bulk of municipal solid waste is disposed of in open landfills with no recovery mechanism. Hence, an effective and long term waste management strategy is the demand of the day. This research offers an incinerating, composting, recycling, and disposing system for the long-term management of the municipal solid waste. A model for the municipal solid waste management with the goal of minimizing the cost of waste transportation, cost of waste treatment and maximizing the revenue generated from various treatment facilities is developed under rough interval environment. To tackle the conflicting nature of different objectives, an approach is proposed that gives the optimistic and pessimistic views of the decision-maker for optimizing the proposed model. Also, the biasness/preference of the decision-maker for a specific objective is handled by establishing the respective non-linear membership and non-membership functions instead of the linear ones. Finally, to demonstrates the practicality of the proposed methodology, a case study is solved and the obtained Pareto-optimal solution has been compared to those obtained by the existing approaches.

Abstract In the literature, fuzzy arithmetic approach has been used for solving fuzzy data envelopment analysis (DEA) model in the presence of undesirable outputs by use of ideal and anti-ideal decision-making units (DMUs). In order to obtain the best and the worst fuzzy efficiencies, such an approach allows each DMU to choose the most favorable weights via optimizing its own evaluation that needs to solve various mathematical models. On the one hand, solving one mathematical model to find the best fuzzy efficiency and solving another mathematical model to find the worst fuzzy efficiency for each DMU increase the computational complexity significantly. On the other hand, the fully flexibility of weights leads to the different set of weights that may not be desirable. This paper proposes a common-weight method from two optimistic and pessimistic perspectives in fuzzy environment to determine the common sets of weights (CWS) to compute the best and the worst fuzzy efficiencies of all DMUs. The advantages of using common-weight DEA method based upon fuzzy arithmetic approach are reduction of the computational complexities and evaluation of equitably the best and the worst fuzzy efficiencies on the same base. The proposed approach first solves one linear programming model to compute each of the best and the worst fuzzy efficiencies of all DMUS, and then combines them to find a relative closeness index for the overall assessment. The developed approach is illustrated by a numerical example form the literature and the obtained results are compared with those from the existing ones.

The shortest path (SP) problem constitutes one of the most prominent topics in graph theory and has practical applications in many research areas such as transportation, network communications, emergency services, and fire stations services, to name just a few. In most real-world applications, the arc weights of the corresponding SP problems are represented by fuzzy numbers. The current paper presents a fuzzy-based Ant Colony Optimization (ACO) algorithm for solving shortest path problems with different types of fuzzy weights. The weights of the fuzzy paths involving different kinds of fuzzy arcs are approximated using the α-cut method. In addition, a signed distance function is used to compare the fuzzy weights of paths. The proposed algorithm is implemented on three increasingly complex numerical examples and the results obtained compared with those derived from a genetic algorithm (GA), a particle swarm optimization (PSO) algorithm and an artificial bee colony (ABC) algorithm. The results confirm that the fuzzy-based enhanced ACO algorithm could converge in about 50% less time than the alternative metaheuristic algorithms.

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.

In this study, we examine the market reaction to the asset revaluation of listed companies. We first estimate the market reaction to the asset revaluation announcement, then explore potential explanations for the market reaction. Asset revaluation can improve firm's access to financing by improving financial ratios. On the other hand, the increase in the firm's capital from the revaluation is accompanied by stock split which results in 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 assess 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 could improve their access to financing or reduce their financing costs. For this purpose, we study a panel of listed companies between 2011 and 2019 for their access to finance, financing cost, investment, and financial leverage, controlling for the firm and year fixed effects. Our results are more consistent with the nominal price reductions causing the market reaction. We do not find evidence of asset revaluations leading to the firm's better access to financing.

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.

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.

Objective: 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? Method: 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. Results: 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.

Objective: We study intraday patterns of trading volume, size, return, and volatility using the Tehran Stock Exchange (TSE) high frequency data from 2008 to 2015. Methods: We first document the intradaily patterns in stock returns, volatility, and trading value and volume. We subsequently examine the insider trading hypothesis by identifying the contribution of large, medium, and small order sizes to price changes. Results: Our results indicate that trading value and volume follow a J-Shaped pattern, whereas absolute return exhibit 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. Conclusion: Our findings are relevant for both policy-makers and traders. From the policy perspective, trading halts imposed by the regulatory body may have implications for trading behavior at the time of market open. Further, traders can use our findings to better understand the intra-daily behavior of the TSE and hence, execute large orders more efficiently.

Objective: 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. Methods: 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. Results: 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. Conclusion: The results show that firm interlock, particularly through cross holdings and common ownership, can increase stock price synchronicity.

Today, most of the world’s inhabitants live in cities [...]

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.

Total Factor Productivity (TFP), as a main resource in providing economic development, has a significant role in increasing competitiveness because one can study the performance rate of economic and industrial sectors in optimal utilisation of productive resources through analysis and calculation of TFP indexes. In Data Envelopment Analysis (DEA), there are different methods for measuring changes in TFP of Decision Making Units (DMU) at different times using different technologies. One of the most important is the Malmquist Productivity Index (MPI). Currently, in many economic and industrial activities namely investment and energy, there are some indexes that transform during different periods (called Carry-Over) and thus affect the performance of a DMU in another period, based on the performance of a DMU in a specific time period. These indexes may vary from time to time, i.e. in one time interval they may be good and in another one they may be bad; this tends to be ignored in the traditional MPI. In this paper, we develop the MPI by considering transforming indexes using a Slack-Based Measure (SBM) model in Variable Returns to Scale (VRS). Finally, we analyse the electricity industry of Iran in two consecutive years. Keywords: Data envelopment analysis, Malmquist productivity index, Carry-over index, Electricity

Objective: This study aims at measuring the effect of added valued of unobserved actions of mutual funds. Methods: Using Return Gap criteria– the difference between the return of hypothetical and actual return – the researchers examined the effect of indiscernible activities in mutual funds throughout seasonal reports. Results: The results showed that unreported activities in mutual funds create just enough value to offset their costs. Conclusion: We studied the unobserved actions of Iranian mutual funds among quarterly disclosure of holdings. We measured the effect of these unobserved actions using return gap – the difference between the return of a hypothetical constant portfolio matching the fund’s beginning of quarter and the fund’s actual return. The results indicated that these actions create just enough value to offset the costs associated with them; hence, the net effect on returns to fund investors is zero. We further documented that the funds are able to create more value through these activities in bull markets.

In this study, we show that ranking fuzzy numbers with the area method using circumcenter of centroids presented by Rao and Shankar failed to rank effectively the generalized fuzzy numbers. By proving a theorem and using some numerical examples, we demonstrate that their proposed method cannot rank consistently some fuzzy numbers or is not consistent with human intuition.

This paper is concerned with the solution procedure of a Transportation Problem in which costs are triangular intuitionistic fuzzy numbers (TIFN) and availabilities and demands are taken as exact numerical values. According to the existing solution approach, TIFN are first ordered by using an accuracy function defined on score functions for membership and non-membership functions of TIFN. Then this ordering is used to develop methods for finding an initial basic feasible solution and the optimal solution of intuitionistic fuzzy Transportation Problems in terms of triangular intuitionistic fuzzy numbers. This solution approach, in spite of its merits, requires a lot of fuzzy arithmetic operations, such as additions and subtractions of TIFN, as well as a lot of comparisons on TIFN. In this paper an efficient computational solution approach is proposed for solving intuitionistic fuzzy Transportation Problems based on classical transportation algorithms to overcome the shortcomings of the aforementioned solution approach. In the approach here presented, the comparison of triangular intuitionistic fuzzy costs is done once and all arithmetic operations are done on real numbers. Finally, for the sake of illustration, two intuitionistic fuzzy Transportation Problems are solved herein to demonstrate the usages and advantages of the proposed solution approach.

The fuzzy primal simplex method proposed by Mahdavi-Amiri et al. and the fuzzy dual simplex method proposed by SH Nasseri and A Ebrahimnejad are two current procedures for solving linear programming problems with fuzzy cost coefficients known as reduced fuzzy numbers linear programming (RFNLP) problems. In this paper, we prove that in the absence of degeneracy these fuzzy methods stop in a finite numbers of iterations. We also prove the fundamental theorem of linear programming in a crisp environment to a fuzzy one. Finally, we illustrate our proof by use of a numerical example.