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EXTENDED ABSTRACT INTRODUCTION Exchange rate is a variable transferring international economic shocks to domestic economy. In countries like Iran which are experiencing a high inflation and whose GDP as well as consumption expenditures are mostly dependent on imports and foreign capital flows, exchange rate changes and its effects need to be carefully monitored by policy makers and economic researchers. Considering the importance of inflation in the theoretical discussions and the high inflation rate in some developing countries, the effect of exchange rate on inflation has attracted economists interested in monetary issues and international economics.Nonlinear behavior in the exchange rate effect on inflation can provide false estimates of exchange rate coefficient when the econometric model is estimated linearly. In such a circumstance, we can accommodate cases when the inflation condition and its rate affect economic factors in response to an exchange rate shock. Indeed, domestic prices may not be sensitive to an exchange rate shock due to a low and stable inflation. However, they may respond wildly to a similar shock when inflation is above some significant thresholds.Although studies have mostly focused on measuring the extent of exchange rate effect on price levels, we believet that investigating the possible existence of one or more thresholds in exchange rate effect is important, because the reaction of monetary policymakers may somehow depend on the extent of exchange rate effect with respect to one (or more) threshold value(s). For instance, policymakers might not take care of the exchange rate fluctuations below a certain level, but as soon as it crosses such a level, they believe it damages the economy and the country welfare, thus triggering some intervention in the currency market. METHODOLOGY A reason for the non-linear response of inflation is the non-linear nature of exchange rate trend. In fact, geometrically, among all the time paths of exchange rate, the probability of a linear path between the two time points is very weak. The effect consequence of all determinants of the exchange rate is displayed in its changes. Here are two important points to note. First, the cross-effects of exchange rate determinants can influence the impact of each determinant. Second, the importance of currency, especially in developing countries, and its key role between the foreign exchange and financial markets, has made the exchange rate an intelligent variable, which corrects mistakes at the next rate through the learning process. Hence, the course of exchange rate over time is expected to be nonlinear.The purpose of the present paper is to the test a nonlinear model estimating the response of inflation to real effective exchange rate in Iran. In order to examine threshold effects of exchange rate on inflation in Iran, following Posedel & Tica (2009), pattern was used:where inflation π is a function of the Real Effective Exchange Rate (REER). The variable  is a dummy variable:  if the REER () is equal or bigger than the threshold () and  if the REER () is smaller than threshold (). FINDINGS Finding based on time series data for the period 1971-2017 and Threshold Regression (TR) model indicates that real effective exchange rate of 6160.27 Rials has been applied as a threshold value. In other words, based on the above threshold value, the estimated model shows the exchange rate coefficient has increased somewhat from the first to the second regime.CONCLUSION Considering the fact that preserving the value of the national currency is one of the most important tasks of central banks and to control inflation, it seems necessary to give the due attention to exchange rate and its threshold impacts when planning, designing and implementing monetary and exchange policies. The results of this study suggests a policy guideline, namely, that, in order to limit the damaging effects of inflation on the economy and household welfare, monetary policymakers in Iran must restrain the foreign exchange shocks.

EXTENDED ABSTRACT INTRODUCTIONIn 2019, Iran is ranked sixth among world countries and fifth among Asian countries (including Russia) in terms of CO2 emissions. Therefore, studying the CO2 emission elasticity of the production sectors of this country is significant and important for energy and environmental policymakers. What factors influence changes in CO2 emission elasticities? Which are the stimulants and which are the inhibators? The answers to these questions are useful in reducing and controlling CO2 emissions. In the present study, CO2 emission elasticities of production sectors are calculated, and then, with the aim of identifying CO2 emission elasticity stimuli, the changes in CO2 emission elasticities are broken down into different components. The methodology of this research is based on Input-Output analysis and decomposition analysis. The novelty of this paper is to determine and calculate the components of changes in CO2 emission elasticities using SAD. Guo et al. (2018) have presented a method for calculating CO2 emission elasticities based on the Input-Output analysis.METHODOLOGY Aim of this paper is to investigate the factors affecting CO2 emission elasticities, CO2 emission demand elasticity and CO2 emission production elasticity. In the first step, the elasticities are calculated and in the second step, changes of elasticities are decomposed. In this study, we have used input-output tables published in 2001 and 2011 by the Statistics Center of Iran. Due to the differences in the sector classification of the input-output tables of 2001 and 2011, we match some production sectors and finally take into account the 65 unified sectors. In order to calculate the CO2 emission of each production sector, we first obtain the total consumption of each energy for each year from the Iranian energy balance sheet, and then we allocate each energy consumption to production sectors and single household sector, according to input-output tables and the share of production sectors and the share of the household sector.                                                                                                                                                                                                                                                                   FINDINGS Findings show that the "Electricity generation, transmission, and distribution" sector has the most elasticity. The "Ghosh inverse matrix" effect is a strong stimulus to the CO2 emission elasticity of the sectors. This result indicates that the change in the share of output i, which is sold to sector j as an intermediate input, is a strong stimulus to increase the elasticity of CO2 emissions. These changes can be due to increased economic activities and the inefficiency of production structure.   CONCLUSION "Electricity generation, transmission and distribution" sector should be considered by energy and environmental policy makers due to having the highest amount and changes in CO2 emission elasticity than other sectors. Increasing the share of renewable energy in the energy consumption basket of production sectors, increasing energy efficiency (reducing energy intensity) by replacing new and advanced equipment with old and worn equipment and improving production structure can help reduce the CO2 elasticity and CO2 emission in Iran's production sectors. Finally, due to the high of CO2 emission elasticities in the "Electricity generation, transmission and distribution" sector, future research can focus on this area and suggest solutions to increase production efficiency and energy efficiency. Also, future research can focus on the production structure of production sectors and provide solutions to improve the production structure of Iran's production sectors.

Researchers examined anomalies in the market to understand the market dimensions. Prior studies considered the effects of biases on momentum strategy. Stock liquidity as one of the risk factors for assets was also considered by researchers. The purpose of this study is to examine the role of stock liquidity in the separately and jointly effect of anchoring bias and the disposition effect on momentum profit. The population of this study consists of all companies listed on the Tehran Stock Exchange. Based on systematic election sampling this study covers 136 companies over the period of 2007-2020. In this study, the effect of disposition effect is calculated using the approach of Greenblatt and Han (2005) and Frazzini (2006) and the anchorage bias is calculated according to George and Hwang (2004). This study calculates momentum profits according to Jegadeesh and Titman (1993). To test the hypotheses, multivariate regressions and the five-factor model of Fama and French (2015) have been used. The results of this study show that the disposition effect in stocks with low liquidity increases momentum profit. In addition, anchoring bias in stocks with low liquidity leads to an increase the momentum profit. Findings of this study document that the interaction effect of anchoring bias and disposition effect, while reinforcing each other, is also associated with increasing in momentum profit. Finally, when anchoring bias and disposition effect reinforce each other, and stocks have low liquidity, they do not increase momentum profits.

Sustainability reporting is an important tool for decreasing information asymmetry, according to the stakeholders' demands for transparency. On the other hand, increasing transparency allows investors to have more appropriate evaluations of firms' activities and direct their investments to companies with more enthusiasm. In the organizational context, information asymmetry creates conflict between owners and managers. Managers tend to reduce the gap between themselves and stakeholders, particularly shareholders, by producing and delivering reports. Companies use sustainability reports to connect with their society and environment, as well as a way to manage interactions with various stakeholders for societal approval and activity continuation. The primary purpose of this study is to provide a model for measuring the quality of sustainability reporting and the determinants. In terms of methodology, the current study is qualitative, deductive, cross-sectional, applied, and exploratory. The criteria were identified and extracted, then evaluated and prioritized using Multi-Criteria Decision-Making approaches including Fuzzy Analytic Hierarchy Process and Fuzzy Decision-Making Trial and Evaluation Laboratory Analytic Network Process-based. The FAHP test revealed that of the six indicators, the GRI's reporting guidelines for sustainability Checklist were placed highest. Internal Controls Reporting, Sustainability Innovation Performance, and Earnings Quality rated first to third, respectively, among the 25 criteria affecting the quality of sustainability reporting, according to the FDANP.

Given the lack of a specific approach to the explanation of values of optimal portfolio weights in the portfolio optimization, the present study aimed to examine large-scale portfolio optimization according to both stock weighting and utilization of SCAD function to minimize the portfolio risk based on the "weight-modified conditional value at risk (CVaR)" and its comparison with the "conditional value at risk (CVaR)" method in the Tehran Stock Exchange. Therefore, the price information of companies listed in the Tehran Stock Exchange and Over-the-counter (OTC) from 2012 to the end of September 2020 was collected, screened, and analyzed daily, and then the risk and return of the portfolios were examined by forming optimal portfolios. The results indicated that the efficiency limit of the stock portfolio and also the ranks of different companies were different according to the types of the optimization method. Based on the behavior of the TEDPIX, the investors' degrees of risk-taking, and the risk management, diversification, and computational complexity of each method, the weight-modified CVaR had a better performance due to better diversification and risk management. Furthermore, the SCAD function added computational complexity to this method .

The oil market is affected by the supply of oil by oil-producing countries. The Organization of the Petroleum Exporting Countries (OPEC) was established in the 1960s to balance oil prices in favor of oil-producing countries. OPEC has gone through a period of convergence and divergence since its inception under political-economic events and crises. In turn, this convergence and divergence have had a significant impact on oil production, supply, and prices in the oil market. OPEC members form a diverse range of population, size, reserves, output, gross domestic product, ideology, and type of relationship with world powers. This diversity, along with internal tensions, leads to different approaches on energy markets and production quotas, which has affected the interests of all producing countries. Thus, this study aims to assess the convergence relationship between OPEC members on the strength of this organization on the market. To reach this aim, we have used a qualitative method of descriptive and analytical type using library resources and documents. Findings show that any lack of convergence and understanding between OPEC members has led to increased supply in the oil market and fluctuating prices. These price fluctuations seriously damage the economies of exporting countries.