مطالب

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 .