International Journal of Finance and Managerial Accounting
Volume:5 Issue: 20, Winter 2021

The purpose of this research is to develop an behavioral agency model by focusing on the moderating role of corporate social responsibility on the relationship between CEO risk incentives and corporate idiosyncratic risk. The main. This research has been carried out using annual data of companies accepted in Tehran Stock Exchange during the period of 2012-2018. For testing of research hypotheses, multivariate linear regression has been used based on panel data. Empirical results show that CEO risk incentives has a positive and significant effect on firm idiosyncratic risk only in low CSR firms that attempt to maximize only investing stakeholders’ interests. In high CSR firms, that attempt to balance the interests of both investing and non-investing stakeholders, CEO risk incentives has no effect on firm idiosyncratic risk. The findings of our paper contribute to enrich the corporate social responsibility /CEO risk incentives literature, and provide academics and managers a clearer understanding of the effect brought about by the corporate social responsibility and CEO risk incentives on corporate idiosyncratic risk.

In recent years, with the governance of behavioral finance paradigm and the standard national theories being challenged, due to their disability in explaining the observed anomalies in the capital market, financial researches have entered into a new intellectual era and in some of the researches, assumptions of modern financial economics have been challenged. One of these assumptions is the assumption that investors are logical and this is seriously challenged and several studies have been devoted to this issue. The purpose of this study is to investigate the effect of fundamental variables on the formation of herding behavior in the Iranian capital market. Experimental findings of the investigation of 110 companies listed on the Tehran Stock Exchange from 2009 to 2019 shows the formation of herding behavior in the Iranian capital market. The results of the present study also confirm that there is a positive and significant relationship between changes in the fundamental variables of accounting (changes in stock returns, changes in assets, changes in sales) and the formation of herding behavior in the Iranian capital market. Analyzing these results, it can be stated that changes in fundamental variables lead to the formation of unintentional herding behavior in the Iranian capital market.

Stock price crash have been described as a severe negative event in stock returns, causing major losses in shareholders' wealth and a loss of confidence in the capital market. This study sought to investigate the stock price crash risk of 114 companies listed on Tehran Stock Exchange within the years 2009 to 2018 on the basis of Bradshaw et al EXTR-SIGMA (2010) and Chen et al. NCSKEW (2001) criterion. Accordingly, the researcher first calculated the stock prices crash risk based on two different criterion and then tested the internal and external factors of the company on crash risk. The statistical model used in this study encompassed regression model and the data type is panel data type. Based on the findings of the present study, there is a significant relationship between the dependent variables (the first and the second criteria for calculating and predicting stock price crash), the factors within the company (company features and financial ratios) and external factors such as dollar market price, volume of shares traded, Iranian oil price and global gold price.

Tenured And Possessive Behavioral words are in the area of financial theories that is in line with the theory of representation, it seeks to narrow the gap of interest between shareholders and investors and guide the company's decisions to maximize shareholder interest, it seeks to narrow the gap of interest between shareholders and investors and guide the company's decisions to maximize shareholder interest. The purpose of this research is the effect of managerial entrenchment of bias overconfidence in companies listed in Tehran Stock Exchange. In this study, 111 Tehran Stock Exchange companies were studied in the period of 2013 to 2017. In this research, in order to measure the managerial entrenchment three criteria were used CEO tenure; Managerial ownership and DUAL And bias overconfidence were measured by two criteria overconfidence-excess capacity and excess debt capacity investment. The results showed a significant positive effect managerial entrenchment On Both overconfidence measure of excess capacity and excess debt capacity investment.

The nature of each investment is not something but to make more profit and more returns for investors. Accordingly, shareholders always seek to control the potential risks of investment through better market intelligence. Nevertheless, excess stock returns volatility caused by impairment in predicting expected returns do not allow investor perceptions in a market to be unified, and most decisions will be affected by emotions even at higher horizons. The purpose of this research is to investigate the effect of excess stock returns volatility on heterogeneous perceptions of investors with the mediating role of investment horizons. The statistical population of the research is the companies listed at the Tehran Stock Exchange. By systematic elimination sampling, 89 companies were selected as the sample that was studied during the period 2013 to 2017. In this research, due to the dummy nature of the dependent variable, logistic regression was used to test the research hypotheses. The results showed that the effect of excess stock returns volatility on investors’ heterogeneous perceptions is positive and significant. It was also found that investment horizons exacerbated the positive impact of excess stock returns volatility on investors’ heterogeneous perceptions.

This study aimed to propose a prescriptive model of environmental reporting in Iran. The model was developed through exploratory research and a qualitative approach using the grounded theory method. The research population included experts in the fields of accounting, environment, natural resources, and law. The snowball sampling method was used to select the respondents for the interviews. After analyzing the data, a model for environmental management information disclosure requirements in financial reporting was developed. The results indicated that environmental laws (measurement and reporting requirement) were classified as causal conditions, international financial reporting standards(IFRS)as underlying conditions, and sustainability reporting standards and acquisition of competitive advantages (adhering to accountability and gaining legitimacy) as intervening conditions. Model strategies include reporting quantitative and qualitative environmental information in the value chain in the form of a board report to the assembly, explanatory notes, and defining a new financial statement. Furthermore, acquiring the component of national power (preserving scarce and non-renewable resources, preventing destructive and polluting activities, maintaining public health, establishing environmental justice among different generations and communities, preventing corruption and rentier capitalism, and achieving sustainable development) and facilitating international political and economic relations, assessing the continuity of corporate activity and public supervision, and reducing information asymmetry were identified as the implications of the developed model.

The Black-Scholes model assumes that the price of the underlying asset follows a geometric Brownian motion. This assumption has two implications: first, log-returns over any horizon are normally distributed with constant volatility σ and the second, stock price evolution is continuous, therefore, there is no market gaps. These conditions are commonly violated in practice: empirical returns typically exhibit fatter tails than a normal distribution, volatility is not constant over time, and markets do sometimes gap. The existence of volatility skew will misprice options price. Derived from these flaws, a number of models have proposed. In this paper we will analyze, simulate and compare two most important models which have widespread using: jump diffusion model and stochastic volatility model. Each of the aforementioned models have programmed in MATLAB and Python, then their results have been compared together in order to provide a robust understanding of each of them. Our results show that in comparison to Black-Scholes model these two models yield better performance.

Traditional financial theories describe investors as rationalist entities but the speculations experienced cannot be explained by existing theories. Behavioral finance argues that individual investors do not make rational financial decisions and that they are affected by their prejudices while making financial decisions. The aim of this study is to identify the components that effect on financial behavior of investors. Delphi was used to achieve the research goal. In this method, the financial and behavioral components of investors were examined by asking questions among the qualitative researches. To achieve the goal of the research, after reviewing the literature in both domestic and foreign domains, a semi-structured interview was conducted with experts using Delphi method and the components affecting investors' financial behavioral fluctuations in four Delphi periods were identified such as optimistic behavior, overconfidence behavior, risk aversion behavior and emotional behavior. In this study, we tried to use Delphi's approach to gain better knowledge and finally for dimension with forty components were introduced.

Abstract One of the main issues in the prediction of financial constraints is the choice of predictor variables. In this study we used machine learning Gussian process and radial neural network to predict the financial constraints. The statistical society consists of 208 companies from 2011 to 2017 and considering the availability of the information all the companies were analyzed as the statistical samples. The results of this study show that machine learning methods can predict the financial constraints of the companies listed on Tehran’s stock exchange. Therefore the main hypothesis of this study is confirmed and machine learning methods are an effective method to predict the financial constraints. Also the results of this study show that the value of the company, the ratio of operating cash to assets, financial leverage, return on assets and the percentage of institutional owners are the main variables in predicting the financial constraints. Key words: financial constraint, machine learning method, radial neural network, Gussian process regression

In behavioral finance and economics; the role of natural reactions of (not necessarily rational) human behaviors as an influencing variable on other economic and financial variables (which has not been considered in the past) is studied with further emphasized.The main issue is the existence of various behavioral biases in the decision making pro-cesses and selection of banking network in financial markets. Delphi and Excellence method test for data collection. In this research, we used a grounded theory approach initially based on data gathering through interviews with 74 experts, taking field notes, participatory obser-vation, documentation, abstract events, data generation, data analysis with a systematic ap-proach, open coding, axial coding, selective coding, and finally, after evaluating the model's validation with the approval of 222 subject matter experts, the model is presented with four dimensions and 20 categories and 239 features. Behavioral Finance for Private Banking: From the Art of Advice to the Science of Advice’ is nonetheless a far-reaching architecture for client-centric bespoke private wealth management, entailing a symbiosis of behavioral finance and private banking, handling state-of-the-art domains of FinTech and neuroscience.

The Purpose of this Paper to examine the effect of firm financial constraint indexes on the risks associated with the excess cash holdings, considering the Stock Trading Continuity Index. In this study, two criteria for liquidity risk are used to measure risk, which include twelve-month liquidity risk and beta liquidity risk. Also in this research, multivariate regression and ordinary least squares method are used in order to test the hypotheses. The research sample includes 130 companies of listed companies in Tehran Stock Exchange that is seven-year period from the beginning of 2011 until the end of 2017. The research results show that financial constraints due to the size of the company, pay-out ratio, and the WW index of Whited Wu affects the relationship between liquidity risk and excess cash holdings and improvement of the stock trading continuity associated with excess cash holding is greater for financially constraint firms. But the amount of the cash coefficient for the KZ Index of Kaplan Zingales is almost the same for the constrained and unconstrained firms. Overall, the results show that the liquidity risk reduction associated with the excess cash holdings is greater for financially constraints firms.

The excessive attention of various institutions on the world of business to social responsibility has made it a necessary element for the success of companies. Due to the lack of firm ranking in this field, as well as experimental research and studies on its relationship with financial performance criteria, it is not yet fully defined in the literature and the results are different, therefore, in this paper, an attempt has been made to explain the disclosure and ranking of companies based on the Vigeo model of social responsibility and its relationship with the financial performance criteria of 118 companies during the years 2008 to 2018. To measure the social responsibility indicators of the Vigeo model, content analysis method and indicators such as return on assets, return on equity, return on invested capital, return on sales and Tobin’s Q were used as criteria for financial performance. The results indicate that the highest disclosure of indicators in the corporate governance dimension and the lowest in the human rights dimension and in general, the level of disclosure of indicators in sample companies is very low. Also, our findings show that the responsibility of companies based on Vigeo's social responsibility is positively related to the variable of return on assets, return on sales and return on invested capital and negatively on the return on equity and Tobin’s Q. Among the performance criteria, return on assets were the highest and Tobin’s Q had the lowest correlation with the corporate social responsibility of the Vigeo model.