International Journal of Finance and Managerial Accounting
Volume:4 Issue: 14, Summer 2019

Given the widespread and deep economic-social consequences of accounting fraud in micro and macro levels of society and the effectiveness of whistleblowing in their discovery and the effect of demographic characteristics on moral behavior as whistleblowing, this study aimed to examine the whistleblowing intentions for accounting fraud including account manipulation and embezzlement based on demographic individual differences, which are important factors in employment, role-playing and job promotion. The statistical population consisted of accounting staff in private and public sectors and the sample size with random distribution was 596. The data collection tools were questionnaire and exclusive scenarios for accounting fraud. The research method was comparative and correlational in nature. The results showed that at the level of 95% there was a significant difference in the whistleblowing intentions for two types of fraud in terms of gender, age and experience and there was no significant difference in terms of educational level.

Fiscal policy is a policy that tries to achieve certain economic goals through instruments such as changes in government expenditure and taxation. The financial policy uses two instruments of government revenue (tax) and government spending (spending) to influence the economy. And in the economic literature, they consider economic growth to be equal to GDP. The impact of financial policies on economic growth is a matter of many economists. The source of finance used by the government of majority of the world countries is mainly tax revenue. Tax paid by the public is an effective instrument for developing financial policy by the nations. This study aims to investigate the impact of financial policy (tax) on GDP of the developed and developing countries using the panel data technique. The data is collected from World Bank database for the period 2008-2016. The results of analysis revealed that there is a negative and significant relationship between the logarithm of the ratio of tax revenues and GDP in the developed countries; however, there is no significant relationship between tax revenues and economic growth in developing countries.

This study provides an empirical evidence on how Corporate Sustainability Performance (CSP), is reflected in the corporate value. Using a theoretical framework combining Legitimacy theory, Stakeholder theory and Agency theory, a set of hypotheses that relate the corporate value to CSP is examined. For a sample of Iranian firms, 28 components with four dimensions as Community, Environment, Employees and Governance are measured in terms of sustainability. Also to assess the corporate value as dependent variable, Q-Tobin index is used. The results show that corporate sustainability performance and its dimensions, unlike the theoretical principles and dominant theories presented in this regard, have significant inverse relationships with the corporate value at 95 percent confidence level. Such a finding amongst the Iranian companies, does not seem to be strange and unreal; because the concept of corporate sustainability is very unfamiliar and strange among senior Iranian managers of organizations, and often due to state ownership and lack of need to create a positive mindset among their customers, Iranian organizations show little interest for employing corporate sustainability principles. This study supports managers to develop effective policies related to CSP that is necessary to increase the value of corporations.

The main objective of this research is to optimize the stock portfolio of investment companies operating in the field of petrochemical and refining industries through minimizing risk with respect to the expected return. In this regard, first of all, the compositions of sample firm's portfolios were investigated during 2013 to 2016 and high-weight industries were selected. Then, the risk of return on each selected industry over time was estimated using the multivariate GARCH model in form of Diagonal BEKK method. Further, considering the expected returns, the optimal risk was calculated for each portfolio. Then, the effective factors on portfolio risk-return such as the currency rate, crude oil price, and stock liquidity risk of the selected industries, was token into accounts and the above steps were repeated and the risk of optimized portfolios was recalculated. Findings of the research show that the optimized portfolios have been more optimized by considering effective factors, and whenever there was a lower risk in each of the industries, the corresponding weights have been higher. Also, most portfolios are made up of industries such as the petroleum products, chemicals, rubber and plastics. Therefore, it is appropriate for investment companies to consider the prioritization of industries and the factors affecting risk and return in order to minimize the risk of their stock portfolios at any time, as well as gaining higher expected returns.

Portfolio selection process is a subject focused by many researchers. Various criteria involved in this process have undergone alterations over time, necessitating the use of appropriate investment decision support tools. An optimization approach used in different sciences is using meta-heuristic algorithms. In the present study, using Water Cycle Algorithm (WCA), a model was introduced for selecting the optimal portfolio, and then the obtained results were compared with those obtained from Harmony Search (HS) and Imperialist Competitive Algorithm (ICA). For this purpose, using the data of 10-month (April 2016 to January 2017) returns of 50 top companies in the Stock Exchange Market of Iran, the optimal portfolio was estimated using the above-mentioned algorithms with the aim of maximizing profit and minimizing risk, and then the optimal portfolios obtained from these algorithms were compared with each other. Results of implementing these algorithms indicated that despite the high capability of the studied algorithms to optimize the portfolios, WCA algorithm had higher capability of portfolio optimization than the other ones

The purpose of this paper is the empirically examination of the effect of the Institutional Quality Components (Voice and Accountability, political stability and Absence of Violence and Terrorism, government effectiveness, regulatory quality, rule of law and control of corruption) on the prediction of total stock price index. The study was carried out using data extracted from 53 countries from the World Bank and Thomson Data Stream website over a period of 15 years between 2002 and 2016. The results of this study in various countries surveyed showed that the components of institutional quality have a positive and significant effect on the total stock price index. The results show that, as the institutional quality of the countries improves, the stock price index will increase. The results also indicate that identifying the institutional weaknesses in developing and developed countries would be a pathway to improve the investment in the capital markets.

The heavy tailed distributions have mostly been used for modeling the financial data. The kappa distribution has higher peak and heavier tail than the normal distribution. In this paper, we consider the estimation of the three unknown parameters of a Kappa distribution for evaluating the value at risk measure. The value at risk (VaR) as a quantile of a distribution is one of the important criteria for financial institution risk management. The maximum likelihood, moment, percentiles and maximum product of spacing methods are considered to estimate the unknown parameters. The data of the insurance stock prices is analyzed for comparing the proposed methods in VaR evaluation. An important implication of the present study is that the Kappa distribution can be considered as a loss distribution for the VaR estimation. Also, it is observed that the maximum likelihood estimator, in contrast to other estimators, provides smallest VaR in the proposed stock prices data.

An information usefulness approach to decision making points out that only the information is regarded as useful that will bring valuable messages to investors and lead to stock price adjustments. This study examines the effectiveness of audit committees in improving earnings quality and informativeness, particularly among family-owned firms. Earnings informativeness was measured through the relationship between accounting earnings and cumulative abnormal stock returns (CAR). In addition, the characteristics of the audit committee include independence, size, and financial expertise. The sample under study included 138 firms listed in the Tehran Stock Exchange over the period from 2011 to 2017. The research hypotheses were tested using statistical analysis techniques including the panel data method and linear regression model in Eviews software. Besides, the Chow test was used to determine if the mixed data would be more efficient for estimating the desired function, and Fisher's statistic was used to examine the significance of the regression model. Also, Student's t-test was employed to examine the significance of the coefficients of the explanatory variables in the regression model and Durbin-Watson's test we run to check the non-autocorrelation assumption of the model residuals. The results showed that the characteristics of the audit committee increase earnings informativeness. Also, the characteristics of the audit committee do not affect the relationship between family ownership and earnings informativeness

The main purpose of this research is portfolio optimization in Tehran securities exchange using the black hole algorithm and the Gravitational Research algorithm. We also propose an algorithm named Hybrid Algorithm which combines the two algorithms above to cover the weaknesses of these two algorithms. Finally we compare the results with the Markowitz model and choose the optimal algorithm. In order to analyze the data that is the same information extracted from the TSE Client software and RahAvard Novin Software, MATLAB software version of 2016and GAMS and SPSS have been used. This research is fulfilled in the period from 2011 to 2016. The method used in this study is based on the purpose of the applied research and based on the way of data collection as a descriptive research and correlation type, which is noticed with the retrospective and post-event approach and through the analysis of the observed information, attempts to optimize the portfolio using a black hole algorithm. In all the years of research, the hybrid method introduced in this research has obtained the nearest solution to the exact solution, which is the same Markowitz. In order to optimize the portfolio, black hole meta-heuristic algorithms, Gravitational Research and hybrid algorithm (hybrid) can be used instead of the Markowitz algorithm with higher accuracy and speed. The results of the present case study and other studies show that black hole algorithms, Gravitational Research, and hybrid algorithms are very quick in solving portfolio optimization problems