درخت حوزه‌های تخصصی

Earning is one of the most important items of financial statements. Sometimes managers manipulate and distort earning reports to maximize their own benefits, reach a certain profitability level, or achieve a certain corporate objective. Firms with a low level of debt tend to have few or no restrictive clauses in their debt contracts, which allow them to operate with less concern about breaching these contracts and give less incentive to managers to engage in earning management reports through accrual manipulation. However, when firms accumulate large amounts of debt, the relationship between debt and accrual-based earnings management tends to get reversed. In firms with large debts, managers are incentivized to report good earnings as they are under pressure to avoid the penalties of violating the restrictive clauses in their debt contracts. In the absence of scientific and empirical evidence regarding this issue, the present study examined the nonlinear relationship between debt structure and real and accrual-based earnings management. For this purpose, the data pertaining to a sample of 130 firms listed on the Tehran stock exchange from 2014 to 2019 were collected and analyzed. The results of multivariate regression analysis showed a nonlinear relationship between debt structure and accrual-based earnings management. A non-linear relationship was also found between current debt structure and real earnings management. However, the results could not confirm the presence of a non-linear relationship between total debt structure and real earnings management

According to the literature, macroeconomic variables have significant effects on financial markets. In addition to investors and traders in these markets, researchers have also paid special attention and sensitivity to these changes. The purpose of this study is to investigate the macro-structural determinants affecting the price index of the Tehran Stock Exchange in the period 1991-2019. To this purpose, the fully modified ordinary least squares estimator (FMOLS) and the Hudrick Prescott filter (HP) were used. Based on the estimation results of the econometric model, economic growth, government budget deficit, and exchange rate have had positive and significant effects on the total price index of the Tehran Stock Exchange, while negative effects on money supply (liquidity) and oil revenue uncertainty index (extracted by HP filter). Economic growth has had a significant effect on the total price index of the Tehran Stock Exchange resulting in negative returns. JEL Classification: G12, C50, C22, E44

Purpose: The purpose of this research was to present a customer experience management model in five-star hotels. Method: In this research, the researcher has used a database approach , and in the first study, he used the database approach based on the Ostrous approach to identify the components of the research. The tool used for collecting the required data in the first study, the protocol and in-depth interviews with five-star hotel managers and its customers in the country has been purposefully chosen and analyzed. Findings: the researcher conducted fifteen interviews in theoretical literature, and also has done axial and selective coding and then presented the results in the form of six main dimensions. Conclusion: The researcher has presented his research in the form of a model including six main dimensions, verbal advertising, service quality, new norms, customer service, event marketing, customer experience and thirty three sub-dimensions. Research findings show that improving the customer experience is the main objective for many people who work in hotels and hospitality industries.

The research on the Markowitz model and optimization of its portfolio using a variety of evaluation indicators and meta-beta-algorithms has always been the focus of attention of accounting and finance researchers. The results of studies carried out by various types of optimization methods are different in the Markowitz modified models. The purpose of this study is to measure the optimal portfolio and its corresponding return, with respect to the portfolio in the traditional Markowitz model, as well as to compare the position of the refining and petrochemical companies versus stock market outperformers, through integrating the operational criteria and the new indicators of liquidity using the genetic algorithm in the Markowitz model. Therefore, financial data related to the research variables for 35 cases of TSE-listed refinery and petrochemical companies from 2012 to 2016 fiscal years were extracted from Rahavard Novin database software and simulated by the genetic algorithm. The results show that returns on the stock portfolio optimized using the genetic algorithm and without considering the liquidity limitations and filters have a significant and positive difference with the return on the stock portfolios optimized with regard to the liquidity limitations and filters. Furthermore, the application of liquidity limitations and filters in the formation of optimal stock portfolios leads to a conservative increase in the choice of stocks (portfolio formation), which leads to a reduction in the risk and return of investment in such portfolios.

This study aims at getting a better performance for optimal stock portfolios by modeling stocks prices dynamics through a continuous paths Levy process. To this end, the share prices are simulated using a multi-dimensional geometric Brownian motion model. Then, we use the results to form the optimal portfolio by maximizing the Sharpe ratio and comparing the findings with the outputs of the conventional model. To examine the robustness of the results, we have evaluated its performance for different investment horizons and various volumes of price information over a long period (approximately twenty years) in the Tehran Stock Exchange (TSE). Findings indicate that within the trading dates spanning the interval 24-Mar-2001 to 19-Sep-2020, the return of the portfolios obtained from applying this simulation scheme for maximization of Sharpe ratio is (244% on average) higher and their risk (standard deviation) are lower (1227% on average) than those realized by the conventional methods. Additionally, a comparison of the simulation approach with a performance of the actual market portfolios indicates that the Sharpe ratios of the simulation method are higher (0.055% on average) than those resulting from the total market performances. The results of the stochastic dominance test show that our proposed strategy has a first-order stochastic dominance (FSD) over the conventional one and market portfolios, that means at each level of cumulative distribution, the Sharpe ratio of our method is higher, and as FSD test makes no assumptions about the curvature of investors' utility functions, these results do not depend on the degree of risk aversion of investors, and as long as investors prefer a higher Sharpe ratio, they would be better off if they follow our proposed strategy.