JOURNAL OF FINANCIAL MANAGEMENT STRATEGY
Year:2019 | Volume:7 | Issue:25|Papers Count:8

Today, Multi-Criteria Decision Making (MCDM) is an integral part of Operations Research and gained a prominent position within the field as a result of significant theoretical and practical developments during the past four decades. In recent years, Multi-Criteria Sorting Problems (MCSP) has become an interesting topic for researchers who are working in MCDM. It consists of developing different decision models in order to assign alternatives to predefined groups. Amongst the suggested approaches for such classification, ELECTRE-TRI is considered to be one of the most important ones. The aim of this study is to implement ELECTRE-TRI in stock portfolio selection as one of the most popular and important decision making subjects. In this research, eight attributes have been taken into account in the process of choosing the stocks. These attributes are return, beta, net profit margin, ROA, ROE, EPS, P/E and P/BV. The study indicates that among the various approaches of ELECTRE-TRI, pessimistic assignment without considering veto threshold provides the best result. This study also indicates the importance of P/E in stock portfolio selection.

These days, financing for startups is one of paramount challenges for entrepreneurs. Also, because of the risk of venture investments, financial institutions and banks often tend to be less willing to invest in these activities. Moreover, with the advent of social network and virtual communities, fundraising through crowdfunding is one of the new ways of attracting retail investors to finance for risky projects particularly startups. Therefore, estimating the required financial investment and consequently valuing startups are of crucial importance. This article introduces valuation methods for startups that are willing to finance through crowdfunding. In this article, according to the characteristics and the nature of the startups, two methods of Discounted Cash Flow in the income-driven approach and Black Scholes in the Real Option Valuation approach have been distinguished suitable to finance for a startup through crowdfunding. Comparing the results of these approaches, we can validate obtained valuation results. The proximity of the results of the two methods suggests an appropriate estimation of the value of the project under study.

If startups are considered as a mechanism for finding superior ideas, an important factor for entering innovation is finding an investor for superior ideas. Hence, the purpose of this research is to identify, prioritize and determine the Cause-and-Effect relationship between the factors affecting start-up financing. In this regard, the decision group includes managers and experts involved in Startups establishment, knowledgebased companies, as well as present companies in Golestan province science and technology parks which include ٣ ٠ people. Factors affecting the financing of startups, at first six components with sub-criteria have been identified and extracted by the Fuzzy Delphi Technique. In the following, in addition to prioritizing the components, the Cause-and-Effect relationship between the main components, that are effective in financing startups, has been determined using DEMATEL Technique. Finally, of the six main components in financing these firms, four present risk factors in the idea, the market characteristic, the feature of idea and the financial characteristic have been identified as the cause and two factors of the legal characteristic and features of the infrastructure along with the subset of each of them, have been identified as an effect in Startup financing, respectively. These factors are very vital for investors` startups.

One of the occasions when management incentives for earning management are triggered is the initial public offering. Due to the high information asymmetry in the IPO, the management of exposed companies is trying to provide a more favorable image than the company by incremental earnings management. The purpose of this study is to explain the effect of initial public offerings on Discretionary accruals earning management. In order to reach this goal, ١ ٤ ٠ ٨ year-company (١ ٢ ٨ companies for eleven years) viewed and collected from the annual financial reports of companies listed in Tehran Stock Exchange were tested, during the period from ٢ ٠ ٠ ٦ to ٢ ٠ ١ ٦ . The findings of the research show that earnings management through accrual items has a positive and significant relationship with initial stock offerings. Further analysis shows that earnings management through accrual items is more than the year before the initial stock offerings, while earnings management through accrual items is lower in the year after the initial stock offerings than the initial stock offerings year.

The study of factors affecting the risk and returns of stock is of great importance in financial studies and is considered as a powerful concept in investment strategies and decisions. Therefore, in recent years, in the form of empirical research, the identification of internal and external factors (macroeconomic) on risk and stock returns have been investigated. In this regard, macroeconomic variables are more important. In this research, among different macroeconomic variables, the effect of oil and currency shocks on systematic risk and stock returns has been investigated. Data were used seasonally between ٢ ٠ ٠ ٢ and ٢ ٠ ١ ٦ , which was used to analyze the financial variables against oil shocks and currency using the DSGE model. The results of the research show that oil and currency shock initially have a negative effect on the systematic risk of stock and price returns, and then in the subsequent periods of this trend, they continue to fluctuate in a balanced and stable state, so that the systematic risk fluctuations are greater than price return. Also, the Iranian economy shows the relative success of the model in the realities of the Iranian economy which is determined by comparing the moments of the variables present in the model and the moments of the actual data.

In this study, in order to evaluate sustainable performance of banks, a framework on the basis of multi-attribute utility approach presented by Rebai et al. (٢ ٠ ١ ٢ ) has been employed, and effort has been made to assess the performance of banks from the perspective of different stakeholders, taking into account their various criteria. From this standpoint, a sustainable bank is one that can achieve a certain level of general satisfaction for all its clients and stakeholders. Two basic questions have been answered in this research: "how is the performance of the banks under study appraised on the basis of the criteria intended by each of the stakeholders? " and “ how is the sustainable performance of banks in question according to multi-attribute utility approach? ". To evaluate bank performance, four groups of stakeholders, namely regulators, shareholders, customers and managers-employees have been identified. In the beginning a single-attribute utility function is defined for each of the employed subcriteria. Then, a multi-attribute utility function is obtained for each main criterion. Next, a general utility function is defined for each stakeholder. A marginal score between zero and one is obtained for each stakeholder that shows the quality of performance with respect to the group criteria. In this research, banks are labeled from A to F. Among the banks, bank A was found to be the most sustainable Iranian banks, and banks B-F were in the second to the sixth places, respectively. The results indicate that privatized banks under article ٤ ٤ are more sustainable compared to privately established banks.

This research in a hybrid approach, using Recurrent Neural Networks (RNN) based on Artificial Bee Colony algorithm (ABC), is going to provide the optimal model to predict the stock prices in Tehran Stock Exchange. For this purpose, using the stock datafor companies listed in the first market of the Tehran Stock Exchange, traded between 􀋻 􀋹 􀋺 􀋺 and the end of 􀋻 􀋹 􀋺 􀋾 , after the definition of different technical and fundamental variables, using step by step regression-correlation, factors affecting stock prices in Tehran Stock Exchange were selected as model input is defined. Then the artificial bee colony algorithm in an atmosphere of parametric design is used to optimize the weights and biases of recurrent neural network. To evaluate the model, several criteria for a given stock of listed companies in Tehran Stock Exchange are used. The results show that the neural network optimized with artificial bee colony algorithm has considerable accuracy, compared to other forecasting methods.

This research aims at simulating the interactions of linguistic variables affecting market capitalization of capital market. In this regard, the dynamic model of the research has been designed by using a system dynamics approach and, in order to reflect investor’ s mentality, the fuzzy inference system has been merged with system dynamics methodology. In this framework, the fuzzy membership functions of variables such as Market Efficiency, Market Manipulation, Investor’ s Knowledge and Culture, Market Trust, and Investor’ s Sentiment has been defined and Using Vensim DSS to simulate the scenarios, the validity of the model has been tested under systemic and statistical tests. This research is an applied study with an exploratory mixed method framework in line with ١ ٤ ٠ ٤ Vision. The results show that Simultaneous change in endogenous variables, results in faster and greater change in market capitalization than distinct change in each of this variables. Changing the Market Efficiency, Investor’ s Knowledge and Culture, and Market Manipulation in the demanded way will increase the market capitalization by ٧ ٧ ٪ in the comparison with base run simulation values. The results of sensitivity analysis shows that market capitalization is more sensitive to simultaneous change of endogenous variables than the distinct changes of each of these variables.