فصلنامه دانش مالی تحلیل اوراق بهادار
سال پانزدهم شماره 54 (تابستان 1401)

With developments in Iranian Capital Markets and the influence of Social Networks, the need to a tailored social platform for Iranian capital market seems inevitable. The purpose of the study is to design a quantitative model for social trading platform based on rating of dimensions and categories. The research was performed as a descriptive-survey, and considering the type of data, it was a mixed research and ranked the dimensions and criterions of the social trading platforms in Iranian Capital Markets. Based on Theoretical Matrix from previous surveys, the research was performed using descriptive and inferential statistics and a quantitative approach based on factor analysis of 380 questionnaires collected from investment, financing, VC and other expert parties and the reliability and validity of the model were tested using structural equations through smart PLS. The dimensions were ranked using structural equations and the criterions were ranked using Friedman rank analysis and confirmatory factor analysis. The highest estimated path coefficient reveals the highest ranks of dimensions. Statistical analysis of questionnaires regarding 11 main dimensions resulted on the following ranks (on the scale from most to less important) as follows: 1) information and trading transparency, 2) the interaction of money market and securities market, 3) training and investor education and reducing herd behavior, 4) stock analysis and returns, 5) the characteristics of social network, 6) owners’ equity and financial statements, 7) risk management, 8) inventory management systems, 9) financial and market ratios, 10) competitiveness ability, and 11) technologic characteristics.It should be noticed that the structural equation modeling results in better ratings for main dimensions, but for the rating of the criterions, one sample T test and Factor analysis end in best results. It could be concluded that dimensions like the information and trading transparency, interaction of money and securities market, and training and investor education have attained the highest ranks and dimensions as financial ratios, competitive abilities, and technologic characteristics has the lowest ranks. It should be considered that these results could be useful in the process of product development for developers and venture capitalists working on social trading platforms.

Financial managers of companies often need financing to carry out development projects or their daily turnover finance. In recent years, crowdfunding has become a valuable alternative source of funding for entrepreneurs seeking funding. Therefore, in this study, which has been used qualitatively and with the Grounded Theory, the appropriate model of debt financing of banks through crowdfunding is sought. For this purpose, the opinions of ten experts in this field who were selected using the snowball method were used to identify the factors affecting the debt of financial institutions and banks. After the interviews, the results showed that the banks' debt financing is formed as a result of mass communication (causal conditions), trust building and culture building (intervening conditions) and environmental factors and legalism (ruling bed) which uses e-commerce strategy to secure the debts of banks and credit institutions.

The purpose of this study is to design a warning system for price bubble and financial crisis in the Iranian stock market. In this study, the statistical information of the seasonal data of the period 1990-2019 and the MGARHC have been used to extract and identify the variable of financial crisis and price bubble in the capital market. The results of this study showed that variables such as production, inflation rate, exchange rate, total stock market index, etc. have a significant impact on the occurrence of financial crisis and the possibility of price bubbles in financial markets. Based on the estimation, it can be stated that the effect of the shocks of the research variables on the occurrence of the price bubble in the stock market leads to an increase in the instability of the variables. This can be due to the dependence of the economic structure on its markets, and this can have heavy consequences due to a shock on the country's structure.

Many studies have been done on the momentum strategy in Tehran Stock Exchange to predict stock returns .In most of research pertaining to momentum, profit and return are used as a criterion for selection of stocks with best (worst) performance in the past for momentum portfolio. Therefore, the purpose of this study is to investigate the profitability of momentum strategy using the analysis of financial statements based on past share returns. For this purpose, the sample includes 213 member companies of Tehran Stock Exchange and has been selected for a period of 10 years from 1388 to 1397. This research is applied in terms of purpose, post-event experimental in terms of research method, reasoning in terms of method, establishment, theory in terms of behavioral financial research and statistically in the form of correlational research using community (sample). It acts as a model for the whole society. To test the research model, first F-Limer test and then Hausman test were used. The results tests showed that the test method for the research hypothesis is the panel (panel) data method with fixed effects, which was performed using 10 EViews software. The results of this study show that the collected data are significant at 95% confidence level (P-Value = 0.000) and the adjusted R2 value is 0.89 and shows that about 89% when performance expectations A company reflected in past prices that is consistent with fundamental analysis, the momentum effect is stronger than when the pure momentum strategy is used.

Disclosure of the main risks of the business unit and changes in those risks, along with management plans and strategies, to address or reduce these risks and the effectiveness of risk management strategies. This disclosure of information helps financial users assess the entity's risks as well as their expected consequences. The purpose of this research of Effect of Different Levels of Corporate Risk Disclosure on Investors' Perceptions. In this study, considering that there was no clear and coherent basis for the separation of levels of risk reporting, based on the methodology of the qualitative sector, an attempt was made to identify the dimensions of risk disclosure based on the content analysis process. Therefore, in terms of the result of this research, it is developmental, and in terms of its applied purpose, it is in the category of semi-experimental research. It is also a combination of research data types. In this study, a scenario-based questionnaire was used to test the hypotheses. The scope of the research in 2020, the statistical population included active investors in the Tehran Stock Exchange, 160 people were selected as a sample size and examined. The results of the research in the qualitative part indicate the existence of two main categories as levels of risk reporting of capital market companies. The results in the quantitative section also showed that the average perception of investors in the convergence of risk disclosure is higher than the divergence in risk disclosure

Green financing is one of the new financial paradigms for combining environmental support and financial-economic benefits. Accordingly, the present study seeks to develop a green financing model for companies through the Iranian banking industry based on the data theory of the foundation. The statistical population includes 16 experts in banking and environment and faculty members of universities who were selected as participants in the study. The data collection method was field and the data collection tool was interview and a semi-structured interview based on exploratory study was used. Data analysis in this method was performed using open coding system (category identification), axial coding (category cultivation) and selective or selective coding (final category selection). The results showed that strategies for removing barriers and formulating transparent and stable laws, equipping banks' financial (environmental) resources, accurate and practical targeting of banks, agile executive organization and implementation of an integrated control and supervision system lead to a mental image based on importance. The process of green financing of companies is done through banks and also the differentiation of this process with other aspects of financing, which can be the basis of analysis.

The main goal of the current study is to investigate the contagion of uncertainty between sectors (finance, housing and macroeconomics) using a dynamic approach. In this regard, using monthly data in the period from 2008:4 to 2020:3, DCC-GARCH models and generalized forecast error variance decomposition (GFEVD), The overall dynamic relationship as well as the directional pairs dynamic relationship of uncertainty indicators between the mentioned sections are investigated. The results of this study show that the housing sector, with the exception of the beginning of 2017, is a net receiver of uncertainty from the other two sectors. Also, the results of the current research show the dual role of the financial sector in the mechanism of inter-sector uncertainty transfer, so that at some periods it is a net receiver of uncertainty and at some other periods (including the years 2017 and 2018) it is a net source and transmitter of uncertainty in the three indicators system. Inflation uncertainty, as an index of macroeconomic uncertainty, is a major source of uncertainty and a transmitter of uncertainty to the financial and housing sectors.

An important part of managers' decision-making functions is rooted in organizational functions in terms of the existence of drivers to monitor their performance. Inertia is considered as one of the consequences of poor organizational performance in regulatory effectiveness as a factor to institutionalize power in managers and create opportunism to prioritize their interests. The Purpose of this research is Provide a model of manager's organizational inertia and examine its effect on Stock Price Crash Risk. In this study, stock price crash risk is calculated using three proxies and data related to organizational inertia of managers were collected through meta-analysis, Delphi analysis and finally sending a questionnaire to sample companies. The questionnaire is sent to 163 firms, among which 126 ones answered back. In order to perform the analysis process, the partial least squares analysis method was used. The results showed that managers' organizational inertia has a positive and significant effect on stock price crash risk. This result shows that non-disclosure of bad news for a long period of time is always created in the structural system of companies and even regulatory bodies, which is often due to organizational inertia, a lack of mobility in effective monitoring of managers' performance. By affecting the difference between intrinsic value and stock market value, it creates a price gap or bubble. This bubble is actually a mass of negative news that, based on the principle of utility in the economy, is transmitted to the market at a saturation point and causes the bursting of the price bubble will result in stock price crash risk.

The aim of this study is to introduce the Risk Management Factor (RMF) as a risk premium factor in capital asset pricing model (CAPM) and multi-factorial models of Fama and French. To answer the research questions, the information of 120 firms listed on the Tehran Stock Exchange during the period 2011-2020 has been used. According to Fama and French research, the monthly returns of the portfolios have been used for analysis. Then, using the panel data regression approach and GRS test, the performance of the adjusted models with magnet effect was compared with the conventional models in explaining the stock returns. The results showed that Risk Management factor (RMF) is effective for pricing capital assets and the development of research models with this factor and the formation of corresponding adjusted models, improves the performance of those models in explaining the difference in stock returns. The results also showed that the adjusted six-factor model with the Risk Management factor showed better performance compared to the adjusted three and five-factor model and the adjusted CAPM with the Risk Management factor.‏