مجله مدیریت دارایی و تامین مالی
سال دهم شماره 3 (پیاپی 38، پاییز 1401)

Algorithms based on a Convolutional Neural Network (CNN), which is a branch of Deep Learning (DL), have seen significant progress in picture and video analyses in recent years. Success of these new models has led to widespread use of them in various fields, including text mining and time series data. DL is part of a broader family of machine learning methods that attempts to model high-level concepts using learning at multiple levels and layers and extract features of higher levels from the raw input. This survey investigated the abilities of different CNN architectures to predict stock prices. Upon running the model with various architectures and parameters for the stock price of Esfahan Steel Company, the results showed that a CNN with max-pooling layers (a combination of Batch size=64, filters=256, and ReLU Activation Function) and Mean Absolute Percentage Error (MAPE) of 1.79% and Normalized Root Mean Square Error (NRMSE) of 2.71% had a higher prediction accuracy than other CNN architectures and Recurrent Neural Network (RNN).

The purpose of this paper was to investigate the effects of board relations network structure on labor investment efficiency. Besides, the role of institutional owners in these relationships was studied. This paper had a quantitative approach based on graphic techniques. The sample included 117 companies in Tehran Stock Exchange (TSE) from 2009 to 2020. The social network analysis and regression analysis approaches were used to conduct the research tests. Evidence showed that the indicators of the degree (negative effect) and closeness (positive effect) of board relations network structure affect labor investment efficiency. In addition, monitoring of institutional owners can have a positive effect on labor investment efficiency. The intensity of the relationship between the degree index and labor investment efficiency depends on the level of this variable. Moreover, the negative relationship between over-investment in labor and the betweenness index depends on the level of institutional owner monitoring.

Disclosure of information, especially information about company risks, provides investors with useful information about the inherent risks of the company. Whether this information signal has information content or not, it will lead to an increase in the investors' understanding and ultimately their reactions and changes in stock prices. Therefore, the aim of this study was to analyze the market reaction to risk disclosure factors, which included financial risk, operational risk, and strategic risk. To measure risk disclosure in this study, a method based on the content analysis of the board of directors' activity report to the general meeting of shareholders was used. Also, to investigate the market reaction, abnormal returns accumulated around the date of publication of the board of directors’ activity report were utilized. In the period of 2011-2019, among the companies listed on Tehran Stock Exchange (TSE), 655 years-companies were selected as a sample. Multiple regression was applied to test the research hypotheses. The results indicated that the total risk disclosure and types of risk disclosure, including financial risk, operational risk, and strategic risk, had a positive and significant effect on the abnormal returns on stock accumulation. In other words, the disclosure of risk factors had information content and the market reacted to their disclosure in the report of the board of directors.

The purpose of this research was to survey the dimensions of implementation and development of risk management in financial industry organizations in Iran so as to reveal the level of risk management implementation and its degree of maturity, including the level of risk management culture, risk management governance, and integrity of risk management systems and processes, in the financial industry organizations.This research, which was a survey in terms of its nature and an applied one in terms of purpose, was performed among 173 organizations from all the companies and institutions in the country's financial industry. A questionnaire was used to collect the required data and information. The results showed that the risk management culture in the country's financial industry organizations was at a slightly lower than average level. Risk governance was at a slightly higher than weak level and the integrity of risk management systems and processes was lower than average. This research investigated enterprise risk management and its development among Iran’s financial industry organizations for the first time.

Crowdfunding has become a modern and favorite financing channel worldwide. Crowdfunding is a new financing method that helps entrepreneurs acquire the financial resources needed for their projects. This study aimed to investigate the factors affecting individuals' interest in participating and investing in social crowdfunding projects. Using the Structural Equation Modeling (SEM) technique, the developed model was tested with the help of Amos software via the data obtained from 318 individuals. This paper examined the direct and indirect contextual variables: awareness of need, altruism, reputation, psychological benefits, efficacy, funder’s trust, and institution-based trust in the investment intention. Finally, it was observed that awareness of need, altruism, values, reputation, psychological benefits, efficacy, funder’s trust, and institution-based trust were the factors influencing people's intention to invest in social crowdfunding projects.

Given the importance of estimating stock returns, the purpose of this study was to identify the factors affecting stock returns by using the meta-analysis method. Meta-analysis is the main tool for combining results in social and behavioral research. It allows researchers to combine quantitative results of studies, explain the compatibility of results, and achieve a single result. Based on the research background, the impacts of different factors on stock returns were considered. A model of factors affecting stock return is designed in the analysis of empirical studies. This research used the meta-analysis method to comprehensively examine the factors affecting stock returns and assess the different factors that had been examined in various studies over the past years. In a similar research, the researcher had selected the factors affecting stock returns and only tested the selected factors via general categories. However, in this research, a more comprehensive study was conducted to separately examine all the factors whose effects on stock returns had been tested in different studies. Therefore, some of the factors investigated in this research had not been studied in the previous research. Accordingly, a model of factors affecting stock returns was developed. In this research, 422 studies were collected and 102 of them were analyzed. Totally, 153 factors were extracted from these studies and finally, 16 factors were tested. The type of effect size calculated in this study was r. Among the examined factors, earnings per share, operating cash flow, net operating assets, operating earnings, market return, earnings quality, and return on equity had an impact on stock returns. Since the majority of the factors affecting stock returns were related to the financial reports of companies, i.e., their financial status and performance, those factors could be considered to investigate investment opportunities.