نشریه مهندسی مالی و مدیریت اوراق بهادار
پیاپی 54 (بهار 1402)

This study aims to design a digital marketing model in the field of capital markets with a qualitative approach for stockbroking companies. The present research is an applied research in terms of purpose, a type of method in terms of method, and a qualitative research method in terms of data collection method. The statistical population includes 17 experts, including CEOs of brokerage firms and their deputies and senior managers. The main data collection tools in the field section included semi-structured interviews. For data analysis, qualitative content analysis method and Max.Q.D software were used. Based on the results of qualitative analysis, three categories of comprehensive categories including customer orientation, branding and digital marketing were identified as the main components of digital marketing in the capital market. Digital marketing includes digital roadmap, and innovation in digital financial services; In relation to branding, customer-based brand equity and social media were identified; Finally, in relation to customer orientation, components such as customer knowledge management, customer engagement and value creation were identified as organizing themes.

The financial markets of each country reflect the dynamism of that country's financial institutions and instruments. In developed financial markets, new tools have emerged to hedge trading risk. options is one of these tools, the price of which is a function of supply and demand. But there are pricing models in this market, the most widely used of which are the Black Scholes model and binomial . The purpose of this article is to evaluate the efficiency of these two methods in the option market to buy transactions on the Tehran Stock Exchange. For this purpose, 30 highly traded symbols during the years 2016-2020 have been selected and their prices have been estimated based on both models. To measure their efficiency based on the obtained regression models, R2 and regression beta have been used. The results show that based on R2 and beta variables, there is no significant difference between the mean scores of the two models and these two models have the same performance in the market. , the bid prices of both models are lower than the call options in the market, but there is no significant difference between the performance of Black Scholes and the binomial .

Corporate social responsibility includes a set of corporate activities and actions that it performs with the aim of doing good for people inside the organization such as employees or people outside the organization, including suppliers, consumers and people. The result of social responsibility motivations of participate in management has been better performance company in terms of better allocation of organizational resources and reform of organizational strutures in line with the companys value oriented goals. The purpose of this study was to investigate the relationship between social responsibility during different stages of the life cycle on the financial constraints of the company. It took place until 1398. The results showed that due to the inverse relationship discovered between social responsibility and financial constraints, firms at each stage of development face different goals of social responsibility and show different capabilities in performing social responsibility. Also, for companies that are in the stages of growth, maturity and decline, the higher their social responsibility scores, the less financial constraints they face.

The question for many corporate finance managers, especially start-ups, is what the financing pattern can do for such companies. This issue is controversial in the financing literature and its various techniques. Improving the performance of any business is the main desire of its shareholders and increasing the performance is a function of several factors. Accordingly, the present study seeks to investigate the impact of various financing techniques on the financial performance of start-ups and knowledge-based companies. The statistical population of this study includes all knowledge-based companies. The available statistical population includes 42 knowledge-based companies that have been accepted in different stock and OTC markets and their shares have been traded in the market in 2020. Research evidence showed that entrepreneurial financing, financing in the form of debt and financing, financing in the form of bank resources, financing in the form of risky financial resources, financing in the form of securities offering in off-market markets, Financing by offering securities on the stock exchange and financing by equity and debt method affect financial performance.

The most important things to do and take time to do is to take advantage of the small amount you can get. The present study is a practical and exploratory combination in terms of purpose and data collection. In the qualitative part, semi-structural interviews, focus group and expert grouping are used, and in the quantitative part, structural equations are used. The results led to the identification and compilation of 204 indicators in the field of Chechnya in which more than 50% of experts selected 87 codes and codes that are of the same genus were placed in a separate group and finally the codes were grouped into 11 components and 4 dimensions. The results showed that blockchain technology, like other new technologies, has advantages and disadvantages, the results of which show that its advantages outweigh its disadvantages. Blockchain capabilities showed that the use of this technology in the processes of acceptance, issuance and damages can significantly increase the accuracy and speed of these processes. Proper implementation of blockchain technology in the insurance industry can play an important role in promoting public confidence in the insurance industry, streamlining processes, optimal pricing, correct damage estimation and service, and identifying low-risk insurers

The main purpose of this study is to investigate the effect of the business cycle and operational efficiency of the cash flow cycle on performance appraisal criteria in the Tehran Stock Exchange. In order to reach this purpose, we were using the data of 120 manufacturing companies active in the Tehran Stock Exchange during the period 1392 to 1397, using the independent variables of cash flow cycle and net business cycle of the company by multivariate regression method, with the help of Eviews software, economic value added indices, return on assets, return on equity as a dependent variable of role-playing performance indicators to achieve the objectives of the study.The results indicated that the cash cycle and the business cycle had a positive and significant effect on the return on equity. Finally, the results indicate that the cash cycle and the business cycle have an inverse and significant effect on value-added and return on assets, and the research hypothesis has been confirmed.

Block chain technology as a promising innovation in the cyber space brings new opportunities. It serves not only the computer world but also other areas like the economy. The purpose of this study is to determine the effect of using block chain as the backend technology for digital currency on reducing costs in economic transactions, which has done in the period of 2019-2021. The hypothesis of the research claims that block chain enables us to reduce searching and bargaining costs towards resistance economy. This research benefits from a pluralistic method to study the impact of applying block chain technology in the field of economy. In doing so, three different methods were used in order to investigate the research hypothesis including theoretical analysis, interview with 20 experts and statistical inference. the findings indicated that applying block chain technology results in reduction of searching and bargaining costs. block chain immutability and decentralizing characteristic reduce searching and bargaining costs more than other features and the existence of distributed ledger has impact on decreasing both searching and bargaining costs. Moreover, block chain can be aligned towards the goals of the resistance economy by bringing new technology into the economy and reducing the costs.

Many companies are using the environmental accounting system to find a suitable way to report and disclose information to the public. Evidence shows that the information provided by the green accounting system is useful for users and plays an important role in their decisions. Industrial, refineries and power plants and smelting and steel companies. These economic actors, their investors, and on a larger scale, society as a whole, will never achieve this success unless they are indifferent to the threats to human and environmental well-being in the long run. In such situations, governments, stock exchanges, markets, investors, professional legislators, academics and other community activists call on companies to be clear about their goals, performance and impact on sustainability. The main purpose of this study is to identify the financial factors affecting green performance in the steel industry. In order to achieve this important, the research was conducted during 1399 and 1400 in two separate stages.

The Behavioral finance literature states that human beings in practice behave differently from what modern financial theories portray as rational human beings, so the assumption of rationality of investors and the belief in the efficiency of stock markets has been criticized. Accordingly, the present study examines the impact of investor behavioral biases on how to make decisions and market efficiency simultaneously, which has not been addressed so far. It also highlights the importance of understanding the process and the role of behavioral factors in investor decisions and market efficiency for future capital market policymakers and regulators. The present study is applied in terms of type of use and descriptive-correlational research. The target population of this study was real investors in Tehran Stock Exchange and Available purposive sampling method was used. Structural equation modeling were used to analyze the data and test the conceptual model of the research. The research findings show that biases of overconfidence, representation, availability and anchoring and adjustment have a significant effect on market efficiency. Findings also showed that overconfidence bias, anchoring and adjustment have a significant effect on investment decisions. Behavioral biases among investors are inevitable that these biases can affect investors' decisions and market efficiency.

The purpose of this study is to investigate the role of Fintechs in customer retention mediated by customer satisfaction and is descriptive in nature and method and correlation in terms of relationships between variables. The statistical population included two sections of customers and employees of bank Melli Iran branches in Tehran and the sample size was estimated 384 for customers and 248 for bank Melli employees using stratified and available sampling method. The collected data were analyzed using structural equation modeling in SPSS and smartpls3 software. The results showed that the direct effects between variables, ie the effect of financial Fintechs on customer satisfaction, financial Fintechs on customer retention and the effect of customer satisfaction on customer retention, are statistically significant and sub-hypotheses are confirmed. the strongest effect is related to customer satisfaction coefficient on customer retention and 0.772 and the weakest effect is related to financial Fintech coefficient on customer retention at 0.152. The results of Sobel test showed that the indirect effect of customer satisfaction on customer retention was significant and the main hypothesis of this study was confirmed. The indirect effect of job satisfaction variable in the relationship between financial Fintech and customer retention is about 0.21.

The cognitive psychological conditions of the investor can influence the financial decision regarding the selection of priorities, risk assessment. In this regard, this article examines how the investor's mood affects the financial decision by making minor changes in the "Lucas" model. The results showed: a) The investor with a better Mood state, has less risk aversion and vice versa. b) Increasing time preference significantly increases the price of capital and reduces the accuracy of forecasts for return on investment. c) Mood State variables have a greater impact on investment markets than on the securities market. Finally, by considering the role of investor Mood State in asset pricing models, objective evidence of growing anomalies in the capital market can be justified. Human behavior is influenced by both the senses and the intellect, so neither should be left out in economic decisions. Therefore, paying attention to the Mood state variable in the investor can help explain the sharp fluctuations in the capital market.

The main goal of investors in the stock market is to get the highest return at the desired time, therefore introducing the most suitable method for conducting transactions is of special importance for investors. Successful trading in financial markets should be done close to key reversal points. In recent years, various systems have been developed to identify these return points. Technical analysis tries to identify the time to enter and exit trades.In this article, we are trying to select the one with a higher success rate by using the technical rules according to the previous researches, and by using soft calculations, the decision parameters in the technical rules are improved using the firefly algorithm.The results of this model are compared with the results of using the standard parameters of the indicators and the results of the purchase and maintenance strategy. In order to validate the introduced trading system, we compared it with the results of the optimized intelligent system based on optics and genetic algorithm. The results of the research show that by optimizing the parameters of technical analysis indicators, the investment efficiency can be increased compared to the usual methods in the stock market and previous researches.

Representation theory refers to managers' equity, financial leverage, and dividends as tools used to reduce the agency dilemma. Ownership of managers, although it causes their interests to align with shareholders, but on the other hand also leads to the fortification of managers or their conservative behavior. In fact, managers with different levels of ownership act differently in other financial decisions such as the use of financial leverage and dividends. The aim of the present study is to find out the effect of managers' shareholding thresholds, in which their behavior in dividend and financial leverage decisions differs before and after. In this study,143 companies have been selected in the period 1392-1392. The research findings show that the effect of managers' ownership on financial leverage is based on two values ​​of ownership thresholds and consequently three different behavioral regimes for financial leverage.In the first and second behavioral regimes, managerial ownership has positive and significant effects on financial leverage. Regarding the effect of managerial ownership on dividends paid, a threshold value has been identified that in both regimes, the effect of managerial ownership on dividends paid is positive and significant, but in high values ​​of thresholds, the effect coefficient shows a significant increase.

There are various methods for comparing the explanatory power and validity test of deregulation patterns to numerical solution methods with their equivalent methods in the financial and technical literature. Also, the advantages of this comparison of patterns are more for the methods of analysis of index fluctuations and de-trending and its reliability to the methods of estimation and regression. Therefore, the purpose of this study was to analyze and compare the explanatory power of the model between the numerical solution method and the estimation approach using regression. In this regard, the new geometric method of droplet motion and pattern solving using the innovative Fokker-Planck algorithm and the Augmented Dicky-Fuller estimation method were compared with the trend-reliability assumption. Statistical population of Tehran Stock Exchange stock price index research; And the statistical sample was the daily values of the index from 1390s to the end of 1399s. The results of de-trending and reporting the explanatory power of the patterns were stated that explanatory power of the geometric pattern of drop solution is more than other models, which indicates the greater validity of the analysis of the movement of the index according to this model than the statistical model named Dicky-Fuller generalized.

The economy of many countries around the world is now dependent on commercial activities in ports. Although ports are considered among the most important transportation infrastructures that can greatly affect economic growth, less attention is paid to ports and their relevant commercial activities in Iran. This study used the mixed-data method to address this issue by reviewing the data related to Khuzestan, Bushehr, Hormozgan, Sistan and Baluchestan, Guilan, and Mazandaran provinces of Iran in the period 2005-2017. The results showed that the operating capacity of ports exhibited a significant and positive effect on the economic production of the studied provinces. In addition, the uploading and offloading volume showed a significant but nonlinear effect on the economic production of hosts. In other words, the economic production increased with the increase in the operating capacity of ports but further increase in the operating capacity beyond the critical point negatively affected economic production. The study findings also indicated that human development, economic growth rate at the beginning of the studied period, employment, government investment in ports, government’s working budget, technology, manufacturing structures, and urbanization rate had positive and significant effects on the economic production of the studied provinces.

AbstractThe purpose of this study is to design a financial stress index to predict the occurrence of a financial crisis. In this study, a composite index has been designed to measure the Iranian financial system and the effects of financial turmoil in conditions of uncertainty in the financial markets and the Tehran Stock Exchange between 2009 and 2021. Since the shocks of variables were used in previous studies, in this study, three factors of currency turbulence, stock market index turmoil, and banking industry turbulence have been used to design and construct the financial stress index. This research is conducted in five steps based on the DCC-GHARCH approach and finally, based on the variables of financial institutions and the stock index, a predictive model for the financial stress index is presented. From the results, we find that all independent variables of the research have a positive and significant effect on the financial stress index, except for the coin price volatility index, which has a negative and significant effect. The value of the model determination coefficient is 0.8736, which indicates that the quality of the fitted model is desirable.