فصلنامه دانش مالی تحلیل اوراق بهادار
سال هفدهم شماره 63 (پاییز 1403)

The purpose of this article is the comparative analysis of bank bankruptcy from the aspect of cultural values of societies, and in other words, the effects of different aspects of national culture on the risk of bank bankruptcy. This study was conducted on an international sample of banks from 111 countries in the world, whose cultural characteristics and bankruptcy risk data were collected between 2009 and 2022, and correlation and regression techniques were used to analyze the data and test the research hypotheses. took The findings of the current research indicate that at the 95% confidence level of the statistical test, the cultural components of individualism, masculinity, avoidance of uncertainty and long-term vision have a significant relationship with the risk of bank bankruptcy. Meanwhile, no significant relationship was observed between the cultural component of power distance and the risk of bank bankruptcy. Also, individualism and masculinity are positively related to bankruptcy risk, and uncertainty avoidance and long-term perspective are negatively related to it. The evidence of this article can provide useful information for the legislators and policy makers in the field of banking about the effects of culture on the risk of bank failure.

The purpose of this research is to provide a decision support system to assess the credit risk of real bank customers. For this purpose, firstly, using the library method, the effective indicators on the credit risk assessment of real customers were identified and then, using the fuzzy Delphi method, the indicators were screened. The community of this section was formed by banking experts (Bank Mellat) who were selected by the snowball method. In the following, The decision support system was designed and implemented to evaluate the credit risk of real bank customers in SPSS Modeler software. The final data related to the indicators included the files of 7318 real customers of Bank Mellat during the years 2013-2016.The results of the research showed that the decision support system consisting of support vector machine and random forest correctly predicted the status of customers in the four categories of on-time delivery, past due, overdue and questionable delivery by 67.09% and 65.10%, respectively. Meanwhile, the combined support vector machine-random forest model has provided a better prediction with a rate of 77.17%.

An investigation of investor sentiment on relation between cross-sectional expected stock return and left tail risk.

For this aim, a sample of 201 listed firms in Tehran Stock Exchange from 2009 to 2019 is examined. “Portfolio analysis” and “Fama-Mcbeth regression” (1973) approaches are used to test this hypothesis “investor sentiment affects the relation between expected stock return and left tail risk”.

Reverse relation between VaR and expected stock return is confirmed for high sentiment period but isn’t for low sentiment period. The volatility effect overcomes the VaR explanation power to elucidate cross-sectional stock return variations for High sentiment. Increased sentiment of noisy investors strengthens their optimism and subsequently increases stock price. This point results in limit to arbitrage therefore the effect of noisy investors can not be cancle out. By increasing the level of investor sentiment, stock retrun is overestimated and its risk is underestimated. Demand for stock having high volatility increases its price and consequently the future stock return decreases.

The relation between expected stock return and VaR affected by investor sentiment.

In This paper we examines the leverage deviation on the cost of capital of Tehran Stock Exchange companies .furthermore the sensitivity of the cost of equity to leverage deviation, has been analyzed to deduce the reasons of heterogeneity in capital structure among firms. the hypothesis of model released according to miller and Modigliani theorem 2. required data form 112 listed companies from the period of 1390 to 1400 to construct variables of model has been gatherd.to examine the hypothesis the companies categorized into overleverage and under leverage. Confirming theoretical predictions, we find that the cost of equity is positively related to leverage deviation and that firms whose cost of equity is more sensitive to leverage deviation exhibit faster speed of adjustment toward the target. Collectively, our findings imply that capital structure targeting is not equally important to all firms. Indeed, we argue that while evidence of the trade-off theory will tend to be obscured in broad samples, it can hold strongly in meaningfully chosen sub-samples of firms — namely, those characterized by high sensitivity of equity cost to leverage deviation.

The purpose of this research iappraiseal the ground drivers of creative accounting for the neurofinance effectiveness in the logic of financial ddecision-makers So, in the qualitative part, systematic screening, it was done to identify the financial drivers of the phenomenon of creative accounting in order to measure the effectiveness of neurofinance in financial decisions and then, based on the pre-test and post-test plan, the difference between the approaches of financial analysts was determined through variance analysis. In fact, with the aim of separating the participants in the form of two experimental and control groups, an effort was made to determine the difference in the approaches of financial analysts in decision-making. In other words, the experimental group was a group of participants who were affected by skill evaluation, and the control group consisted of people with demographic characteristics such as experience; Knowledge and education were influenced by the classical functions of behavioral finance. The results of the study showed that the experimental group, which is influenced by the skill evaluation of the financial drivers of the creative accounting phenomenon, has a higher coefficient than the control group in both decision-making scenarios of the analysts. It was also found that the experimental group, which was influenced by the DOPS skill evaluation based on the identified background drivers, has a higher favorability in the fair value fluctuation decision scenario than the conservative decision scenario. While the average of the control group is exactly the opposite of the experimental group.

The design of automated trading systems has increased in various countries, including Iran, recently. The advantage of such systems is the increase in speed and accuracy of trading decisions without emotional interference. Having a model that can simultaneously estimate opening, maximum, minimum, and closing prices is a significant advantage for investors. In this study, using the LSTM neural network, simultaneous estimation of these four prices is performed, and various classification algorithms are used for buying, selling, and holding points to design an optimized algorithmic trading system using a genetic algorithm. To evaluate the proposed model, data from Shapna, Khodro, and Fajr stock markets in Iran from 2012 to 2020 and MATLAB software are used. The results of this research show that the proposed method has a very desirable performance in both simultaneous multi-price estimation and classification of buy, sell, and hold classes. Therefore, it can be considered a very suitable method for automated trading, and a robot based on this method can be designed and implemented in the Iranian stock market for this purpose.

The main purpose of this article is to investigate the effect of monetary and financial shocks on the prices of financial assets using the Panel VAR method. The current research method is based on the research objectives of applied type. Research data in the period between 1390 and 1400 in the period. It was fitted using Eviews12 software. The results of the Dickey-Fuller test showed the stationarity or meanness of the variables. research variables; The logarithm of the exchange rate, the logarithm of the price index, the logarithm of the gross domestic product, the logarithm of the price index of construction services, the logarithm of the land price index, the logarithm of the volume of liquidity, the logarithm of government expenditures, and the logarithm of the building rent index were stationary at level I_1; The results of the optimal interval based on the Schwartz Bayesian criterion (SBC) showed that the best interval is one and two. The results of Johansen's cointegration test based on the effect statistic and the maximum eigenvalue showed that there is a long relationship between the research variables. The results of the analysis of shocks showed that monetary and financial shocks affect the price of financial assets.

Investors are willing to invest in the capital market which would earn a proper profit and would make the possibility of an accurate forecast of future trends and prices. In this regard, deep learning (DL) networks have been able to help in predicting the capital market movement. Due to the high capacity of DL approaches in many fields due to their strong capacity, they have been widely used in financial issues such as stock market movement prediction, portfolio optimization, financial information processing, etc. Recently, generative adversarial networks (GANs) illustrated suitable results intending to analyze and predict time series data. Therefore, in this study, the GAN consisting of a convolutional neural network as a generator and long short-term memory in the adversarial network is proposed for stock price prediction. In addition, in order to increase the accuracy of the network, other DL approaches have been used in network training. The results of the daily data of the Tehran Stock Exchange between 1394 to 1398 demonstrate that the prediction accuracy of the GAN network using the most appropriate features is up to 10%. The experimental results of this model show that the GAN network with the mentioned architecture can have a promising performance in stock price prediction compared to other DL models.

The aim of this study is to expand the network process of assessing the financial stability and risk of capital market companies based on MES and CoVaR scales, which is calculated through the coefficients of the multi-layer network model of the total capital market index. In this study, the assumption that the financial crisis and the capital adequacy ratio can be estimated as the basis of the risk and financial stability of capital market companies, which can be estimated through the definition of the network process model and the two scales of MES and CoVaR in 2012 to 2022 surveys were conducted. Therefore, the value at risk of the daily return data of the total market index using a GARCH model to estimate "CoVar" first, then in the next step based on quantal regression at two confidence levels of 0.05 and 0.01%, the scale "ΔCoVaR" » be calculated and show whether the total market index indicates higher or lower financial stability risk parameters than the MES scale. The results showed that, on average, the ΔCoVaR scale shows financial stability risk lower than the MES scale. The reason for this is that the higher the share of parameters such as low capital adequacy and financial crises, the higher the probability of financial stability risk increases, and this issue causes companies to face more serious problems in securing financial resources.

During the last two decades, the concept of sustainable development, which refers to the interrelationship of economic, social and environmental considerations, has attracted a lot of attention. Therefore, in the present study, the association between sustainability reporting and firms’ cost of debt was investigated. For this purpose, the World Reporting Organization checklist was used to measure the firms’ sustainability reporting. The research hypothesis was investigated using a sample consisting of 134 firms listed in Tehran Stocks Exchange during the time period 2018-2022 and using the multivariable regression model based on the panel data technique. The findings of the research indicate that there is a negative and significant relationship between sustainability reporting and significant firms’ cost of debt. The findings of the research indicate that there is a negative and significant relationship between sustainability reporting and significant firms’ cost of debt. The findings of the research indicate that there is a negative and significant relationship between sustainability reporting and significant firms’ cost of debt.

Therefore, considering that there is no adequate understanding of the functions of this approach, in this research, an attempt has been made to evaluate the functions of the civilized governance structure at the level of capital market companies through scenario development. This study is considered applied in terms of the type of result, and from the point of view of the goal, it is placed in the category of exploratory studies that have been carried out using quantitative and qualitative models. The present study does not follow one type of research method, but uses a separate method to answer the formulated questions according to each department. Therefore, based on the nature of collection, this study can be classified as mixed methods approach. The statistical population in the qualitative part was 10 experts in the field of financial management and accounting, and in the qualitative part 29 experts and experts in the field of corporate governance participated. The result in the qualitative part indicated the existence of 6 factors to evaluate the corporate civilizational governance structure functions at the level of the capital market, which was confirmed based on the Delphi analysis. Then, by selecting 2 factors out of the 6 factors identified as the basis of scenario planning, by conducting thematic analysis, 11 sub-factors emerged.

In this study, we seek to test the effect of government policy uncertainty on the investment of listed companies in recession and boom regimes. For this purpose, the effect of study variables during the period of 1380 to 1400 is investigated by using the rotation model and the Markov switching (MS) regime change. Based on the results of the model estimation, with the increase of government policy uncertainty, corporate investment decreases. In general, the uncertainty of government policies increases the risk of investment projects and leads to a decrease in corporate investment. Especially in an inflationary situation where the value of money decreases, the nominal interest rates for savings and reserves are low. In this case, investing in currency, real estate, gold, etc., provides a higher interest rate compared to keeping reserves in the banking system. This causes a decrease in the desire to save and reduces the funds available for investment in the banking system, and as a result, corporate investment decreases.

Tehran Stock Exchange companies in the field of construction industry. From the point of view of the practical goal and from the point of view of data collection, this research is descriptive, exploratory and analytical, and in order to carry out the research, a mixed method has been used in two qualitative and quantitative phases. The population and statistical sample of the research includes 10 experts in the field of financing in Tehran Stock Exchange companies active in the field of construction industry. In the first phase, the researcher used the qualitative method of thematic analysis to code the axes of the experts' interviews, which led to the identification of 27 risks in the form of 7 main criteria, including financing costs, risk of timely supply of resources, repayment structure, risk of interest rate fluctuations, The risk of exchange rate fluctuations, the risk of not realizing the project's income on time, and the risk of macroeconomic variables, and in the second phase, using the quantitative method of the intuitive hierarchical analysis process, 5 financing methods were prioritized in the form of identified risks. The results of the research showed that financing methods through 1-borrowing from international development banks, 2-foreign finance, 3-national development fund, 4-Islamic securities and 5-shareholder of the project have priority.

The purpose of this research is the impact of abnormal stock returns on the future fluctuations of stock returns. The statistical population of the research is the companies admitted to the Tehran Stock Exchange in the period of 2013-2014. Sampling has been done by systematic target method. According to the conditions of the companies admitted to the Tehran Stock Exchange, 130 companies met the conditions of admission in the examined sample. Research data were extracted from the audited documents of financial statements published by companies, statistics and figures published on the website of the Stock Exchange Organization, Codal and Central Bank. Then, the reliability of the research variables was investigated using the Bayesian panel method in EViews 10 software, and the research hypotheses were investigated. Finally, the results of the hypothesis test showed that abnormal stock returns have a positive and significant effect on the future fluctuations of stock returns of companies listed on the Tehran Stock Exchange