میر فیض فلاح

In this paper the price bubble contagion in two currency market and the stocks market in a six year period (2015-2021) is investigated. For this purpose, the price bubble of both markets was examined and the dates of their formation and collapse were determined by using (RADF), (SADF),(GSADF) test. Then the contagion of the bubble in the financial market of Iran was investigated using a regression model. The findings of this research showed that there was a bubble in the foreign exchange market during five periods of 2016:10:31-2017:01:21, 2017:10:03-2018:12:16,2018:12:23-2019:07:14, 2020:02:22-2021:01:17 and 2021:01:23-2021:03:19.There were four bubble periods in the stock exchange for the total price index in periods 2016:02:06-2016:04:28,2017:09:04-2017:10:10,2017:10:17-2018:04:19 and 2018:06:10-2021:03:19. Also, the results indicate that the contagion of the price bubble from the currency market to the stock exchange market is statistically significant and the contagion of the bubble has occurred between the currency market and the stock exchange market .

This article introduces a designed model to elucidate the contagion effect of risk in the credit portfolio of a bank. The dynamic conditional correlation approach has been applied on a daily basis within the time span from March 26, 2011, to September 2, 2021, to model the dynamic patterns of changes in correlation among various types of risks. Initially, the risk for each contract is determined using the optimized ARMA-GARCH model. Subsequently, Conditional Value at Risk (CVaR) is extracted as the risk factor for each contract. The obtained risk values are further modeled using the multivariate BEKK and DCC-GARCH models to analyze the contagion levels based on their results and address the research hypotheses. The research results indicate that the contagion of oscillations among different contracts in the bank's loan portfolio is not unidirectional. Additionally, it cannot be definitively claimed that the spillover of risk shocks from one contract to another is symmetric. This study is anticipated to contribute to the enhancement of predictive model performance and the development of effective risk management strategies in banks.

The interaction between financial derivatives and their underlying physical markets has been the subject of extensive research in finance. This article examines the effect of dynamic contagion between the gold futures market and the physical gold market in financial markets and Tehran Stock Exchange, period of 08/29/2009 and 09/05/2018. It specifically focuses on the oscillating cycle that occurs between these two interconnected domains. Data is collected daily. Using a comprehensive data set covering a significant period, advanced econometric techniques from GARCH-BEKK, Markov-Switching and Structural VAR models to analyze volatility dynamics and contagion between gold futures and We use the physical gold market. Our findings show the existence of a two-way relationship, in which there is a contagion effect of turbulence from the physical gold market to the coin futures market. Also, another result of the research is that the contagion effect of turbulence from the physical gold market to the coin futures market is different in different regimes.

The purpose of this study is to investigate the ability of mutual fund investors to predict the performance of mutual funds and select a fund with higher returns. To predict whether investors and the cash they enter into investment funds will be able to select a more efficient fund, first, the information of 34 funds in the period 2012 to 2020 was Collected to examine the intelligence of cash. The economic prosperity periods of the market were then examined separately to determine whether investors had acted differently in different market periods. Also, real and legal investors are separated from each other to examine the performance of each separately. Using Carhart's four-factor model, the adjusted return on risk of the funds was calculated to assess the intelligence of investors, which showed that group of real and legal investors, at the time of entry during market blooming and at the time of exit money during market stagnation act wisely in mutual funds.

The purpose of this research is to choose the composition of the bank's foreign exchange portfolio to reduce the risk of managing net open positions (NOP). This realization aims to answer the question of whether it is possible to optimize the currency portfolio based on different value-at-risk models, including Var, Copula VaR, and Copula CVaR. In this research, on a quantitative scale and observations in the form of time series, the daily logarithmic return percentage of the two main and common currencies in the country's business, including the US Dollar and the EURO, in Sepah Bank from 2013 April 6 to 2021 September 22.The results of the selected portfolio based on these three methods show that, according to the obtained results, the Copula GARCH VaR model has a higher Sharpe value than the other two methods. On the other hand, the results of the average Sharpe obtained from the portfolios on the efficient border between the three methods are presented, according to the obtained values, we find that there is a significant difference at the 95% statistical confidence level between the average of the three methods presented, during which the Copula model GARCH VaR is ranked higher.

Objective:

 The pricing and valuation of initial public offerings (IPOs) are the subject of extensive literature in finance, primarily focusing on well-documented pricing anomalies such as IPO underpricing and significantly abnormal post-issuance returns. The use of peer company information to value IPOs has received attention due to their signaling role. Among the things that can be compared in the field of peer companies is the quality of their accounting information and financial reporting. Due to the lack of accounting information related to IPOs, practitioners rely significantly on comparable Peer Accounting Information when attempting IPO Valuation. Firms desiring to obtain capital through an IPO depend on more accounting information than their own when transitioning from a relatively opaque to a relatively transparent information environment, such as the accounting information of their priced peers. According to these cases, this research aims to present the model of the effect of the degree of group similarity, the quality of accounting information and the quality of financial reporting on the valuation of the initial public offering of shares using the algorithm of artificial neural networks.

This research is practical in terms of purpose and data collection method; it is ex-post facto research in accounting proof research. The statistical population of this research includes 92 companies listed on the Tehran Stock Exchange between 2012 and 2020, which uses the multiple regression method to test the hypotheses. The degree of similarity of the quality of accounting information of the supplier company with the peer group has been calculated and tested separately using three indicators of abnormal accruals, profit predictability and profit stability. Also, considering that artificial network patterns can be used to predict the valuation of an initial public offering of stocks and probably have different powers, this research compares the power of three algorithms (firefly algorithm, machine regression algorithm, decision, and tree algorithm).

The comparable companies' approach to pricing IPOs depends largely on the availability of accounting information from peer companies already priced in the market. However, to be most effective, peer accounting information should be useful in making decisions about how to use the accounting information of peer companies. The results showed that the valuation of shares in an initial public offering is possible based on the degree of similarity of the companies in the group and the quality of the accounting information. Stock valuation in initial public offerings based on profit and sales approaches differs in terms of the similarity of group companies and the quality of the company's accounting information. Group companies and the quality of accounting information aren’t associated with incorrect pricing (overvaluation and undervaluation) in initial public offerings. The results of neural networks also indicated that the firefly algorithm has a higher power to predict the initial public offering valuation than the machine regression algorithm; the firefly algorithm had a higher power to predict the initial public offering valuation than the tree algorithm. The decision tree algorithm is more likely to predict the valuation of the initial public offering of stocks than the support vector machine regression algorithm.

in the comparison between valuation theory and practice (use of information of peer companies), the second view is more effective, and the accuracy of information of peer companies is a key component of pre-publication estimates of the accuracy of information of IPO companies, and the information set of an IPO, it is not limited to its own accounting information, but also includes the information of its peers. Given that companies often decide to offer their initial shares when they think they can maximize their equity earnings (such as when they feel their stock is overvalued or during periods of booming stock markets and heightened investor sentiment), the results of this research can be used by potential investors to reduce the effect of underwriters' incorrect valuation and to monitor them, especially in the emotional stock market; Therefore, it is suggested that buyers of shares of companies that are listed on the stock market for the first time should consider the accounting information and quality of financial reporting of similar and peer companies, especially the quality of accruals and the predictability and stability of their profits; because it contains information about the future price estimation of initial supply companies. Underwriters and initial price estimators are also suggested to consider the quality of accounting and financial reporting of their peers in estimating the initial price of initial public offering companies. In the end, due to the higher power of the Firefly algorithm to predict the valuation of the initial public offering of stocks compared to the vector machine regression algorithm and the decision tree, it is suggested to use these algorithms for valuation due to the lower error.

The aim of this research is to compare the performance of the value-at-risk model with the liquidity-t-copula approach with dynamic conditional correlation (t-copula-GARCH-LVaR) with the value-at-risk (VaR) model to optimize the portfolio in the Tehran Stock Exchange. In the current research, in order to test the desired hypotheses, the period is between 2001 and 2021. All the variables used in this research on a quantitative scale and observations in the form of time series are the daily logarithmic returns of 40 stock market indices, including 39 industry indices and one index of fixed-income bonds from the beginning of September 2011 to the end of July 2021. In this research, to perform the final analysis, all the calculations required for this research were done using the open-source software R 4.2.1. Our results showed that the t-copula-GARCH-LVaR optimization model performs better according to the Sharpe criterion based on Mann–Whitney U test at the 95% test level.

The purpose of this paper was to assess the overall risk in various financial sectors, including banking, insurance and investment companies. Pervasive risk in general indicates the possibility of collapse of the entire financial system in a crisis. While in most cases, investors in different markets worry about losing the value of a stock or commodity and measure the risks involved, the risk is pervasive, focused on the market as a whole and likely to fall. In this study, the method of measuring changes in value at risk based on the returns of financial institutions has been used. In this study, statistical information of banks, investment companies and commercial insurances during the years 1380-1399 has been used. The results show that all three sectors during this time period are significantly involved in hedging risk in Iran and investment companies have the largest share in hedging risk, followed by segments respectively. Banking and insurance are included.

The country's tax system consists of various components, the analysis and analysis of each of which will lead to the promotion and increase of the efficiency of the tax system. The process of collecting taxes in the country has generally started from finding a unit and the process of reviewing, identifying and determining taxes, and finally, by paying or protesting against the relevant taxes, the tax process has been completed, which ultimately leads to fraudulent government tax collection. In this direction, there are several problems and challenges facing the tax system from the beginning of the process to the end, and counting these problems and solving them will improve the tax system. The method used in this study is field. The statistical population of this study includes people working in the tax organization, the Society of Certified Public Accountants and university professors, and the statistical sample used in this study was 157 people.. The research findings showed that; Risk management in the tax administration is affected by the risks of tax laws, tax litigation, tax collection, human resources, information technology, administrative health, risk - based auditing, noncompliance, tax incentives, tax evasion, tax audit quality, The quality of the tax audit, databases, knowledge and Skills, power, relationships, and the risk of outsourcing tax processes are at stake.

Credit risk is the probability of default of the borrower or the counterparty of the bank in fulfilling its obligations, according to the agreed terms. In other words, uncertainty about receiving future investment income is called risk, which is of great importance in banks. The purpose of this article is to estimate the credit risk of individual and corporate customers. In this study, the statistical information of 400 individual customers and7500 corporate customers was used. In this regard, the results of neural network model and support vector machine model have been compared. The obtained results have shown that the components considered in this study based on their personal, financial and economic characteristics had significant effects on the probability of customer default and credit risk calculation. Also, the results of this study showed that the application of control policies at the beginning of the repayment period suggests facilities that have the highest probability of default with long life and high repayment. The comparison of the results of the prediction accuracy shows the higher explanatory power of the support vector machine model and the use of the survival probability function than the simple neural network model for both groups of customers.

This research aims to model and present an appropriate pattern in order to forecast systemic liquidity risk of corporate stocks in capital market of Iran. For this purpose, 486 listed companies in Tehran stock exchange and OTC from 2011 to 2020 were sampled and then the companies were divided into four groups (portfolios) according to combination of indicators and types of activites of companies. Then by using types of multivariate GARCH models and comparing them, finanlly the VAR(1)-DBEKK(1,2) was selected as an optimum pattern . The results of research showed significant relationships among of liquidity shocks and volatilities with all of subsections, and consequently the main hypothesis based on “presence of systemic liquidity risk of corporate stocks in capital market of Iran” was accepted. In a way that the portfolios of company stocks with a “low level of liquidity- industry section” and “low level of liquidity- financial section” respectively had maximum and minimum liquidity shocks transmission of effects on future returns of the other portfolios, as well as the portfolio with a “high level of liquidity- financial section” had maximum volatility persistence and liquidity risk transmission to other portfolios.

Trade and relations between countries are a necessary condition for the financial convergence. With this approach, the present study investigated the impact of the Iranian stock market on the stock market of Iran's trading partner in the MENA region. for this purpose, information about the total stock market index of selected countries was collected during September 2015 to June 2022 and index fluctuations calculated using wavelet analysis. Next, the VAR model was estimated and the Granger causality test was performed. Finally, the effect of the news on the country's stock market was investigated using GARCH models. The results of wavelet analysis showed that, the range of stock market fluctuations in MENA countries has increased. Based on the results of the VAR model and Granger causality test, Iran's stock market is unilaterally affected by fluctuations in the stock market of trading partner and OPEC member countries, including Kuwait, Oman, Qatar, Saudi Arabia, the United Arab Emirates, and Lebanon. However, there was no sign of Iran's stock market being affected by fluctuations in the stock market of Jordan, Bahrain, Egypt, Tunisia, and Morocco. Finally, the results of the conditional variance models indicate that the selected countries follow a similar asymmetric fluctuation pattern.

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.

Investigating the Effectiveness of Audit Committee on Brand ValueA case study of the food and automobile industryAbstractThe purpose of this study is to investigate the effectiveness of auditing committee on brand value in the automotive and food industry of Tehran Stock Exchange. For this purpose, the size variables of the audit committee, the independence of the audit committee, the expertise of the audit committee and the size of the audit unit were used as the criteria of the audit committee and the cytobein criterion was used as the variable expressing the company's brand value. The results of this study, which were obtained from the financial information of 32 automotive industry companies and 28 food companies during the years 1391 to 1398 and multi-variable regression method, showed that the effectiveness of the auditing committee on brand value in both food industry and automotive industry with different characteristics of audit committee In the short-term and long-term financial periods, there is information content that can be analyzed. In general, the same characteristics of the audit committee as a supervisory criterion cannot explain the brand value of companies.

The purpose of this study was to identify barriers to implementing a risk-based auditing system in Iran. Content analysis was performed using a qualitative method and the statistical population was the community of auditors and members of the community and the Association of Certified Auditors, which was selected by purposive sampling of 20 people. The method of analysis of this research was qualitative and based on the Interpretive Structural Modelling (ISM). Findings show that in this study, the factors are in 9 levels, in the highest level of factors are the emphasis of universities on the theory, complexity of operational and practical implementation of the audit system based on the risk of instructions and the lack of professors. It is dominated by taste management and is at the lowest level of technical challenges. It should be noted that the factors that are at a higher level are less effective and are more affected by the factors at lower levels. These strategies can lead to the adoption of guidelines and the complexity of the operational implementation of the risk-based audit system in an organization.

The use of cryptocurrencies is a creative and technology-based way to circumvent unilateral sanctions against Iran. Due to the importance of this issue, this article was compiled with the aim of designing and validating the pattern of using blockchain technology and cryptocurrencies in the conditions of sanctions. The present study is a cross-sectional survey in terms of applied purpose and in terms of method and time frame of data collection. The statistical population includes managers and senior experts of the Central Bank, the Ministry of Industry, Mines and Trade and the Ministry of Economic Affairs and Finance. The sample size was estimated to be 384 using Cochran's formula and sampling was done by simple random method. The data collection tool was a questionnaire that was validated by structural validity, convergent validity and divergent validity. Using Cronbach's alpha and combined reliability, the reliability of the questionnaire was assessed as desirable. The partial least squares method and Smart PLS software were used to validate the pattern of application of blockchain technology and cryptocurrencies. Finally, the indicators of using blockchain technology and cryptocurrencies were prioritized by Savara method. According to the results, the financial sanctions of the Islamic Republic and the threats of virtual currency are the underlying elements of the model that have a direct impact on risk management. Risk management also affects the technological infrastructure and management of virtual currency information, and thus strategic strategies can be developed.

Creating a value creation chain is essential for those bank customers who have a significant share of financial resources, opportunities and potentials in the financial markets to attract resources, allocate and invest and perform financial and economic activities. This segment of customers includes legal customers, or in other words, companies, public, private and semi-private companies. The purpose of this study is to design an appropriate tool to determine value creation factors and evaluate its validity and reliability. First, using the snowball method, experts, key specialists and customers of the company were identified in the Welfare Bank of Tehran and Isfahan provinces, which according to the theoretical saturation of the researchers, 18 people were interviewed. Then, using their opinions, 61 items of the questionnaire were extracted and by calculating the content validity ratio and content validity index, the number of acceptable items was reduced to 51 items and the reliability of the questionnaire was confirmed using Cronbach's alpha and ICC.

The present study has investigated the contagious risk of turbulence.In this study, the contagious effect of real and virtual currency (Bitcoin) fluctuations has been measured. In this regard, the method of self-regression vector analysis (VAR) and the conditional autoregressive model on the heterogeneity of multivariate generalized variances (MGARCH) have been used.The data used in this study, including the exchange rate of the dollar based on the euro and the price of bitcoin in the period 01/2015 and 2020/01, were collected and examined by the generalized multivariate conditional variance heterogeneity (BEKK) method. The present study is based on the classification of research based on method, nature and direction, respectively descriptive survey, applied and post-event. The results of this study confirm the relationship between the volatility of real currency and virtual currency. In other words, the main hypothesis of the research on the contagion of virtual and real exchange rate fluctuations has been confirmed unilaterally from virtual exchange rate to real exchange rate.

In the past years, financial markets have faced uncertainties such as financial crises, oil shocks, changes in currency policies and similar cases. The statistical population in the current research are financial intermediaries such as insurance, banks, active investment companies (PGPIC) in the stock market on a daily basis in 1990-98. For the insurance market, by increasing one unit of its efficiency, the value at risk of the whole system decreases by 0.016. With the increase of one unit of its yield, the value at risk decreases by 0.051. With an increase of a unit or one percent of profit in the banking sector, the efficiency of the whole system increases by 0.0014. The results of estimating the value exposed to conditional differential risk indicate that the share of value exposed to conditional risk of capital is equal to 0.045, bank 0.026 and insurance 0.037, and the value exposed to conditional risk of capital and insurance sector is more and bank is less, and the share of value exposed to conditional risk of capital equals 0.045, bank 0.026 and insurance 0.037, which means the value exposed to conditional risk of capital and insurance sector is more and bank is less.

The purpose of this article is to predict probability of default of 60 corporations with structural Merton model. we used market data of 60 corporations from 2018/08/01 to 2019/09/01 witch are listed in Tehran Stock Exchange For predicting probability of default . to reach this goal we estimated assets value of corporations, volatility of assets and drift rate. We used Capital asset pricing method to estimate expected assets return. Then We used simple regression method and multivariate GARCH (MGARCH) to estimate Beta of corporations. in the end we compute d likelihood function of the average predicted default for each industry and compared the results with actual default rate of that industry in the next year after predicted date. Regarding obtained results of likelihood function probability of default prediction with multivariate GARCH (MGARCH) approach outperform the simple regression model, therefore we recommend using the MGARCH approach for its better prediction performance.

One of the most important factors in investment and financing in the Muslim community and Islamic countries is the conformity of the type of investment, financing methods and contracts with sharia standards (in Iran, compliance with Imami jurisprudence is considered). In addition, the laws governing transactions and contracts in order to maintain investment security, promotion and economic stability, has been the biggest concern of companies, investors, as well as lawyers and officials. This study examines the jurisprudential, legal and economic aspects of bold Islamic investment, which is one of the ways to finance start-ups with technological ideas in the international market and in most Islamic countries in the last two decades. It is considered and also paves the way for the development and progress of small and medium companies in Iran. The use of this investment procedure requires pathology in various fields, the three main axes of which are jurisprudence, law and economics in this research, using the opinions of experts in two stages in the form of a questionnaire, in a society consisting of legislators. The professors of the seminary and the university and the managers of the knowledge-based companies were interviewed after the calculation of validity and reliability and finally using the survey method as well as hierarchical analysis and selection of three main criteria and 26 sub-criteria was also identified. The research finding is that the investing community in Iran is acutely concerned about the type of contracts and the lack of confidence in adhering to Islamic rules in contracts, property rights, as well as stability in economic indicators. Finally, it offers remedial solutions.

The possibility to renewal of loan contracts in Iran may lead to the identification of fictitious profits by banks and ultimately lead to a banking crisis and disruption of the country's monetary system, so to prevent banks from reaching the stage of this, Measuring customers' credit risk is essential. The aim of this study is to increase the accuracy of customer accreditation using the structure of hybrid models and has been done as a case study on Mellat Bank. In this regard, 14 learning models were compared with each other and their ability to validate customers was determined. Learning models show that based on both accuracy criteria (success rate) and measurement F (harmonic mean between accuracy and recall), the combined learning model (KNN-NN-SVMPSO) - (DL) - (DBSCAN) with an accuracy rate of 99.90 is the highest It has more performance than other basic and hybrid models. Also, using the principal component analysis (PCA), Gini index, interest rate ratio (IGR) and interest rate (IG) methods to calculate the weight of features and their average rank, it was shown that features such as collateral, The type of collateral and the amount of facilities have been the most important features in distinguishing good from bad customers, respectively.

The purpose of using risk-based auditing is to increase the efficiency and effectiveness of auditing, because by determining the type and nature, timing and scope of content tests in a reasonable way and with the ability to be fully responsive, the reviews are done to the appropriate extent. The result of the time spent changes to a more logical level. In the general audit plan, in case of reliance on internal control system, content tests are limited and in case of non-reliance on internal control system, more extensive content tests are predicted and performed. The purpose of this study was to identify barriers to implementing a risk-based audit system in Iran. For this purpose, 200 experts were selected from the auditing experts who constitute the statistical population of this study. This selection was done randomly and data were collected from samples. For this purpose, using the confirmatory factor analysis method, the reliability and validity of the questionnaire were first investigated and then the model considered for this study was evaluated and analyzed through the structural equation method. After the analysis, it was found that the questionnaires and collected data were completely approved in terms of structure, validity and reliability, and final analyzes could be performed based on them. Through the analysis of structural equations, it was found that the final model has a significant relationship and the model is confirmed that this model is the result of a qualitative analysis extracted through the ISM model.

Examination of macro indicators and the level of economic development shows the inefficiency of financial markets. A limited portion of GDP is devoted to investing in the production of goods and services, and a significant portion of it is absorbed in speculative activities in unproductive financial markets. The present study has modeled the performance of financial markets using system dynamics. For this purpose, first using the financial markets data of gold, land and construction, capital market, bank deposits, market dynamics and financial consequences of investing in markets were examined. The financial markets dynamics model was designed and after model validation, simulation was performed on a ten-year horizon (1408-1398). According to the behavior of variables and model sensitivity analysis, financial market development policies including "capital market development", "liquidity reduction monetary policy", "land and building market organization" and "gold market organization" are identified and identified separately. The model was applied and the results of comparison and behavior were analyzed. According to the model findings, hybrid policies have been presented as the best policies for the development of productive financial markets based on the dynamics of Iran's financial markets.

This study presents a model of group companies degree and accounting information quality effects on initial public offering valuation in companies listed in Tehran Stock Exchange. To test hypotheses, data is collected from 77 companies listed in Tehran Stock Exchange for an eight-year period from the beginning of 2011 to end of 2018 and then statistical tests are performed.The valuation of shares in initial public offering is possible based on group companies similarity and the quality of the accounting information. Stock valuation in initial public offerings based on profit and sales approaches differs in terms of similarity of group companies and the quality of the company's accounting information. Similarity of accounting information quality adjusts effects of group companies on initial public offering valuation.  Stock valuation based on group companies and the quality of accounting information are associated with incorrect pricing (overvaluation and undervaluation) in initial public offerings.Accounting information is a part of information an investor uses to predict future cash flows to achieve the estimated value of stocks.