amir mohammadzadeh

The present study examines the application of deep learning in forecasting option pricing under the stochastic interest rate and stochastic volatility model. In the stochastic interest rate model, the interest rate of financial products is randomly determined at different times. This randomization causes volatility in prices and interest rates. In this research, characteristic function, Monte Carlo simulation and conditional Monte Carlo simulation are used to generate data. Monte Carlo simulation is used as a random and probabilistic method to obtain statistical results and predictions related to option pricing by generating data that belong to the characteristic function. since the financial markets contain a lot of data, in order to be able to manage this data as a financial expert and make decisions based on it, one must master the science of deep learning. The tools available in deep learning and finance affairs are also used to determine and predict the option price under the stochastic volatility model and stochastic interest rate model. Results show that the efficiency of deep learning models, in terms of time and accuracy, compared to traditional methods such as Monte Carlo method is more. The results of this research can be used as a practical tool for investment decisions and risk management.

This study examines the impact of blockchain technology on the banking industry and identifies the indicators and applications of this technology using the meta-synthesis method. The findings include 28 indicators: preventing fraud, reducing banking costs, ensuring security and transparency, identity management, and strengthening the capital market. The results show that blockchain can facilitate domestic and international transactions and increase the productivity of the Iranian banking system. The research method is qualitative and applied, and a seven-step meta-synthesis process was used in data analysis. This study provides a valuable tool for banking planners by identifying key indicators. There are limitations, such as generalizability to other organizations and using the meta-synthesis method. Still, the research is valuable regarding innovation in theoretical foundations and methodology and can guide the development of blockchain technology in banking.

The present research aimed to study the relationship of threat-rigidity, entrepreneurial orientation and signaling (The risk taking behavior theories) with performance of the companies listed on the Tehran Stock Exchange with respect to the moderating role of the risk management committee. However, according to the Article 2 of the Audit Committee Charter approved by the Stock Exchange and Securities Organization, one purpose of the audit committees is risk management and improvement of internal controls; As a consequence, audit committees of the companies were considered as risk management committees. The statistical population of the research consisted of the all companies listed on the Tehran Stock Exchange during 2013-2022. Eighty-two companies were selected as the sample of the study. The hypotheses were tested using linear regression model and Eviews software was used to perform the tests. The research results showed that according to the threat-rigidity theory, the companies' performance decreased with the companies' debts and debt financing. However, according to the entrepreneurial orientation theory, the companies' performance increased with earnings uncertainty risk. Study of the risk-taking behavior based on the signaling theory showed that there was not a significant relationship between capital intensity risk and the companies' performance. The additional findings showed that risk management committee does not moderate the relationship between risk-taking behavior (financial leverage risk, earnings uncertainty risk and capital intensity risk) and the companies' performance.

In Iran, the subject of taxation on intellectual property (IP) has not yet been introduced by the government or the Tax Administration. However, due to the significant volume of these assets in the Iranian economy and their trade and transactions, taxation on them is an inevitable necessity. As a result, the issue of taxation on intellectual property rights is being extensively discussed in academic and professional circles. Intellectual creations and social credits, such as inventions and trademarks, although difficult to create, are easily imitated, reproduced, and distributed with industrial and mechanical means. Consequently, the financial and economic benefits of intellectual property are often enjoyed by imitators and duplicators. Without proper support for creators, they may be unwilling to share their knowledge and assets. Therefore, intellectual property rights are recognized in most countries

Tax , as the most important source of governments revenue, plays a special role in financing governments. Although some countries, such as Iran, do not pay as much attention to tax revenues as they deserve due to access to alternative benefits such as oil, but they emphasize and acknowledge the essential role of taxes in their budget structure and are looking for ways to increase their potential tax capacities. Despite the efforts made in recent years to develop the country's tax system, the country's tax system is still facing many challenges. One of these challenges is fair tax collection, which plays an important role in taxpayers' tax compliance. The purpose of this article is to provide a model for the fair collection of the country's taxes. Since no model has been presented for the fair collection of taxes in the country, in this article, by analyzing the writings related to the fair tax collection and among the 180 searched sources, 30 reliable sources were selected in this regard, and by using the qualitative approach and the meta-composite method of collection characteristics, tax fairness is presented to provide a basis for designing such a model. By analyzing these sources, 7 concepts and 46 codes for fair tax collection have been obtained.

The purpose of this research is to investigate the impact of the outbreak of the Covid-19 disease on the financial restrictions and dividend payment policy in government and non-government companies admitted to the Tehran Stock Exchange. The research method is descriptive-correlative in terms of its applied purpose and in terms of its nature and method, and the data collection method is library and archival. The statistical population of this research includes all the companies accepted in the Tehran Stock Exchange from 2016 to 2021 and according to the considered conditions and limitations, 151 companies were selected as the statistical sample of the research. By using two multivariable regression models and with the help of a combined data model, the research hypotheses were tested and the results showed that the outbreak of the Covid-19 disease has a positive and significant effect on the financial limits of the companies admitted to the Tehran Stock Exchange, as well as the spread of Covid-19 has had a negative and significant impact on the dividend payment policy of companies listed in the Tehran Stock Exchange. The extent of the impact of the outbreak of the Covid-19 disease on the financial restrictions and dividend payment policy of government and non-government companies of the Tehran Stock Exchange has been different.

The late Triassic metabasites in the southeast of Borujerd area in the middle part of Sanandaj Sirjan zone (SaSZ) are associated with marble and locally intersected by mafic dykes. Metabasites rocks are metamorphosed in the lower green schist facies and are mainly composed of plagioclase and amphibole. However, they locally preserve ophitic and porphyritic igneous textures. The electronmicroprope analysis showed that feldspars are albite, oligoclase and anorthoclase. Also, according to this analysis, type of amphiboles is calcic and includes actinolite, actinolite-hornblend, magnesiohornblend and tschermakit-hornblend to tschermakit. According to geochemical studies, these rocks have alkaline magmas characteristics. The chondrite normalized REE patterns show enrichment in LREE and the Primitive-Mantle normalized multi-element patterns show uniformly enriched LREE, Th, Nb, Ta. These characteristics are similar to those of basalts derived from OIB-like mantle sources. Trace-element ratios, including Ce/Nb (1.22– 2.20), Hf/Nb (0.08–0.2), Zr/Nb (3.63–6) and high TiO2/Yb and Nb/Yb ratios, indicate that these magmas were derived from a deep OIB reservoir, i.e. an enriched asthenospheric mantle source. These rocks underwent slight crustal contamination. These geochemical characteristics of these late Triassic metabasites suggests that they formed in an intra-continental rifting regime.

This article examines the relationship between investment opportunities and the message of future stock profitability.

In order to investigate the subject and test the research hypotheses, linear regression models and 1500 data of company-year observations in the time return of 2007 to 1399 companies listed on the Tehran Stock Exchange have been used.

The results show that managers of companies with poor investment opportunities, instead of holding cash, distribute profits among investors. They invest positive value and distribute more dividends to shareholders next year to avoid the unintended consequences of reducing dividends. Also, changes in dividends in companies with strong and weak investment opportunities make it possible to predict changes in companies' future profits in the coming years, but the previous power is not significant.

The findings of this study show that changes in dividends contain information about the amount of investment opportunities facing the company.

cooperative and stock companies play an important role in the country's economy. On the other hand, one of the most important and extensive financial researches is the explanation of the return in these companies. In the financial literature, identifying the factors influencing the return has always been of great importance. Based on this, the aim of the current research is to model returns in agricultural cooperatives and companies listed on the Tehran Stock Exchange.The current research is a quantitative research that is practical in terms of the type of goal. Also, it belongs to the group of descriptive and survey research. The statistical population of the research is all the cooperative companies active in the field of agriculture and all the companies accepted in the Tehran Stock Exchange. It includes 154 stock exchange companies and 52 agricultural cooperative companies.The research results showed that in both types of cooperative and stock exchange companies, size, profitability and leverage have a significant relationship with return. In companies listed on the Tehran Stock Exchange; The sentiment factor has no significant relationship with the return. The profitability factor has a positive and significant relationship with the return. The factor of value, size and leverage has a negative and significant relationship with the return. In agricultural cooperative companies; company size, return on asset, current ratio have a significant and positive relationship with return, and leverage has a negative and significant relationship with the return.

Therefore, in the present study, a model for stock portfolio optimization based on a combination of GARCH-copula models in the Tehran Stock Exchange was presented. The present study is in the group of descriptive-correlational researches in terms of practical purpose and data collection method. Also, the statistical sample of the study includes 50 more active companies in the fourth quarter of 1398. For this purpose, the monthly stock return information of these companies was studied over a period of 10 years between 2011 to 2020, and therefore the number 120 rows of observations for each company are the basis of the analysis. The findings of this study show that that the Garch-Copola EVT method has the necessary efficiency to form a portfolio. In terms of risk criteria, it can be seen that this method has presented the lowest risk among the existing methods, and these results confirm the relationship between risk and return in investment activities. Although in this method, a smaller return is obtained than other methods, but the risk will be lower for the investor. Therefore, it can be accepted that this method has been effective in order to optimize the stock portfolio. Comparing the performance of this method with the uniform weights method, it can be seen that the Sharpe ratio in the portfolio with uniform weights was significantly larger than this ratio in the Garch-Copola portfolio. Therefore, it seems that in terms of Sharpe's criterion, the uniform weights method performed better than the proposed method and this method did not have an acceptable efficiency in improving the performance of the portfolio compared to the uniform weights method. Although based on the Sharpe criterion, this method has shown the worst performance among the portfolio formation methods, but in terms of the risk criterion, it can be seen that the risk of this portfolio is significantly lower compared to other methods. Therefore, it can be accepted that the formation of the portfolio using the Garch-Copola EVT method has been able to reduce the portfolio risk compared to other methods.

Intangible assets are defined as non-monetary assets that do not have physical substance but possess economic features that grant rights and advantages to their owner. The role of digital applications in this century can be compared with the function of oil in the past century with was the driving force for growth, wealth, and change. The Covid-19 pandemic has led to the rapid growth of digital services in Iran, and many companies have included digital development in their plans. However, the valuation of these companies poses many difficulties, and introducing the national information network in Iran will add to the importance of evaluation even further.This may lead to an underestimating of the book value of enterprises with extensive intangible assets. Intangible assets are usually difficult to evaluate, and the International Valuation Standard 210 recommends three approaches: (a) an income approach; (b) a market approach; and (c) a cost approach. However, generating accurate results can be challenging. This study innovatively apply traditional approaches to digital intangible assets and combines them with a customer-perspective value to provide more precise results for decision-making and suggest new valuation pattern. To this end, one of the large companies providing digital services in Iran was selected for evaluation, and the results are presented. This pattern is practical and can be implemented for all companies providing digital services in Iran.

This article surveys the fundamental value of digital platforms, such as Instagram and Google. Despite the commutable nature of digital technologies, it is challenging to value digital services, given that the usage is free of charge. Applying the methodology of discrete choice experiments, we estimated the value of digital free goods. For the first time in the literature, we obtained data for the willingness-to-pay and willingness-to-accept, together with socio-economic variables. The customer’s valuation of free digital services is on average, for Google, 4.9m Rial per week and Instagram, 3.27. This paper corroborates that Instagram and Google have an intrinsic value to users, despite the fact that the service of the digital platforms is free of charge. This is the beginning of the valuation of free services such as Shad, Rubika, Zarebeen, etc. in Iran, which has played a significant role in the communication industry since the beginning of the Covid-19 pandemic, and in the discussion of the national information network, the market value of the provider companies will be very important.

To assess the added risk of acute endophthalmitis after intravitreal injections associated with the widespread use of face masks during the COVID-19 pandemic.

In this retrospective, single-center study, records of patients with acute endophthalmitis following intravitreal bevacizumab (IVB) injections during the pre-COVID era—that is, March 1st , 2013 to October 31st, 2019 —and the COVID-19 era—that is, March 1st, 2020 to April 1st, 2021 —were reviewed and compared.

A total of 28,085 IVB injections were performed during the pre-COVID era; nine eyes of nine patients developed acute post-IVB endophthalmitis in this era, giving an overall incidence of 0.032% (3.2 in 10,000 injections). In the COVID era, 10,717 IVB injections were performed; four eyes of four patients developed acute post-IVB endophthalmitis in this era, giving an overall incidence of 0.037% (3.7 in 10,000 injections). The incidences of post-IVB endophthalmitis during these two eras were not statistically significantly different (P = 0.779).

Face masking protocols seem unlikely to impose any additional risk of post-IVB endophthalmitis.

Environmental problems and global warming are one of the biggest concerns of societies. Using renewable energy generation technologies as one of the most basic solutions is one of the main concerns of planners and beneficiaries of power grids, considering the variability of their output power day and night and their dependence on weather conditions. The uncertainty caused by these generations can have many effects on the costs imposed on the grid and the operation of electricity grids, such as an increase in power outages and energy not supplied. To solve this problem, a comprehensive multi-objective and probabilistic model has been proposed to determine the installation location, type, and optimal capacity of DGs in the modern supply chain of electricity. The final objective of this model is to minimize energy losses, investment and operation costs, energy not supplied, and environmental emissions. The proposed methods have been implemented by MATLAB software on the Garver power grid and IEEE 33-bus distribution grid and solved by the multi-objective NSGA-II. The final model can be effectively used to plan the supply chain of the modern electricity grid with the influence of renewable energy-based products in various economic, environmental, and social dimensions.

Globalization and, consequently, intensifying the competition between banks and financial institutions in domestic and foreign financial markets increase significantly the importance and requirement of strengthening and modifying systems in financial enterprises. Banks are no exception. Credit risk assessment is one of the most significant components of the granted facilities process. Small and medium enterprises are the majority of customers of commercial banks; hence, it is possible that designing a credit risk system considerably helps banks to manage credit risk.This study aims to introduce a new approach to predict and assess the credit risk of small and medium-sized enterprises. To this end, we identified the indices effective on the credit risk of medium and small-sized enterprises and determined significant indices by selecting the feature. We selected 98 cases of medium and small-sized legal clients in the industrial sector for research data from one of the commercial banks during the years 2018-2020. We then implemented the logit regression models, artificial neural network, and hybrid model (fuzzy expert system, logit, and artificial neural network) in order to predict and assess customers' credit risk and also calculated the accuracy of the models. Ultimately, we have designed the program applying visual studio software. We calculated the customer using logit regression models, artificial neural network, and hybrid model according to the designed program by inserting each customer's information and we also determined credit rating and type of collateral of each customer based on customer risk.

The goal of this research is to identify the effects of oil, dollar and gold prices on the capital market; and meanwhile the investors’ Behavioral Biases.

The same research is a qualitative study of phenomenological type. Field data were collected using in-depth interviewing techniques and theoretical saturation criteria among 10 active participants of Tehran Stock Exchange who have at least three years of experience in investing in financial markets. After the implementation of the analysis phase using the Colaizzi method and MAXQDA10 software, the recorded interviews have been conducted.

Based on data analysis, seven main themes including external factors, parallel markets, cognitive biases, emotional biases, abnormal phenomena (in behavioral economics) as well as cultural and personal factors were extracted from the interviews. The results emphasize on the need for taking measures to predict exchange rates and avoid government-mandated pricing.Key words: Currency, Gold, Oil, Behavioral Biases, Capital Market

This study predicts Price of stocks in the short term by using the analysis of investors' opinions of the social network. The predictability of stock markets, due to having a complex, dynamic and nonlinear system that it has always been one of the challenges for researchers. The effect of users' feelings on the social network and its combination with 20 technical indicators on the accuracy of stock price forecasting. The study period is from the beginning of April 2016 to the end of March 2017 (two years). To access sufficient data, a sample of 14 active companies that had the most comments and posts. Data mining of technical indicators was performed and support vector regression was used to predict. The results show that the use of technical indicators is more accurate compared to combining it with the aggregation of users' emotions and has less RMSE errors. The number of comments has a significant correlation and the results of Granger causality test showed that it is possible to use the aggregation of users' daily emotions to predict stock prices.

Due to these discussions and complications, the issue of tax on intellectual (intellectual) assets has not been raised by the government and the tax organization in Iran. But due to the significant amount of these assets in Iran's economy as well as their trade and commerce, taxing them is necessary and unavoidable. It is on this basis that the topic of tax on intellectual property rights is widely discussed in expert and scientific circles. The purpose of this research is to identify the effective factors on the capacity of tax revenues arising from intellectual property rights using multifaceted foundation data theory.This research is applied in terms of purpose and qualitative in terms of method, which was carried out using the grounded theory method. The method of data collection, library studies and in-depth interviews with 20 experienced university professors and experts of the country's tax affairs organization through targeted sampling until the saturation point is discussed. The validity of this research was examined and confirmed by the interviewees and then expert professors. Reliability was also obtained using the retest reliability method of 91%. To analyze the data, the continuous comparison method was used during three stages of open, central and selective coding.Data analysis showed that political, functional, organizational factors as causal factors; Organizational ability, organizations and organs, management, as categories; Systemic, human, structural, national factors as background factors; organizational, process, economic factors, as intervening factors; Technical and society factors, as organizational and national strategies and consequences, were identified and extracted as the consequences of factors affecting the capacity of tax revenues arising from intellectual property rights, which by creating an arrangement of causal conditions, contextual and intervening conditions, action strategies and consequences around The central category will help to create a complete and comprehensive understanding of the existing problem and solve it.The unique role of research and development in production, development and economic growth of countries is undeniable. In all developed countries, significant investments are allocated to the field of research and development, which has resulted in many social benefits for these countries.

One of the characteristics of the financial market, especially the stock market, is the effects of behavioral factors and on other financial and non-financial markets. There are several factors that affect the return of a stock exchange. We can refer to political, socio-cultural, technological and finally economic factors. A stock market is an economic market in which securities are traded under specific rules and regulations. Accordingly, in this study, the effect of behavioral financial arguments and other financial markets on stock market returns based on quantitative analysis has been studied. This article tries to examine how exchange rates, gold, and oil as key factors of a model can explain fluctuations of the stock market index. so the effect of those variables on the stock market index in the period 2008 to the first six months of 2018 has been analyzed using the FIAPGARCH-X model. The results of the analysis show that the effect of exchange rates on the stock market fluctuations is greater than the other two factors. The results also indicate that there are asymmetric effects of increased returns on the stock market, which is consistent with behavioral bias in behavioral finance.

We reported a case of corneal perforation due to longstanding exposure keratopathy treated successfully with lamellar corneal patch graft, conjunctival flap, and lateral tarsorrhaphy. A 75-year-old male presented with ocular pain and decreased visual acuity in his right eye since 2 weeks ago. On external examination, lagophthalmos in the right eye was evident. Visual acuity was hand motion on slit-lamp examination. 2×3 mm perforated area in the right cornea accompanied by adjacent corneal melting and diffuse punctate epithelial keratopathy were observed. The anterior chamber was flat. Intraoperatively, a 7×2.5 mm-diameter corneal patch graft was fashioned manually; its thickness was reduced and placed over the perforated area, successfully sealed the cornea, a partial bipedicle conjunctival flap was also applied over the graft, and lateral tarsorrhaphy was performed. Four weeks after surgery, Corrected Distance Visual Acuity (CDVA) improved to Counting Finger (CF) 20 cm. The lamellar corneal patch graft was intact without a leak, and the conjunctival flap was partially removed retracted. Corneal perforation can occur in patients with severe exposure to keratopathy, and corneal patch graft is a good option when a sizeable corneal perforation (≥3 mm diameter) is not amenable to corneal gluing.

The purpose of this study was to investigate that behavioural factors play an important role in decision-making and subsequently formation of markets phenomena.

The population of this study consist of all companies listed in The Tehran Stock Exchange of various industries and groups and samples were collected between the years 2007 and 2017. Using regression analysis, we estimated the influence of institutional investors anchoring bias on the 52-week highest price by the cross-sectional regression model, as well as measuring the effect of increasing proximity of price to the 52-week highest price next abnormal returns in parallel with controlling of the other factors over PEAD.

Given the statistically significant anchorage coefficient, it can be stated that there is a significant relationship at a 95% confidence level between the anchorage bias and the abnormal returns resulting from the profit declaration. Also, the level of institutional ownership has a significant relationship with the abnormal returns of profit declarations. In institutionally-owned companies, the role of the anchor variable is not even significant. However, in companies with low institutional ownership, this role is positively significant with a 0.13 coefficient.

Anchoring bias plays a minor role in explaining the additional returns resulting from the profit declaration in companies that are institutionally owned. Therefore it can be said that the first hypothesis of this research on the minor effect of anchorage variable in case of low institutional ownership is confirmed.

This study predicts the future movement of stock prices in the short term by using the analysis of investors' opinions on the social network. The predictability of stock markets, due to having a complex, dynamic and nonlinear system that it has always been one of the challenges for researchers. In this research, for the first time, we developed a model with 72.08%accuracy for predicting stock movement and predicting the trend by analyzing the feelings of users' opinions and combining it with 20 technical indicators and we use three data mining algorithms include decision tree, Naïve Bayes and Support Vector Machine. According to the results, the support vector machine showed better performance than the other algorithms. It was also found that the next day trading volume and the number of comments have a significant correlation and the results of Granger causality test showed can be used to predict stock price and also it took advantage of the aggregation of users' daily emotions.

We live in an age characterized by the very rapid rate of financial innovation. The study of the historical evolution of progress and economic development of developed and industrialized countries shows that one of the main factors in the emergence of rapid and massive growth has been the existence of financial reforms in these countries. There are different incentives for individuals and active enterprises in the financial system to perform financial innovation, which is one of the most important incentives, the introduction of tools and methods to reduce, eliminate or manage existing risks. One of the most important tools the current situation that can help banks in the optimal management of consumption and prevention of claims. Designing and applying credit risk assessment models in granting facilities. The purpose of this study is to provide a suitable model for financial innovation based on credit risk measurement of SMEs in commercial banks. In this regard, effective indicators on the credit risk of SMEs were identified by using the genetic algorithm method and logit, neural network and fuzzy expert system were evaluated. The results show that the using the hybrid model has more accurate results in the assessment the credit risk of SMEs.

Today, because of increasing immigration and the prevalence of drug‑resistant tuberculosis in Iran, identifying intra‑community cases is necessary in the country. It will be possible through the use of molecular epidemiologic methods. In this inquiry, in order to determine the role of immigrants in the transmission of specific strains to Iran, the studies have been examined which had been conducted based on molecular epidemiologic methods among Iranians and non‑Iranians people.

All studies from 1997 to the end of March 2017 were examined in three databases of PubMed, Scopus, and Google Scholar and finally, 16 studies were selected.

The common clustering rate between Iranians and non‑Iranians was determined to be 19.8, and the intra‑community recent transmission rate was from 0% to 49% with average of 18.1%. The rate of multidrug‑resistant tuberculosis (MDR‑TB) was 12.5%, which was higher among immigrants, especially Afghans, and a significant number of the strains were Beijing.

The studies have shown that migrants, especially Afghans, are more effective in transmitting specific strains of tuberculosis to migratory areas. To control tuberculosis, it is necessary to register of immigrant’s health information, while enter to the country, so that, by doing appropriate diagnostic tests, the curing the patients, the transmission of tuberculosis to the country would be prevented.

Literature review shows that investors in Tehran Stock Exchange behave on murmur, unscientific information and confirm on few members in market that called Herding behavior in addition to on mathematical method. This research aims to present a model to introduce and quality and quantity variables on herding behavior in Tehran stock exchange depend on literature review. This research is exploratoryby descriptive and survey method. We choose 190 investors in this market for example and they answered to online questionnaire. The answers analyzed by SPSS22 and AMOS18 in SEM method. The results showed our model have eligible practice to delineate relationship between variables and specified that there are significant direct and mediator relationship between personalities, cultural variables, risk taking and herding behavior.