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Advances in Mathematical Finance and Applications - Volume:8 Issue: 1, Winter 2023

Advances in Mathematical Finance and Applications
Volume:8 Issue: 1, Winter 2023

  • تاریخ انتشار: 1401/11/17
  • تعداد عناوین: 20
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  • Aram Sepehrivand *, Abolghasem Hashemipour, Isa Taheri Pages 1-22

    Economic freedom or economic liberty is one of the instances of freedom which is a target intrinsically, and individuals and units make attempts to achieve. The liberalization of financial markets can have a different effect on economy. Several studies have indicated that economic liberalization has had a positive effect on developing economies by the reduction in capital expenditures, increase in profit-ability, and individuals’ investment. The present study aimed to investigate the effect of economic freedom on stock returns. The statistical population of this study is the selected countries of the Organization of the Islamic Conference (OIC) for the years 2001 to 2019, and is used in the statistical section of the Fraser Institute website and the World Bank website. In this study, the regression model of panel data was employed for data analysis. The research results show that the effect of the economic freedom variable is positive and significant on the stock price index and cash-on-cash return. At best, economic freedom can lead to increasing demand for stocks and, subsequently, raising the stock price index and cash-on-cash return. The government should provide a legal and regulatory framework to protect the rights of owners of assets and fair implementation of contracts, and facilitate access to sound money. It should also provide stable money and refrain from activities and interventions interfering in personal choices, exchanges and voluntary exchanges, and the free-dom to enter the competition in product and labour markets.

    Keywords: Stock Return, Economic Freedom, Organization of Islamic Cooperation (OIC)
  • Reza Tehrani, Ali Souri, Ardeshir Zohrabi *, Seyyed Jalal Sadeghi Sharif Pages 23-45
    The issue of asset pricing in the market is one of the most important and old issues in the financial world. Factor pricing models seek to be able to determine a significant relationship between return on assets based on the risk parameters of that asset. A wide range of factors can be found in the literature that can be an element for measuring the risk of an asset, but the big question is which of these models will work better. The factors studied in this research include factors that cover market risk, valuation risk, psychological (technical) market risk, profit quality risk, profitability, investment, etc. In this study, we have tried to Using machine learning techniques and optimization tools is a way to derive adaptive-robust nonlinear models that can reduce the risk of model error as much as possible. In this research, two models have been developed. In the first model, using the feature extraction technique and optimization of models based on neural network, a non-linear and adaptable model has been developed for each asset. In the second approach, a portfolio of improved neural network-based models is used in the first stage, which can be used to minimize the risk of model error and achieve a model that is resistant to different market conditions. Finally, it can be seen that the development of these models can significantly improve the risk of error and average error of the model compared to traditional CAPM approaches and the Fama and French three-factor model.
    Keywords: Asset pricing Model, Machine Learning, Neural network, Gray Wolf Optimization
  • Hossin Sharifirad, Negar Khosravipoor *, Sina Kheradyar, Mohammadreza Vatanparast Pages 47-61
    investors and managers are always faced with uncertainty in the information environment, which uncertainty can be due to factors such as the synchronization of stock returns, extraordinary fluctuations in stock returns and the number of equations. The purpose of this study is to investigate the political uncertainty caused by the size of the firm under the influence of risky information environment, the irregular behavior of accruals anomaly and the anomaly behavior of the cost of normal stock equity of companies. For this purpose, the data of 99 companies listed on the Tehran Stock Exchange and Iran TSETMC during the years 2009 to 2019 were examined and tested through combined data. The results showed that the political uncertainty caused by the firm size affected the concurrency stock returns with the optional accrual anomaly behavior and the cost of normal stock equity behavior of companies has a positive and signification relationship. The results also showed that the political uncertainty caused by the firm size is affected by the extraordinary fluctuation of stock returns with the optional accrual anomaly behavior and the cost of normal stock equity behavior of companies has a positive and signification relationship. In addition, the political uncertainty caused by the firm size is affected by the number of equations with the optional accrual anomaly behavior and the cost of normal stock equity behavior of companies has a positive and signification relationship.
    Keywords: Political Uncertainty, Firm Size, Accrual Anomaly, Normal Stock Anomaly Cost
  • Fatemeh Pouraskari Jourshari, Mohsen Khodadadi *, Seyed Reza Seyed Nejad Fahim Pages 63-74
    The portfolio selection problem is one of the main investment management prob-lems. In the portfolio selection problem, robustness is sought against uncertainty or variability in the value of the parameters of the problem. This paper has been conducted for Robust portfolio optimization based on the mean-cvar approach. And introduces the linear mean-cvar model as a criterion for calculating risk and provides an optimal Robust mean-cvar model. Robust approach used in this research is the Bertsimas and Sim. In this approach, Robust counterpart presented for a linear programming model remains linear, maintaining the advantages of the linear programming model in the optimal model. The model developed in this research is randomly selected by real data of 20 stocks of the S&P 500 index for three years, this development help portfolio selection problem to consider uncertainty. Interval optimization is modeling approach to consider parameters uncertainty in this paper. Considering uncertainty make model more realistic. The results of model show that this approach has computational efficiency and on the other hand proposed model produce better solution in risk and portfolio rate of return point of view
    Keywords: Robust Optimization, Mean- CVaR, Linear model, Uncertain
  • Hossein Dalvand, MohammadHasan Maleki *, Hossein Jahangirnia, Mojgan Safa Pages 75-94

    One of the biggest shortcomings of urban spaces in most cities of the country is the lack of suitable sports spaces, which in addition to improving the health of the general public, especially the youth, creates a lively environment and can boost the development of the tourism industry. Many projects in the country, especially sports, are slow or stopped due to not evaluating the relevant risks, so the purpose of this study is to identify and prioritize investment risks in the country's sports projects. The present study is a positive research in terms of philosophical foundations and is applied in terms of orientation. The statistical population of the study includes experts in the field of sports tourism and the sampling method has been done judgmentally. To conduct the research, in the first stage, the risks of investing in sports projects were assessed through literature review. The number of these risks was 15, and after screening with a Binominal test, 6 factors were excluded. The remaining 9 factors were evaluated in terms of degree of impact with Dematel technique and 5 factors, i.e. market risks, economic risks, legal risks, financing risks and stakeholder conflict risks were selected as the most effective risks in terms of net effect index. Finally, these 5 risks were ranked by Aras decision technique and it was observed that the economic, market and financing risks, had the highest priority.

    Keywords: Risk, investment, Investment Risk, Sports Project, Tourism
  • Fatemeh Taheri, Mohammad Setayesh *, MohammadHasan Janani, Mahmoud Hematfar Pages 95-115

    Banks as the largest financial intermediaries play a vital role in collecting savings and directing them toward manufacturing activities. Hence, assets and liabilities management is crucial for them and their depositors. In this study, through system dynamics approach, a dynamic model was proposed to manage assets and liabili-ties optimally. After building the model and conducting validation and sensitivity analysis, three scenarios were devised and were simulated and analyzed via the proposed model. The results revealed that taking effective decisions and actions to collect more deposits, especially time deposits as well as increasing the quality of credit assets (if allocated optimally) can be effective in improving the performance of banks. Therefore, using systems thinking and system dynamics can aid banks in managing their assets and liabilities optimally. mary of the significant items in the paper, including the results and conclusions.

    Keywords: System Dynamics, Credit assets, Systems thinking, Asset management, Liability management
  • Fatemeh Karamiverdi, Farhad Dehdar *, Esmail Alibeiki, MohammadMehdi Hosseini Pages 117-136

    The purpose of this study is to evaluate the most effective strategic implica-tions of green accounting based on the function of sustainable reporting. In this study, theoretical screening based on similar studies was used to identify the components (strategic consequence of green accounting) and research propositions (themes of sustainable reporting function). Then, in order to determine the reliability of research components and propositions through the participation of 12 experts and experts in the field of accounting and financial management, Delphi analysis was used. In the quantitative part, the identified components and propositions in the form of matrix questionnaires were evaluated by interpretive analysis by 17 managers of the top 50 companies in 2009. The results showed that the proposition of sustainable responsibility as the most influential theme of the sustainable reporting function causes the effectiveness of the value consequence in green accounting. This result shows that by developing the dimensions of social responsibility in sustainable reporting, the level of inclusive values in the value functions of green accounting is strengthened and builds trust and confidence in the company's performance.

    Keywords: Green Accounting Strategic Consequences, Sustainable Reporting Function, Interpretive Prioritization Ranking
  • Mohammad Noroozi, Daruosh Foroghi *, Farzad Karimi Pages 137-156
    The occurrence of unexpected phenomena in recent decades in financial markets around the world,led to the development of theories,beyond the defined principles and criteria of classic finance.These theories are based on financial psychology and they are explaining the role of psychology in financial sciences as an influential factor and became irreplaceable in financial markets and investor decisions.One of the important theories in this field is the bounded-rationality-theory,which can explain the behavior of decision-makers about financial and economical issues based on defined theoretical frameworks and assumptions.This study developed the stock pricing model by comparing the predicted stock price based on the bounded-rationality-theory and the real stock price through collecting the data of 122 companies listed on the Tehran Stock Exchange during the period 2011to 2019.The results of this study show the effectiveness of the bounded-rationality-theory based on the separation of stock return components and measuring the irrationality coefficient and emotional reactions of investors' decisions in stock prices.Accordingly,the limitations of investors 'ability to process information seem to affect the level of use of reasoning and rationality in decision-making and the effect of bounded-rationality through the irrationality and limited attention on stock pricing.Therefore,it is expected that knowledge about the process of bounded-rationality based on the rational-bounded of investors and the behavioral biases resulting from the irrational part of their thinking,will provide a good explanation for the process of changes in financial markets.This can provide both profit opportunities and costs in investment management so that it can be used in modeling,analysis and investment strategies.
    Keywords: bounded rationality, Behavioral Finance, Stock Pricing Model, Investors' Sentiment
  • Sharifeh Soofizadeh, Reza Fallahnejad * Pages 157-172
    Bank efficiency is essential in the establishment of healthy financial systems in countries. In this respect, bank managers are expected to respond correctly to questions raised about the financial performance of banks, which is practically impossible without examining the efficiency of the branches under their oversight. In most previous studies, Data Envelopment Analysis was used for evaluating the efficiency of financial branches. The large number of evaluation factors in the analysis leads to an increase in the number of efficient units and thus a decrease in the power of discrimination. Taking a systematic view into consideration, in this study, a step-by-step method was developed for selecting the effective factors in the efficiency of different branches of one of the Iranian Banks based on the effect of each factor or indicator on the whole system’s efficiency including the branches under evaluation. To this end, a new method was proposed for the evaluation of system’s efficiency and some of its properties were stated.
    Keywords: Financial assesment, Modified Russell measure, Variable Selection
  • Mohsen Azhdar, Mohsen Dastgir *, Saeid Aliahmadi Pages 173-186
    The main role of financial reporting in capital markets is to provide the necessary conditions for the optimal allocation of resources and making correct and timely decisions. Achieving this goal is possible if the financial statements are consistent with economic realities or even have the slightest deviation from economic performance. However, over the past few decades, fraud detected in corporate financial reporting has increased the risk of financial reporting. Therefore, the current paper aims at investigating the impact of internal control weaknesses on financial reporting risk in companies listed on the Tehran Stock Exchange. In order to achieve the purpose of the research, using the method of systematic elimination of information related to 143 companies among the companies listed on the Tehran Stock Exchange in the period from 2009 to 2019 was collected. A multivariate regression model based on composite data was used to test the research hypothesis. The research findings show the significant positive impact of internal control weaknesses on financial reporting risk. The results indicate that reducing the weaknesses of internal control can reduce the risk of financial reporting and reduce information asymmetry and consequently improve accountability processes.
    Keywords: Financial reporting risk, Internal control weaknesses, Quality of accruals
  • Fatemeh Saatichoubar, Mohammad Mohebbi *, Yaghoob Zeraat Kish, Ebrahim Negahdari Pages 187-202
    Profit is one of the most important factors influencing economic decision making, the changes of which depend on various factors. Banks, as one of the most important business units, have a special reliance on the concept of profitability and their performance is significantly influenced by macroeconomic conditions. Government economic policies are placed. This paper aims at applying the panel regression model to study the effect of monetary policy on the profitability of banks from 2006 to 2018 using data from 30 provinces to find appropriate policy recommendations for decision-making in the banking system. The research method was the use of GMM regression technique in the context of combined data. According to the results, the performance and profitability of banks are improved by the implementation of expansionary monetary policy. However, bank lending and price inflation have a negative effect on banks' performance. According to the results of this study, control variables such as the amount of overdue claims and GDP also had a positive effect on the performance of banks. Also at the macro level, with regard to the negative effects of Expansion monetary policy and the growth of liquidity, with the controlled implementation of Expansion monetary policy, it helps to improve the performance of banks in the banking system.
    Keywords: Monetary Policy, Banking Performance, Combined Data Regression, GMM
  • Mohammad Moradi, MohammadSadegh Horri *, Iraj Nouri Pages 203-218

    The objective of this study is to present a framework to increase the return and profitability and reduce credit risk of Mellat Bank customers by developing the RFM model. In this study, which was conducted as a case study in Mellat Bank of Iran, first the variables of RFM model were identified. In the next step, relevant weights of RFM variables were calculated using AHP technique. In the next step, using the K-means algorithm, customers were clustered based on weighted RFM and extended RFM. The result included customer clusters. The results indicated that the three clusters 5, 1, and 7 obtained the highest scores for receiving facilities and the coefficients for receiving facilities were equal to 0.271, 0.173, and 0.556, respectively. By determining the facility coefficient for the cluster and consequently for the customers presented in these top groups, granting facility becomes more transparent and more purposeful, and therefore, it will help the company increase profitability, reduce the churn among high-efficiency customers, and create value for customers. This research demonstrates a systematic method for granting facilities to recognize the true value based on the capability and prevention of arbitrary acts

    Keywords: profitability, Credit Risk, Customer, RFM Model
  • Saba Salimi *, Mohsen Shahriari Pages 219-240
    The complexity of the competitive business environment has highlighted the need to be aware of the organization's strengths and weaknesses and to continuously improve processes. Therefore, managers are looking for a solution for performance measurement of their organization to be able to promote and improve their organization. Evaluating the performance of listed companies in the stock exchange organization is important because in addition to the managers of the organizations, stock traders can also evaluate the companies and make the necessary decisions about holding, selling or buying the shares of these companies in a timely manner. One of the organization's performance measurement solutions is to use financial ratios. Given that a separate study of financial ratios does not provide a correct view of the efficiency of the organization, so the aggregation of the effect of financial ratios seems to be effective. DEA and MCDM are suitable because they enable the achievement of performance index by considering several factors simultaneously, so the performance obtained from this method is reliable. the main purpose of this study is to ranking pharmaceutical companies in the Tehran Stock Exchange between the years 2018 and 2020 using DEA approach and MCDM to provide a single ranking through the Copeland method.
    Keywords: Efficiency, Data envelopment analysis, Multi-Criteria Decision Making
  • Neda Kiani, Ghasem Tohidi *, Shabnam Razavyan, Nosratallah Shadnoosh, Masood Sanei Pages 241-254
    Nowadays, the rapid growth of data in organizations has caused managers to look for a way to analyze them. Extracting useful knowledge from aggregation data can lead to appropriate strategic decision-making for the organization. This paper suggests an application of hybrid network based on amount month demand in every ATM device based on transaction mean of 9 months for 1377 devices to obtain customer behavior patterns, to do so, first designed a basic model based on an auto-regressive with exogenous input network (NARX) then, the optimization of the weight and bias of the designed network is made by the genetic algorithm (GA). As a result, finding the weights of the network represents a nonlinear optimization problem that is solved by the genetic algorithm. Paper results show that the NARX-ANFIS Hybrid network using GA for the learning of rules and to optimize the network weights and weights of the network and the fixed threshold can improve the accuracy of the prediction model. Also, classic models are more efficient and increased benefits and lower financing costs and more rational inventory cash control. As well, the designed model can lead to increase benefits and decrease costs in the bank so that, exact forecast and optimal cash upload in ATMs will lead to increase funds on the bank and rise customers and popularity the brand of the bank.
    Keywords: Prediction model, autoregressive with exogenous input network, Genetic Algorithm, ATM device
  • Marzieh Ahmadi, Saied Sehhat *, Maryam Khaliliaraghi, Hashem Nikoumaram Pages 255-272
    Financial markets play a key role in economic development, and the insurance industry as a financial institution can be the bedrock of economic growth. Thus, risk and performance appraisal are very important in the insurance industry. There are several methods for evaluate risk and efficiency in financial markets, but since the performance of insurance companies is different from other financial institutions for the risk acceptance of other organizations and individuals, it is necessary to rank factors affecting efficiency and risk in insurance companies separately based on the performance of companies prior to focus on the calculation method. This paper discussed factors affecting the financial risks of insurance companies and efficiency and their rankings using the Delphi qualitative method and collecting expert’s opinions as well as data from domestic and forign papers. The statistical population of the research is experts and specialists in the field of risk and insurance. Spss, Eviews and Excell 2013 were used to review the questionnaires and estimate the results. The results of this paper identified the factors affecting each of the risks of financial wealth, liquidity, credit, operations and efficiency, and in the ranking obtained through Friedman test, efficiency is the highest rank, followed by liquidity, operational and credit risk in the rankings.
    Keywords: Wealth Risk, Operational Risk, Credit Risk, Liquidity Risk, Efficiency, Ranking
  • Ali Afruozianazar, Nader Rezaei *, Zohreh Hajiha, Asghar Pakmaram Pages 273-285
    Services are important major element of the economy in today's societies, and banks as one of the most important service organizations direct and support many of the community's economic activities. The purpose of this study was to develop an optimal model for East Azarbaijan banks' performance based on organization risk management using the standardized questionnaire of Kosovo 2017. In order to achieve this purpose, the director or assistant director, head or deputy head, bank managers and experts of banks were selected for statistical sampling and structural equation Modeling approach was used for estimating the model and tests. Organizational risk management factors including "written job descriptions and resources to describe personnel duties, fraud risk assessment with regard to how management and other employees participate" were assessed as factors af-fecting bank performance. Therefore, the structural problems of the banking sys-tem should be resolved so that this system can function and develop in the future, and consequently, in order to resolve the crisis of the banking system, it is neces-sary to reform the banking system.
    Keywords: Enterprise Risk Management (ERM), Banking Performance
  • Kiamars Fathi *, Majid Rashidi, Mahmoud Modiri, Sayedeh Mahboubeh Jafari Pages 287-303

    The increase in non-performing loans considerably reduces profit in the banking systems. To solve these problems, factors influencing the collection of non-performing loans have to be examined in a hopeful attempt to reduce it to an ac-ceptable level. The present study is conducted to analyze and study factors influ-encing the collection of non-performing loans in Shahr Bank. This research is an applied study regarding its goal. It was conducted in two sections, namely the qualitative and quantitative sections. In the qualitative sections, the factors influ-encing the collection of receivables were identified using the theoretical literature and interviews with senior managers of Shahr Bank through the encoding process. In the quantitative section, data was collected by surveying the opinions of 12 experts, including senior managers of Shahr Bank in 2020 using a questionnaire. Thereafter, the factors were selected using the fuzzy Delphi technique and the relationships between them were determined using the fuzzy DEMATEL method. Finally, the factors were weighted and prioritized using the fuzzy ANP method. The research findings showed that non-performing loans can be collected through six types of factors including organizational, regulatory, customer, banking, envi-ronmental, and operational factors. The environmental factor is the most influential factor, while the operational factor is the most influenced and most important factor. In addition, behavioural, contextual, and structural sub-factors have the highest level of importance in the collection of non-performing loans in the order mentioned. These findings can help bank managers make decisions to improve the collection of receivables.

    Keywords: Bank, Non-performing loans, Fuzzy multiple-criteria decision-making
  • Shadi Khalil Moghadam, Farimah Mokhatab Rafiei *, MohamadAli Rastegar, Hamed Aghayi Bejestan Pages 305-317

    Managing a single portfolio is a basic assumption in the most of research. However, in reality, an advisor manages many accounts at the same time; therefore, there is a significant dependency among portfolios and correlation between decisions on one portfolio with the performance of others, so the results of multi portfolio is different with classic models (single portfolio management, that portfolios are optimized independently) due to market impact and the trade dependency of one account to the other accounts. We propose a structural model to optimize accounts simultaneously, considering interdependences, decision’s correlation and mutual behavioral effects of managed portfolios. Moreover, to compare and analyze both single portfolio and multi portfolio approaches, real data from Tehran Stock Exchange in 1398 are used and model is solved with GAMS. Results indicate that multi portfolio optimization excel other approach and consequence notable improvement on the perspective of customer and advisor. Also, for the validation of the proposed model, the selected stocks are considered in pairs to solve the model and the results show the proper performance of the model with different stocks, thus indicating the validity of the model.

    Keywords: Mult portfolio optimization, Market impact, Tehran Stock Exchange
  • Sayyed MohammadReza Davoodi *, Sayyede Elnaz Afzaliyan Boroujeni Pages 319-335

    Designing trading systems with good returns is critical for capital market investors. Trading systems are often based on a combination of several tools to use their combined information. For the first time in Iran, the present study aimed to propose a pattern detection algorithm for a flag pattern based on Japanese candlestick charts and their arrangement. By recognizing the pattern and if the 4- and 10-day moving average is confirmed, a shopping position is developed, and the selling time is determined based on an optimized and dynamic process commensurate with price changes and the data scale. Our objective was to address the question of whether the returns resulting from this strategy have a more significant positive return compared to the purchase and maintenance strategy. The research sample included the daily information of 16 active companies of basic metals in Tehran Stock Exchange during 2007-2019, extracted from the database of Novin Rahavard software. Data analysis was performed in MATLAB software, and the obtained experimental evidence was described using t-test. According to the results, the research strategy had a higher performance in terms of returns and risks compared to the market.

    Keywords: Particle Cumulative Algorithm, Optimization, Japanese Candlestick, ChartFlag Pattern Detection, moving average
  • MohhamadReza Mozafari *, Marzieh Ghasemi, Farhad Hosseinzadeh Lotfi, Mohsen Rostamy-Malkhalifeh, MohammadHasan Behzadi Pages 337-350

    Allocating fixed costs with undesirable data has recently been one of the most important issues for managers to discuss. Lack of attention to undesirable data may lead to incorrect cost allocation. Considering and determining undesirable inputs and outputs, data envelopment analysis (DEA) technique can be significantly helpful in determining the cost allocation strategy. In-puts and outputs are divided into two desirable and undesirable groups. Obviously, desirable inputs and undesirable outputs must be reduced and undesirable inputs and desirable outputs must be increased to improve performance. This manuscript presents two strategies for allocating fixed costs with undesirable data. In the first strategy, each decision making unit (DMU) first determines the minimum and maximum shares that it can receive from the fixed resources while the efficiency of that DMU and other DMUs re-mains the same after receiving the fixed resources. Finally, the decision maker chooses the fixed cost for each DMU between the minimum and maxi-mum cost values proposed. In the second strategy, the allocation of fixed costs is done using the CCR multiplicative model with undesirable data. The effectiveness of both methods is examined by an applied study on the commercial banks.

    Keywords: Data Envelopment Analysis(DEA), Fixed costs, Fair allocation, undesirable data