The primary goal of option pricing theory is to calculate the probability that an option will be exercised at expiration and assign a dollar value to it. Options pricing theory also derives various risk factors or sensitivities based on those inputs, since market conditions are constantly changing, these factors provide traders with a means of determining how sensitive a specific trade is to price fluctuations, volatility fluctuations, and the passage of time. In this study, we derive a new exact solution for pricing European options using Kurganov-Tadmor when the underlying process follows the constant elasticity of variance model. This method was successfully applied to nonlinear convection-diffusion equations by Kurganov and Tadmor. Also, we provide computational results showing the performance of the method for European option pricing problems. The results showed that the proposed method is convenient to calculate the option price for K=3,β=(-3)/4,and N=200.
Measurement of Bitcoin Daily and Monthly Price Prediction Error Using Grey Model, Back Propagation Artificial Neural Network and Integrated model of Grey Neural Network(مقاله علمی وزارت علوم)
One of the recent financial technologies is Block chain-based currency known as Cryptocurrency that these days because of their unique features has become quite popular. The first known Cryptocurrency in the world is Bitcoin, and since the cryptocurrencies market is a contemporary one, Bitcoin is currently considered as the pioneer of this market. Since the value of the previous Bitcoin prices data have a non-linear behaviour, this study aims at predicting Bitcoin price using Grey model, Back Propagation Artificial Neural Network and Integrated Model of Grey Neural Network. Then, the prediction’s accuracy of these methods will be measured using MAPE and RMSE indices and also Bitcoin price data for a five-year period (2014-2018). The results had indicated that wen estimating Bitcoin daily prices, Back Propagation Artificial Neural Network model has the lowest absolute error rate (5.6%) compared to the Grey model and the integrated model. Additionally, for the monthly prediction of Bitcoin price, the integrated model, with the lowest absolute error rate (9%), has a better performance than the two other models.
Iran's economy has been suffering from the dominance of fiscal policies and financial repression for many years, so that this issue has become one of the structural challenges of the country's economy. Banks, as one of the most important parts of macroeconomics, play an important role in the mechanism of transferring monetary policy to the real sector of the economy. Monetary policy transmission operates through various channels: the lending channel, the balance sheet channel, and the capital channel. Examining how the role of banks in monetary policy transmission is affected by government fiscal repression policies provides useful information for monetary and financial policymakers and banking activists. In this study, we tried to investigate the effect of financial repression on the monetary policy transmission through the lending channel of the country's banks. First, an indicator for the financial repression variable was defined using the PCA method, and then the relationship was estimated using the SVAR method and instantaneous response functions and using seasonal data for the period 1999- 2017. The results show that financial repression policies have a significant effect on bank lending and reduce banks' lending power. This issue, along with the negative real interest rate of bank facilities, causes a decrease in the profitability index and loss of banks.
The purpose of this paper is to provide an overview research on the hedge fund performance. In the first step, we review recent studies and put them into a joint evaluation of hedge fund performance. Stressful market conditions have a negative impact on HF performance in terms of alphas as the majority of HF strategies do not provide significant excess returns. This study examines the performance of hedging funds that are active in the world and evaluates the feasibility of its creation in Iran. for the first time, the international data of hedging funds from Barclay hedge, Eurkhedge, database during the last 20 years were examined. The statistical population of the present study was international hedging funds during the years 2000 to 2020. The sample size according to the screening method and after removing the pert observations is equal to 150 international hedging funds. In this study, Spss, Amoz, Lisrel software were used. Has been. The results of hedge fund data analysis using multivariate regression at 90% confidence level show that there is a significant and positive relationship between AUM and fund returns. Other research results also show that cost stickiness has a positive effect on the efficiency of hedging funds.
Investigating the Relationship between Earnings Management and the Stock price bubble of the Firms Accepted in Tehran Stock Exchange(مقاله علمی وزارت علوم)
Capital market is considered one of the most important channels in appropriating the financial resources optimally, and any disruption occurs in it will encounter the appropriation of financial resources in the economics of each country with a serious problem. The economic bubble is one of the reasons disrupting capital appropriation. Generally, when there is a difference between the price of a share and its expected price in the future, the economic bubble issue is considered. The economic bubble will face investors by choosing the best investment opportunities. It will finally deviate the process of equipping and appropriating the resources optimally from its principled path. The present study aims at investigating the relationship between earnings management and economic bubble. To achieve this purpose, the number of 109 companies has been studied from 2008 to 2018. The study's hypothesis was tested through a multivariate regression method and panel data method and utilizing Eviews9. The findings show a significant relationship between earnings management and economic bubble, which shows that besides the external factors, the managers' behavior may influence the generation of the economic bubble.
Development of data envelopment analysis model for financial and social evaluation of companies based on stock returns and accounting value(مقاله علمی وزارت علوم)
Corporate social responsibility has long attracted the attention of academics, researchers, NGOs, and the government, and has become an important aspect of corporate operations. Increasing the globalization of business, increasing the strategic importance of stakeholder relations and the growth of corporate image management are the three key factors and the main driver in increasing the importance of corporate social responsibility. Data envelopment analysis is a well-known methodology that is applied to evaluate the selected firms based on the most important features. Therefore, in this research, it is important to examine the social responsibility of companies with emphasis on stock returns and accounting value. For this purpose, information related to the member companies of the stock exchange during a ten-year period from 2010 to 2020 after performing the necessary statistical tests using linear regression and EViews 10 and SPSS 26 software to test We addressed the hypotheses. In this research, multivariate regression method has been used as a statistical method. The results show that there is no relationship between social responsibility and accounting value, but social responsibility has an inverse and significant relationship with corporate stock returns.
The effect of information disclosure on market reaction with meta-analysis approach(مقاله علمی وزارت علوم)
The present research aims to conduct meta-analysis of the effect of information disclosure on market reaction. In order to integrate the results of different researches and identify the determinants of relations between information disclosure and market reaction, we used meta-analysis methodology as a quantitative statistical method. To perform the meta-analysis method, the scientific magazines all over the world (the published papers relating the research variables from 1990 to 2020) were identified and gathered as statistical population and. As a result, 86 studies were analyzed using systematic removal. The results of the relating studies published during this period indicate that most of these studies are heterogeneous. By classifying these studies based on different measurement criteria of information disclosure and market reaction and also by calculating the intragroup statistics along with identifying the factor of this heterogeneity, we found that these diverse measurement criteria used in the mentioned studies are considered as contradiction factors in research results. We also found that there is no meaningful relation between Non-financial information component, company cycle, type of industry and company size with market reaction whereas there is a meaningful relation between financial information and market reaction.
Moderating effect of managerial ability in the relationship between Corporate governance features and financial distress likelihood: (PLS Approach)(مقاله علمی وزارت علوم)
The purpose of this research is to examine the effect of ownership structure and audit features on the financial distress likelihood by considering the moderating effect of managerial ability. This study utilized partial least squares structural equations modeling (PLS-SEM) analysis and data from 107 firms listed in the Tehran Stock Exchange. Audit features measured by auditor size and audit opinion and ownership structure measured by the block-holder ownership and institutional ownership. Backward logit analysis was used to calculate the financial distress likelihood. DEA technique and Tobit regression were used to measure the managerial ability. The results of the study show that audit features have a positive effect on the likelihood of financial distress. Moreover, the effect of ownership structure on the financial distress likelihood and the moderating effect of manage-rial ability were not confirmed. This paper offers evidence on the extent to which distress is associated with corporate governance and managerial ability from a developing country. The paper should be of interest to the regulatory bodies and practitioners because in many developing countries the implementation of corporate governance mechanisms is voluntary and is not yet required.
Determining the interest rate on deposits in the Iranian banking system: cooperative or competitive game between the central bank and followers?(مقاله علمی وزارت علوم)
This paper studies the monetary policies of the central bank to determine the inter-est rate on deposits in the interaction with the Iranian banking system in the form of Stackelberg and Nash equilibrium games. The leader of the game is the central bank of the Islamic Republic of Iran, while the followers of the game include three banks called A, B, and C. The leader of the game regulates its monetary policies based on the relationship between inflation rate and interest rate on depos-its in the form of three scenarios of "legal deposit ratio", "legal deposit award rate", and "the rate of commissions received" from the followers. The follower players also determine "the interest rate on deposits," based on the scenarios of the leader player. The results of this research (2010-2019) by MINITAB Soft-ware indicated that in the studied year (2019), the strategy of the players of this game has been mostly Nash (more competitive) rather than cooperative. If the players of this game had chosen cooperative strategy (Stackelberg game), they would have achieved greater profit. Also, the optimal tool for the monetary policy of the leader and follower players has been the “increasing the legal reserve re-ward rate".
The Relationship between Risk and Return on Financial Assets (The Panel Vector Auto-Regression and Panel Cointegration Ap-proaches)(مقاله علمی وزارت علوم)
In this study, considering the necessity and importance of the relationship between risk and return on investment, some explanations were presented about the relationship between risk and return on the asset portfolio including gold, exchange and stocks during the period 2001: 1 - 2018: 3 using panel vector auto-regression (PVAR) method and Kao and Pedroni panel cointegration approach and pooled mean group (PMG) method and Engel-Granger time series methods. The software used in this study involves EVIEWS 10 and STATA15. In this study, multivariate GARCH (M-GARCH) approach (BEKK) was used to extract portfolio risk. The results showed a positive relationship between risk and return based on PVAR approach. And also, given the beta coefficient of the CAPM equation, gold was the best inflation cover during the period under study, with a slight difference from the exchange rate.
Integration of Liability Payment and New Funding Entries in the Optimal Design of a Supply Chain Network(مقاله علمی وزارت علوم)
In recent years, the supply chain network design (SCND) problems that integrate financial issues have attracted the attention of managers and researchers. In this paper, in order to address an SCND problem, a mixed-integer nonlinear programming (MINLP) model developed that considers operational and financial decisions simultaneously for designing a deterministic multi-echelon, multi-product, and multi-period supply chain network. The developed model provides the possibility of opening or closing facilities at every time period to adapt to market fluctuations. The model also considers bank loans, liability repayment, and new capital from shareholders as decision variables, therefore, it provides an accounts payable policy for the company managers. In addition to common operational objectives(profit/cost) and constraints, we also applied the economic value added (EVA) index to measure the financial performance of supply chain and lower and/or upper limit value for financial ratios to ensure the company's financial health, while making decisions at strategic and tactical levels. To show the model applicability, data of a case study in the literature employed and solved using BARON solver in GAMS software. The results clearly show an improvement in the total value created for the company compared to the base model, so it can be applied as an effective decision tool.
Identification and Refinement of Effective Factors of Financial Reporting Transparency of Firms Listed on Iran Stock Exchange(مقاله علمی وزارت علوم)
This study aimed to identify effective factors of financial reporting transparency (FRT) of companies using knowledge analysis and selected the final effective factors from them using the ANP analytic network process. In this regard, 16 professors and pundits in financial and reporting areas were selected as the experts. Then, these factors were assessed, refined, and categorized in three survey stages using Delphi method. First, 20 factors were extracted from the literature review based on the knowledge and content analysis: institutional ownership, independence of the board of directors, the lack of ownership concentration, size of the board of directors, information quality, information accuracy, profit fluctuation, sales margin, return on assets, return on investment, asset turnover, company value, competition, age of company, size of company, technology, current ratio, quick ratio, cash flow and asset liquidity. Further, the identified factors were categorized, assessed and refined based on the survey results from the experts’ opinions using Delphi and ANP analytic network process methods. Results showed following 10 out of 20 factors, identified using the content and knowledge analysis, as the effective factors of FRT: institutional ownership and independence of the board of directors (corporate governance mechanisms), information accuracy and profit fluctuation (financial analysis), return on assets and return on investment (financial performance), competition and age of company (environment), and cash flow and asset liquidity (liquidity).
Cash Holding Adjustment Speed: The Role of Managerial Ability and Moderating Role of Political Connections in Tehran Stock Exchange(مقاله علمی وزارت علوم)
Optimal cash is an amount of cash that balances benefits of cash holding; and the speed of cash holding adjustment is called the rate of actual cash response to the optimal cash. The question of how fast companies compensate for excess or inadequate cash to the optimum level in terms of how closely they hold cash flow and maximize company value has been an important topic of interest for academics and managers in recent years; and they have examined factors affecting the speed of cash holding adjustment. Since company managers play important roles in firm's key decisions such as cash holding, the present study investigated the impact of managerial ability as an important management feature on the speed of cash holding adjustment to an optimal cash flow and study as well as the moderating effect of political connection. To this end, data of on companies during 2013 to 2018 were analyzed using econometric software (Eviews), multivariate linear regression. Results of statistical tests indicated that the managerial ability decreased the speed of cash holding adjustment to an optimal level if the cash rate of a company is higher than its optimal level. Furthermore, In companies with political connections, the negative relationship between managerial ability and the speed of adjusting cash holdings towards the optimal level is higher than other companies.
Identifying and explaining the topics in the financial literacy training using fuzzy Delphi approach(مقاله علمی وزارت علوم)
The purpose of this qualitative research is to identify and explain the topics in financial literacy training in Iran using an exploratory approach. For this purpose, 20 semi-structured interviews with experts were conducted in the first stage to identify the topics of financial literacy training, and 36 primary categories were identified in the open coding stage using qualitative content analysis. The identified sub-categories were linked in the axial coding stage and categorized into nine axial categories. In the next step, namely selective coding, the identified central categories were systematically categorized into three general chapters. In the second stage, the fuzzy Delphi technique in two phases was used to achieve group consensus between experts and screening the findings of the first stage. At this stage, the most consensus between the experts was reached in 32 topics. Based on the results, all areas of personal finance are covered under three general topics, including income and savings management, risk management, and cost management. The topics extracted in this study can be utilized to design, codify, and implemented financial literacy training programs in Iran.
The purpose of this study is to develop a prediction-based stock returns and portfolio optimization model using a combined decision tree and regression model. The empirical evidence is based on the analysis on 112 unique firms listed on the Tehran Stock Exchange from 2009 to 2019. Regression analyses, as well as six decision tree techniques including CHAID, ID3, CRIUSE, M5, CART, and M5 are used to determine the most effective variables for predicting stock returns. The results show that the six decision tree methods perform better than the regression model in selecting the optimal portfolio. Further analysis reveals that the CART model outperforms the other five decision tree models when compared using Akaike and Schwartz Bayesian. This finding is confirmed by comparing the actual returns of the selected portfolio across all six models in 2019. The findings indicate that the predicted returns on portfolio based on the CART model are not significantly different than the actual returns for 2019, suggesting that the selected model appropriately predicts the returns on the portfolio
Experimental Comparison of Financial Distress Prediction Models Using Imbalanced data sets(مقاله علمی وزارت علوم)
From machine learning perspective, the problem of predicting financial distress is challenging because the distribution of the classes is extremely imbalanced. The goal of this study was comparing the performance of financial distress prediction models for the imbalanced data sets with different proportions. In this study, the data of the previous year before financial distress was used for 760 company year for the time period of 2007-2017. Besides using traditional classifications such as logistic regression, linear discriminant analysis, artificial neural network, and the classification models of least square support vector machine with four kernel functions, random forest and the Knn algorithm, the measures of the area under the curve and Friedman and Nemenyi tests were also utilized to determine the average rank and the difference significance of the Auc of the models. For selecting the models´ optimal parameters, the combined method of grid search optimization and cross validation was used. The results of this experimental study showed that for the balanced and imbalanced datasets with lower proportions, the best performance was for the random forest. For more imbalanced datasets, the best performance belonged to the least square support vector machine with sigmoid, radial, and linear kernel functions; performance of Knn algorithm had no significant difference from the other models and the performance of the artificial neural network was average or appropriate. Also, the performances of the linear logistic regression and linear discriminant analysis were weaker than other nonlinear models.