نشریه مهندسی مالی و مدیریت اوراق بهادار
پیاپی 51 (تابستان 1401)

Today, investing in gold markets is an important part of any country's economy, so estimating the price of gold is one of the most important topics of study for economists and financial analysts who have developed different approaches and perspectives. Naturally, methods can be durable and suitable for use that have the least investment error and risk. In developing countries such as Iran, due to inflation and uncertainty about the future, the demand for gold to cover the risk of inflation is high.The formation of the Bahar Azadi coin futures contract market in the Commodity Exchange in recent years has also helped to create an organized market to cover risk and also to use arbitrage opportunities in the gold market. The trading statistics of Bahar Azadi coin futures contract have grown significantly since the entry of its first symbol in the trading table of Iran Commodity Exchange, so that it has created an organized market with high trading volume and appropriate liquidity in the field of derivatives trading in the country. In this study, we decided to use two models of stochastic differential equations (Heston and Merton) to predict the price of futures contracts and compare the results.

Today, due to the expansion of capital markets, it is essential to identify investor behavior and variables that affect stock prices and returns. The purpose of this study is to use the electrification technique to investigate the effects of irregular calendar day, week and month, with the help of returns and non-systematic risk in chemical companies listed on the Tehran Stock Exchange, in the period 2015-2020. The reason for using the electrification technique, which is a new method in financial research based on stochastic dominance analysis, is the existence of problems in both regression methods with virtual variables and Garch model, as well as achieving more realistic results about the effect of calendar irregularities. The findings show that Monday has the highest and Tuesday the lowest returns for investing in the Tehran Stock Exchange. Also, the best time to invest is from May to the end of summer, especially August, and the most inappropriate time is February and December. In addition, the findings show that investing in the second week of each month is a better opportunity than other weeks.

In the present study, he presented a statistical sample related to the information of legal and credit customers of Tejarat Bank, accepted in the stock exchange during the years 1398 to 1399. Using factor analysis technique and Delphi method, the variables affecting credit risk were selected and entered into the data envelopment analysis model, and the performance scores of law firms were obtained using them, and then ranked by the Fitch Institute model. Performing and using the results to predict the movement of customers in different groups using the Markov chain process. The results of data envelopment analysis indicate that 7 companies were identified as efficient in the financial approach and 12 companies in the combined approach. The results of the Markov chain show that the average probability of stopping at the current rank in 1400 in the financial condition is 46% and in the combined mode is 53%, the average probability of improving the situation of companies is 23% and the average probability of falling is 20%.

Monte Carlo Markov chain methods are a set of algorithms for sampling possible distributions based on building a Markov chain with desirable properties. One of the most common Markov Monte Carlo chain algorithms is the Metropolis-Hastings algorithm. Therefore, the purpose of this study is to evaluate the relationship between financial distress and stock returns using the Metropolis-Hastings algorithm in the Tehran Stock Exchange. For this purpose, 151 companies were selected from the Tehran Stock Exchange in the period 2011 to 2020 using systematic elimination sampling method. R software was used to test the research hypotheses. Altman Z and Olson's score were also used to calculate financial distress. Also, in evaluating the relationship using the Metropolis-Hastings algorithm, two different previous distributions for the research variables were used. The results of the study showed that for Altman's financial distress variable, the accuracy of estimating financial distress was higher with the previous non-informed distribution. For O-Olson's financial helplessness variable, the precision of financial distress was higher with Zelner's previous distribution. Meanwhile, in the previous non-informed distribution, the effect of financial distress was not significant and was significant in Zelner's previous distribution.

This study has conducted to assess the role of customer pressure on the company's stock price response to the announcement of participation in green supply chain programs. The present study is applied in terms of purpose and is a survey in terms of how it is performed. The data used in the present study is the available financial information of companies that were listed on the stock exchange during the years 1390 to 1398 and have not been removed from it. The research data were analyzed using control charts and estimation of logistic and linear regression models. The results showed that, as a measure of customer pressure, the type of industry affects the participation of companies in green supply chain management. There will be a reduction in the stock prices of companies by announcing the participation of them in management of the green supply chain. The results also show that in indirect industries where the pressure from customers is more on announcing the company's participation, announcing the company's participation in green supply chain activities will have a lower reducing effect on its stock price

In recent years increase in the speed of information transfer and market connectedness caused markets to convergence and affect each other. Today every shock or volatility from one market affect the other markets. This paper investigates nexus and spillover effect between commodity and Tehran stock index. Time periods of this paper is 12 years starting from the first of 1388 to the last of 1399. We used VAR-BEKK-GARCH Model to measure correlation and spillover effect from two groups of commodities: the first group includes precious metals (gold, silver, platinum and palladium) and second group includes base metals (copper, aluminum, zinc, tin and nickel) toward Tehran overall stock index. Results for the first group (precious metals) show spillover from gold to Tehran overall stock index and volatility spillover from palladium to Tehran overall index. for the second group (base metals) return spillover from copper, tin and zinc to overall index and volatility spillover from aluminum to overall index was revealed. shock spillover was not seen for any groups of precious metals and base metals to overall index.

In the past, attempts have been made to conceptualize all purchases based on the LBO model and through the lens of agency theory. This view of the past has severely limited the ability of financial engineers to create models and tools for entrepreneurship motivation. ETA is a window to revitalize businesses by acquiring small businesses with entrepreneurial capacity instead of starting a start-up business.In this study, according to behavioral, financial, economic, social, and legal indicators, the efficiency degree of entrepreneurship through acquisition models using the non-parametric method of data envelopment analysis based on output-oriented BCC and CCR models from the entrepreneurs and investors' perspectives in the Iranian market. We have demonstrated a comprehensive ranking of the models based on the Anderson and Peterson (A&P) model finally.The results show that based on the output-oriented BCC and CCR models, the crowdfunding model from the perspective of entrepreneurs, and the incubator model from the perspective of inefficient investors. According to Anderson and Peterson model, the optimal model from the point of view of investors is the sponsor model and from the entrepreneurs' view, the self-fund model was considered with the highest efficiency and compliance according to the indicators

The Financial market analysis is an important issue that influences investors' decisions. This paper developed the stock pricing model by comparing the predicted stock price based on the anchoring and adjustment theory and the real stock price through collecting and analyzing the initial information and data of 122 companies listed on the Tehran Stock Exchange during the period 2011 to 2019. The results of this study show the effectiveness of the anchoring and adjustment 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 investmentstrategies.

The impact of public debt on economic growth is recognized as one of the important issues in economic analysis. . Therefore, in the present study, using the annual data of 128 selected countries and the Panel Smooth Transition Regression (PSTR) model, an attempt has been made to investigate the threshold impact of the country risk index on the impact of public debt on economic growth in four separate models over time. 2018-1996 .the findings indicate that, there is a significant nonlinear relationship between public debt and economic growth. However, the estimated models with transmission variables of political risk and composite risk in both regimes indicate that the public debt have had a positive effect on economic growth. Moreover, in the models with the transmission variables of financial risk and economic risk, the impact of the general debt on economic growth was negative and positive respectively in the first and second regime.

Today, some systems such as credit scoring and credit customer rating have been developed to validate customers. The present study is aimed to identify and evaluate the effective factors on the credit risk of real customers of Bank Melli in Iran using Delphi-Fuzzy and Fuzzy -DEMATEL approaches. This research is exploratory in terms of purpose and is descriptive and survey in terms of data collection and analysis. The validity and reliability of the research measure were verified statistically using 20 experts related to the research topic, which was in the form of a questionnaire. A total of 60 factors were identified in 4 main dimensions including personal factors, environmental, behavioral and social factors, credit factors and macroeconomic factors. Later, the model was evaluated, and by re-interviewing the experts through the Delphi-fuzzy technique, 55 factors were finally confirmed. Then, the dimensions and indicators of customers' credit risk were ranked, which was done through the fuzzy- DEMATEL technique. The results of research indicators showed that among the indicators, income index had the highest effect and collateral index had the most impact. Also, among the main dimensions, the personal factor had the highest impact among the factors.

The issue of stock portfolio selection has always been one of the most attractive and practical issues in financial markets. The present article introduces a two-stage model for stock portfolio optimization by using a combination of the six smart beta strategies founded in the literature and fuzzy approach. In this article, first, the six factors of smart beta factores, for 76 pharmaceutical and steel companies active in the stock market, are calculated by using the financial information in the financial statements of 2016 and 2017 and their trading information in the period 2016 to 2017. Then, by combining the six factors of smart beta and fuzzy logic, the final weight of each share in the portfolio is determined. In order to evaluate the model, using SPSS software and Levin statistical test and based on yield information of the mentioned companies, during 2017 year, the difference between the efficiency of the proposed model and the index portfolio based on the market index was discussed. The results showed that at 95% confidence level, a higher profit can be obtained from the portfolio based on the proposed hybrid model.

The first step in risk management in the field of investment is to calculate the variable that explains the risk accurately. One of the most widely used criteria for calculating risk is the value at risk, which has been the focus of financial researchers for the past three decades. Therefore, the aim of the present study is dynamic modeling and variable time using a technique called Generalized Autoregressive Score (GAS) to estimate value at risk in bitcoin and gold by using daily data since 2010 to 2020 and assuming the distribution of t-student. its results are compared with the results of known AR and GARCH models. The results showed that for gold models such as GAS, GARCH and AR were able to estimate the value at risk at 5% error level. Among them, the GAS model had the best performance. For Bitcoin only two models, GAS and GARCH, are suitable for estimating value at risk and GARCH model is preferable. Also, the duration of risk of value at risk errors for all three models for gold and bitcoin lacks long-term memory, indicating its reliance on financial turmoil.

The aviation industry is one of the strategic, technology-based, and capital-seeking industries. One of the most important challenges in this industry is proper financing. On the other hand, crowdfunding is one of the new methods of financing, which is based on Web 2. It has expanded today in various fields, including business and technology. However, due to its characteristics, this method requires proper design and adaptation to the intended industry to be implemented in a specific industry, so this article seeks to design a crowdfunding model in the aerospace industry. To design an appropriate model, first, a systematic review of the literature and empirical studies of crowdfunding platforms in the world and Iran was used, and then using semi-structured in-depth group interviews with experts to accurately determine stakeholders, models, and components of crowdfunding in The field of aerospace industry was addressed and the final model of mass financing for the aviation industry was designed. Findings showed that the crowdfunding model in the aviation industry has 5 stakeholders including platforms and social networks, founders, investors (funders), financial institutions, and legal and regulatory institutions. The components are involved in crowdfunding include law, project, campaign, benefits, communication, proximity, dissemination, and credibility.