Financial Engineering and Portfolio Management: 5 (53)

Open Access Article

1 - Provide a two-stage mathematical model for evaluating and selecting a project portfolio
shahab Forootan chehr saeid aghasi sayyed mohammad reza davoodi

Today, the need to choose a project portfolio as the main factor in the success of investment profitability is obvious. Evaluating a portfolio of all its dimensions is an urgent and vital need in investment organizations. Therefore, in this research, a two-stage multi-o More

Today, the need to choose a project portfolio as the main factor in the success of investment profitability is obvious. Evaluating a portfolio of all its dimensions is an urgent and vital need in investment organizations. Therefore, in this research, a two-stage multi-objective mathematical model was evaluated and the project portfolio was selected. Due to the uncertainties in the evaluation of the project portfolio, the theory of firm uncertainty based on Bertsimas and wire were developed on a mathematical model and then due to the NP-HARD being the problem under study, to validate the model in larger dimensions using two algorithms. The meta-initiative of MOPSO and NSGAII analyzed the model findings. Based on the analysis of the results obtained from the two algorithms, it was shown that the computational time of MOPSO algorithm is better than NSGAII algorithm and the means of the first and second objective function of MOPSO also showed the superiority of this algorithm compared to NSGAII. Other analytical parameters such as NPF, MSI and SM showed that the NSGAII algorithm performed better than the MOPSO algorithm. Finally, using TOPSIS method, it was shown that NSGAII algorithm with a weight of 0.6945 was more favorable than MOPSO. Manuscript profile

Open Access Article

2 - Portfolio optimization based on parametric and nonparametric period value at risk
Mohamad ali tabibi sayyed mohammad reza davoodi abdolmajid abdolbaghy ataabady

Value at risk is one of the most widely used risk measurement criteria. Period value at risk extends the concept of value at risk for an investment with a set of maturity horizons, thus neutralizing the model's sensitivity to a point investment horizon. This reduces the More

Value at risk is one of the most widely used risk measurement criteria. Period value at risk extends the concept of value at risk for an investment with a set of maturity horizons, thus neutralizing the model's sensitivity to a point investment horizon. This reduces the impact of liquidity risk and the investor has ample opportunity to sell and can make the right decision in an interval. In the present study, two stock portfolio models are designed based on the period value at risk, the first based on historical simulation and the second is parametric and based on the distribution of normal-Laplace mixture for proper fitting of tail data. The result of the experimental study of the models designed on a stock portfolio with eight indices of the Tehran Stock Exchange in the period 1390 to 1399 shows that the parametric approach in the test data in average return and Sharp ratio criteria has a better performance than the historical scenario. Also, the relative error between the period risk value predicted by the stock portfolio and its estimation in the test data in the parametric approach is less. Manuscript profile

Open Access Article

3 - Presenting a market direction prediction model for gold coin trades in Iran’s Commodity Exchange market using Long Short-Term Memory (LSTM) algorithm
Soheil Zoghi Reza Raei Saeed Falahpor

In recent years, deep learning neural networks have been recognized as powerful tools for solving complex problems. Deep learning is a subfield of artificial intelligence in which complex problems with numerous parameters and inputs are modeled based on a set of algorit More

In recent years, deep learning neural networks have been recognized as powerful tools for solving complex problems. Deep learning is a subfield of artificial intelligence in which complex problems with numerous parameters and inputs are modeled based on a set of algorithms. In this research, a new framework of deep learning is presented. Using wavelet transform, stacked auto-encoders, and the Long Short-Term Memory or LSTM, we predict the market direction in the future contracts of gold coins of Iran's Commodity Exchange market. The input data is first denoised using the wavelet transformer in the proposed method. Then, using the stacked auto-encoder, the indicators influencing the market direction are identified. Ultimately, these indicators are given as input to the LSTM architecture to predict the market direction. Proposing several new technical indicators to increase the accuracy of the proposed model, adjusting the parameters of the utilized algorithms, including LSTM, for this problem, and suggesting a trading strategy to achieve appropriate profitability are among the contributions of the present study. Investigations reveal that the proposed method outperforms other approaches and achieves higher accuracy and efficiency. Manuscript profile

Open Access Article

4 - Explain the factors affecting stock liquidity using genetic algorithm and minimum and maximum correlation (MRMR) methods
Mahmoud Rezaei Hossein Panahian Mahdi Madanchi Zaj Hasan Ghodrati

Liquidity of stocks is an important challenge in the capital market. Identifying the factors affecting liquidity helps to predict the stock liquidity situation and thus stock risk management. The purpose of this study is to find the factors affecting the liquidity of st More

Liquidity of stocks is an important challenge in the capital market. Identifying the factors affecting liquidity helps to predict the stock liquidity situation and thus stock risk management. The purpose of this study is to find the factors affecting the liquidity of stocks. For this purpose, in the first stage, using the research literature and experts, the influencing factors are identified and using the methods of minimum redundancy and maximum correlation (MRMR) and genetic algorithm, the effective variables are selected. In this research, using Excel software and existing raw data, the required data was created and then using support software and neural network toolbox and support vector machine was created. . Finally, the extracted variables using MRMR include stock market value, intensity of product market competition, GDP growth, equity returns, stock returns, inflation rate and family ownership, and using the financial model of financial leverage, government ownership, Equity returns, GDP growth, share buoyancy percentage, market type and board (on the stock exchange and OTC), the intensity of competition in the product market were selected. Manuscript profile

Open Access Article

5 - Ranking of Firms listed in Tehran Stock Exchange Using Multi Criteria Decision Making Methods (Case Study: Cement Industry Companies)
Shayan Rouhani Rad Mohammad Reza Akhavan Anvari Kamran Pakizeh

This study primarily aimed to evaluate the performance and ranking of companies listed in the Tehran Stock Exchange cement industry using the multi-criteria decision-making methods. The main problem in the analysis of financial ratios is that each of the financial crite More

This study primarily aimed to evaluate the performance and ranking of companies listed in the Tehran Stock Exchange cement industry using the multi-criteria decision-making methods. The main problem in the analysis of financial ratios is that each of the financial criteria evaluates a particular aspect of the organization's financial performance; thus, financial ratios confuse managers and investors. As a result, solutions are needed to overcome these limitations. Multi-criteria decision-making methods are one of these solutions. In this study, we use the BWM method, which is one of the new multi-criteria decision-making methods. Because of the benefits such as less comparative data and more stable comparisons, the BWM method is used to weigh objectives. According to the characteristics of multi-criteria decision-making methods, in addition to the BWM method, TOPSIS, ELECTRE, and VIKOR methods were used to rank the fifteen companies in the cement industry group listed in Tehran Stock Exchange during a period of three years (from 2017 to 2019). Finally, the results of methods were combined by Borda and Capland. Manuscript profile

Open Access Article

6 - Identification of Effective and Influential Factors on Debt Financing for Financial Institutions and Banks in the form of crowdfunding Using Fuzzy DEMATEL Method
Ghazal Shahabi shojaei Shadi Shahverdiani Hashem Nikoumaram

The purpose of this research is to identify the effective factors on the debt financing of the financial institutions and banks in the form of the crowdfunding using Fuzzy DEMATEL to propose a model for obtaining the essential conditions for crowdfunding. Debt financing More

The purpose of this research is to identify the effective factors on the debt financing of the financial institutions and banks in the form of the crowdfunding using Fuzzy DEMATEL to propose a model for obtaining the essential conditions for crowdfunding. Debt financing is borrowing money from companies and investors through bonds, banks or financial institutions to support related business activities. The research methodology is fuzzy technique, in which multi-criteria decision method (MADM) is used. The opinions of the experts and interviews with ten related experts and the snowball method have been used to reach the theoretical saturation stage in order to identify the factors affecting the development of crowdfunding model and also open, axial and optional coding has been considered. The results depicted identification of the influential factors in crowdfunding including legalism, culture building, funding, collective communication, e-commerce and trust building. According to the results of the study, it can be concluded that this issue is difficult regardless of the effective factors of crowdfunding to finance debt in financial institutions and banks in order to grow. Manuscript profile

Open Access Article

7 - Optimization on ELM network using Particle swarm Optimization Algorithms and OSELM to predict the industry index in Tehran Stock Exchange
, benyamin hakimzadeh ehsan Taiebysani Mahdi Saeidi Kousha

There have always been two approaches to forecasting in financial markets: traditional and intelligent approaches. In the traditional method, this forecasting is based on statistical models and in the intelligent method is based on artificial intelligence models. Tradit More

There have always been two approaches to forecasting in financial markets: traditional and intelligent approaches. In the traditional method, this forecasting is based on statistical models and in the intelligent method is based on artificial intelligence models. Traditional methods mainly use linear patterns to model market behavior, while the main advantage of smart models is the ability to learn and model nonlinear behaviors in the market. It has always been a question of which methods can better model market behavior, and despite the many models that have been proposed for forecasting, there is still an attempt to build a model that can use more effective variables for forecasting. Continues to be able to take into account factors such as time, risk and return. In this research, we have used the neural network to predict the industry index. This is done by ELM neural network using two optimization methods OSELM and PSO. The results show that the prediction accuracy of these two methods is not significantly different from each other, but in terms of execution time, the OSELM neural network algorithm has performed much better and faster. Manuscript profile

Open Access Article

8 - Nonlinear Exchange Rate Analysis in the Iranian Economy
Mohammad abbasifard Seyed Abdolhamid Sabet Masoud Salehi Rezveh abdolkarim hosseinpour

Exchange rate pass-through (ERPT) means the impact of exchange rate fluctuations on domestic prices. The study of the relation between the exchange rate and the general level of domestic prices, known in the international financial literature as the exchange rate analys More

Exchange rate pass-through (ERPT) means the impact of exchange rate fluctuations on domestic prices. The study of the relation between the exchange rate and the general level of domestic prices, known in the international financial literature as the exchange rate analysis, has been one of the most important and fundamental topics in the economic literature. This study investigates the nonlinear exchange rate pass-through in the Iranian economy in the period 1984 to 2019 using the Markov switching method. The results show that in the period under review, for a one percent increase in the exchange rate, the inflation rate increases by 74 percent. In other words, transfer to prices is not complete and exchange rate transition in the Iranian economy is incomplete. The imperfection of the exchange rate passage is due to the fact that the price of imported goods is probably not only a function of the exchange rate, but also other factors have contributed to the fluctuation of these prices. Manuscript profile

Open Access Article

9 - Portfolio optimization in capital market bubble space, application of bee colony algorithm
Iman Mohammadi Hamzeh Mohammadi Khashoei arezoo aghaei chadegani

The existence of bubbles in the market,especially the capital market,can be a factor in preventing the participation of investors in the capital market process and the correct allocation of financial resources for the economic development of the country.On the other han More

The existence of bubbles in the market,especially the capital market,can be a factor in preventing the participation of investors in the capital market process and the correct allocation of financial resources for the economic development of the country.On the other hand,due to the goal of investors in achieving a high return portfolio with the least amount of risk,it is necessary to pay more attention to these markets In this study,in order to maximize returns and minimize investment risk,an attempt was made to create an optimal portfolio in conditions where the capital market has a price bubble.According to the purpose,the research is of applied type,and in terms of data,quantitative and post-event,and in terms of analysis,is descriptive-correlation.In order to identify bubble months in the period from2015to2019in Tehran Stock Exchange,sequence tests and skewness and kurtosis tests were used and after identifying bubble periods,artificial bee colony algorithm was used to optimize the portfolio.The results indicate the identification of 10 periods with a price bubble in the study period.Also,in portfolio optimization, selected stock portfolios are formed with maximum returns and minimum risk.This research will be a guide for investors in identifying bubble courses and how to form an optimal portfolio in these conditions. Manuscript profile

Open Access Article

10 - Application of Fuzzy Delphi Integrated Approach / Multiple Logistic Regression in Identifying and Assessing the Credit Risk of Real Bank Mellat Customers
sirous Azizollahi Mahdi Madanchi Zaj ghasem Mohseni Mehrdad Hosseini Shakib

The purpose of this study is to validate the real customers of Bank Mellat using fuzzy Delphi approach and multiple logistic regression. For this purpose, first, the effective indicators on assessing the credit risk of real customers were identified by library method an More

The purpose of this study is to validate the real customers of Bank Mellat using fuzzy Delphi approach and multiple logistic regression. For this purpose, first, the effective indicators on assessing the credit risk of real customers were identified by library method and then, the fuzzy Delphi method was used and the indicators were screened. The community of this section was formed by banking experts (Bank Mellat) who were selected by snowball method. Then, the final data related to the indicators, including the files of 7318 real customers of Bank Mellat during the years 2014-2020, were collected and analyzed by multiple logistic regression method in four categories of timely receipt, past due date, delinquent and doubtful receipt. The results showed that the loan amount, loan repayment time, installment interval, installment amount, loan extension, previous loan, real estate collateral, inventory average, facility interest rate and education level have a significant effect on credit risk of real customers. Also, the significance of gender, age and occupation indices was not confirmed. Manuscript profile

Open Access Article

11 - A model for determining the optimal financing tools for companies using the mechanism of matching the conditions of supply and demand sides
Seyed Mahdi Nemati Kheirabadi Seyed Abdolhamid Sabet seyed saeed malek sadati Masoud Salehi Rezveh

Corporate financing has always been one of the main concerns of managers and in this area, choosing the optimal financing tool is vital. This study has determined the optimal financing tools for companies by emphasizing the matching of supply and demand side conditions More

Corporate financing has always been one of the main concerns of managers and in this area, choosing the optimal financing tool is vital. This study has determined the optimal financing tools for companies by emphasizing the matching of supply and demand side conditions in different stages of the company's life cycle using Delphi and DEMATEL techniques plus ANP and AHP processes. The results show that there are a total of 28 tools for financing companies and 6 indicators for selecting the appropriate financing tools. Also based on matching: "expected return (justifiability)", "risk level" and "time horizon" are given priority, respectively. In addition, among the various financing instruments, in the "start-up" phase, business angels, crowdfunding, and direct government assistance take precedence. In the "early stage" stage, after the tools of the previous stage, venture capital and short-term banking resources take precedence. In the "development" phase, after the tools of the previous stages, short-term banking facilities, asset-based financing, hybrid instruments (excluding mezzanine) and the stock market of start-ups are preferred. Finally, in the "stabilization" stage, after the tools of the previous stages, long-term banking facilities, mezzanine, bond-based methods and initial public offering of shares take precedence. Manuscript profile

Open Access Article

12 - Evaluating the Performance of Financial Institutions using a Data Envelopment Analysis model in a FDH networks (Case Study: Saman Bank)
Hadise Vahedi-Anvar Narges Norouzi

Today, measuring efficiency is one of the most important methods of performance evaluation in any organization. The outputs obtained in all inputs represent the efficiency. Due to the comprehensiveness of the banking sector, it can be introduced as one of the main areas More

Today, measuring efficiency is one of the most important methods of performance evaluation in any organization. The outputs obtained in all inputs represent the efficiency. Due to the comprehensiveness of the banking sector, it can be introduced as one of the main areas of economic development. In this paper, a data envelopment analysis (DEA) model in a Free Disposal Hull (FDH) network is presented considering the undesirable output for handling the status of the financial deposits in Saman Bank branches. Since the basic models calculate efficiency by considering the overall output and input and ignoring the internal relationships in the banking process flow system; therefore, by considering this issue, in this paper, we present a DEA model that calculates the efficiency score of the branches with the high accuracy. Then the proposed model is compared to the basic CCR model. Finally, the cross-performance method is used to rank the units of the branches. Manuscript profile

Open Access Article

13 - Providing a comprehensive model based on the effect of behavioral indicators of Vals lifestyles on Purchase decision making styles of Asel - case study: female buyers with high and low income and financial resources in Tehran city
Seyed Mohamad Taghi Hosseinikia Vahid Reza Mirabi

Today, numerous researches in the world have shown that in order to investigate the behavior of consumers and their purchase decisions in the markets, their lifestyles and the type of purchase decision of each style should be taken into consideration. And also researche More

Today, numerous researches in the world have shown that in order to investigate the behavior of consumers and their purchase decisions in the markets, their lifestyles and the type of purchase decision of each style should be taken into consideration. And also researches in the world show that among the behavioral factors, lifestyle is a very important factor for knowing and recognizing the behavioral tendencies of each person due to its constant and unique nature and can provide better knowledge and information to the buyers. Each consumer makes a purchase decision according to their lifestyle, and one of the effective styles in making purchase decisions is the Vals lifestyle, which can determine the situation of buyers according to two behavioral factors and financial resources. up and down), specify. And based on that, he proceeded to cluster the target markets. Therefore, the aim of this article is to present a comprehensive model based on the influence of behavioral indicators of Vals lifestyles on shopping decision making styles Manuscript profile

Open Access Article

14 - Provide IPO valuation model using genetic algorithm and compare the value of the proposed model with Op
samaneh fathalian seyed Ali Nabavi Chashmi Ebrahim Chirani

Proper Ipo Valuation Companies entering the capital market for the first time are critical to both business owners and investors. But the valuation of these stocks is influenced by many quantitative and qualitative factors. Nonlinear intelligent systems such as neural n More

Proper Ipo Valuation Companies entering the capital market for the first time are critical to both business owners and investors. But the valuation of these stocks is influenced by many quantitative and qualitative factors. Nonlinear intelligent systems such as neural networks and genetic algorithms are good tools for accurately predicting the initial stock value. Therefore, the purpose of this study is to present the IPO valuation model using genetic algorithm and compare the value of the proposed model with Op. For this purpose, data related to 421 companies were collected that during the years 2009 to 1397 had made an initial public offering of shares on the Tehran Stock Exchange. In order to analyze the data, the methods of regression, neural network and genetic algorithm have been used. The results showed that the Ipo valuation model using genetic algorithm is the optimal IPO valuation model. Also, the projected valuation, while close to the OP, while meeting the relative price increase, can meet the expectations of investors and business owners in a proper IPO valuation. Manuscript profile

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