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Open Access Article
1 - Portfolio ranking: using finance technology set in DEA models (Case Study: Tehran Stock Exchange)
A. Davtalab R. MehrjooOne of the most important concerns of investors in financial markets is choosing a share or stock portfolio that is optimal in terms of profitability. To this end, there are many ways in which the stock portfolio has been chosen. The optimal portfolio selection is a por MoreOne of the most important concerns of investors in financial markets is choosing a share or stock portfolio that is optimal in terms of profitability. To this end, there are many ways in which the stock portfolio has been chosen. The optimal portfolio selection is a portfolio management goal. In this dissertation, the DEA technique has been used as a new and reliable way to select the stock optimal stock. In this thesis, the risk of different orders, average returns, return variances, higher torque are considered as output variables. It will also be possible to take into account the priorities for increases in risk ignored by DEA in applied studies but discussed in economic theory. Finally, in this research, 278 companies were evaluated in 50 stock portfolios during the 5-year period, which is evaluated by 3 models, one for higher returns, one for lower risk and one for a combination of these two methods has meant greater returns and less risk. Also, baskets number 6 and 8 ranked best in the first, second and third models. . Manuscript profile -
Open Access Article
2 - Stock portfolio optimization based on the combined model of omega ratio and mean-variance Markowitz based on two-level ensemble machine learning
sanaz faridi Mahdi Madanchi Zaj amir daneshvar shadi shahverdiani fereydoon rahnamaIn this paper, the stock portfolio of active companies listed on the Tehran Stock Exchange is optimized based on the combined model of omega ratio and mean-variance Markowitz (MVOF). For this purpose, 480 companies listed on the Tehran Stock Exchange during the years 13 MoreIn this paper, the stock portfolio of active companies listed on the Tehran Stock Exchange is optimized based on the combined model of omega ratio and mean-variance Markowitz (MVOF). For this purpose, 480 companies listed on the Tehran Stock Exchange during the years 1390 to 1399 were selected and based on the input data, the companies were filtered. Hence a combined method consisting of trading rules optimization method based on technical analysis (6 indicators RSI, ROC, SMA, EMA, WMA and MACD) and two-level collective learning machine (SVM, RF, BN, MLP and KNN) for Data training and purchase signal presentation were addressed. Therefore, 85 companies were selected to optimize the stock portfolio. To teach the data, 85 companies filtered by the combined method were used and the number of different classes with 50 learners was used. The results show that using the OF model compared to the MVF model has the highest stock portfolio returns during the years 1395 to 1399. While the MVF model has the lowest investment risk. As a result, by combining the above models, the stock portfolio return in this method is much higher than other methods. While the investment risk was lower. Therefore, if the MVOF model is used, the return on the stock portfolio will increase and the investment risk in it will decrease. Manuscript profile -
Open Access Article
3 - Mean-Variance test based on theoretical framework of downside risk using VAR
fereydoun Rahnamay Roodposhti mehdi Hemmati Asiabargi Laleh Shabani Barzegar Fatemeh KhaksarianVariance and downside risk are different variety of risk factors in portfolio management. The purpose of this research is testing mean-variance based on theoretical framework of downside risk using VAR. Period used for this test is from 1384 to 1393 for Teh MoreVariance and downside risk are different variety of risk factors in portfolio management. The purpose of this research is testing mean-variance based on theoretical framework of downside risk using VAR. Period used for this test is from 1384 to 1393 for Tehran Stock Exchange. VAR is the statistical methods used in this study. The results of this study suggest downside risk works better than the framework of mean - variance. In addition, the difference is even more visible when return on assets is more skewed. The study's outcome suggest the downside risk is a better measurement than mean -variance for investment decisions Manuscript profile -
Open Access Article
4 - The Tail Mean-Variance Model and Extended Efficient Frontier
Esmat Jamshidi Eini Hamid Khaloozadeh -
Open Access Article
5 - Multi-objective possibility model for selecting the optimal stock portfolio
Abdolmajid Abdolbaghi Ataabadi Alireza Nazemi Masoumeh Saki -
Open Access Article
6 - Visualized Portfolio Optimization of stock market: Case of TSE
Fatemeh Lakzaie Alireza Bahiraie saeed mohammadianAn investment portfolio is a collection of financial assets consisting of investment tools such as stocks, bonds, and bank deposits, among others, which are held by a person or a group of persons. In this research, we use the Markowitz model to optimize the stock portfo MoreAn investment portfolio is a collection of financial assets consisting of investment tools such as stocks, bonds, and bank deposits, among others, which are held by a person or a group of persons. In this research, we use the Markowitz model to optimize the stock portfolio and identify the minimum spanning tree (MST) structure in the portfolio consisting of 50 stocks traded in the TSE. The observable which is used to detect the minimum spanning tree (MST) of the stocks of a given portfolio is the synchronous correlation coefficient of the daily difference of logarithm of closure price of stocks. The correlation coefficient is calculated between all the possible pairs of stocks present in the portfolio in a given time course. The goal of the present study is to obtain the taxonomy of a portfolio of stocks traded in the TSE by using the information of time series of stock prices only. In this research, report results obtained by investigating the portfolio of the stocks used to compute 50 stocks of the Iran Stock Exchange in the time period from January 2012 to October 2022. Manuscript profile -
Open Access Article
7 - Portfolio Optimization and the Momentum- Contrarian Strategy (MCS)- Based Performance: Evidence from Tehran Stock Exchange
Homayun Soltanzadeh Reza Keykhaei Abdolmajid Abdolbaghi Ataabadi Mohammad Hosein Arman -
Open Access Article
8 - Portfolio optimization based on return prediction using multiple parallel input CNN-LSTM
Hatef Kiabakht Mahdi Ashrafzadeh -
Open Access Article
9 - بهینه سازی سبد سهام با استفاده از الگوریتم Big Bang-Big Crunch
علیرضا علی نژاد سرمایهگذاری نقش تعیین کنندهای در رشد اقتصادی دارد. یکی از اهداف اساسی کشورها، دستیابی به رشد اقتصادی و توسعه ی پایدار میباشد. امروزه حجم قابل توجهی از کار مدیران سرمایه گذاری و همچنین به طور عموم سرمایه گذاران، ساختن پورتفوی کارآمدی از دارایی هاست که اهداف تقا More سرمایهگذاری نقش تعیین کنندهای در رشد اقتصادی دارد. یکی از اهداف اساسی کشورها، دستیابی به رشد اقتصادی و توسعه ی پایدار میباشد. امروزه حجم قابل توجهی از کار مدیران سرمایه گذاری و همچنین به طور عموم سرمایه گذاران، ساختن پورتفوی کارآمدی از دارایی هاست که اهداف تقاضا را برآورده سازد. در این تحقیق از مدل میانگین-واریانس مارکویتز به همراه محدودیت‏های عدد صحیح و همچنین یک رویکرد فرا ابتکاری جدید به نام الگوریتم Big Bang-Big Crunch برای تشکیل سبد سهام بهره گرفته شده است. الگوریتم مورد استفاده در این تحقیق با سایر الگوریتم‏های فراابتکاری نظیر الگوریتم شبیهسازی تبریدی، ژنتیک و... با استفاده از داده‏های سهام شاخصهای بورس هنگ کنگ، ایران و ژاپن مقایسه شده است و نتایج، حاکی از رقابتی بودن این الگوریتم برای حل مسأله بهینهسازی سبد سهام دارند. Manuscript profile -
Open Access Article
10 - Portfolio Optimization of Listed Industries in Tehran Stock Exchange using Orthogonal GARCH
sahar abedini esmaiel abounoori Gh. Reza Keshavarz HaddadAbstract The development of financial markets and the stock market play an essential role in economic development. Considering that financial markets are always associated with risk and uncertainty, and shocks and turbulence in one market affect other markets, therefor MoreAbstract The development of financial markets and the stock market play an essential role in economic development. Considering that financial markets are always associated with risk and uncertainty, and shocks and turbulence in one market affect other markets, therefore, one of the main objectives of this research is to identify the type of distribution of financial series (stock returns of different industries) and estimate their uncertainty and risk (turbulence), determining the weight of stocks in the investment portfolio, as well as accurately identifying how the volatility changes and the intensity of correlation and interactions between the stocks of different industries over time in order to maximize the interests of investors and provide the necessary solutions to planners and policy makers Investors are for managing and developing the stock market.In order to optimize, statistics related to the weekly price index data of selected industries (mass housing, banks and credit institutions, chemical, automotive, pharmaceutical and basic metals) have been used. For this purpose, using orthogonal GARCH model and weekly data of stock price index of different industries in the period March 27, 2010 and January 18, 2021, the elements of the variance-conditional covariance matrix were estimated, Then, the stock portfolio was optimized using the obtained information and the distribution of general hyperbolic (GH) skewed t, in the framework of the static and dynamic classical Mean-Variance model as well as the static Mean-CVAR model. The results of fitting (estimation) of the data distribution show that the return distribution of the price index of the studied industries follows the distribution of the general hyperbolic skewed t; Based on the dynamic classical mean-variance model, the highest weight in the stock portfolio in the study period was related to the pharmaceutical (0/6336) and chemical industries (0/3539), respectively. Manuscript profile -
Open Access Article
11 - Development of stock portfolio trading systems using machine learning methods
Ali Heidarian Mohadeseh Moradi Mehr Ali FarhadianInvestment portfolio theory is an important foundation for portfolio management, which is a well-studied but not saturated topic in the academic community. Integrating return forecasting in investment portfolio formation can improve the performance of portfolio optimiza MoreInvestment portfolio theory is an important foundation for portfolio management, which is a well-studied but not saturated topic in the academic community. Integrating return forecasting in investment portfolio formation can improve the performance of portfolio optimization model. Since machine learning models have shown a superiority over statistical models, in this research, a approach of forming the stock portfolio in two stages is presented. first step, by implementing neural network, suitable stocks are selected for purchase, in the second step, using the (MV) model, the optimal weight in investment portfolio is determined for them. In particular, the stages of selecting suitable stocks and forming a stock portfolio are the two main stages of the model developed in this research. first step, a convolutional neural network model is proposed to predict stock buy and sell points for the next period.second step, stocks that are labeled as buys are selected as stocks suitable for buying, and MV model is used to determine their optimal weight in the stock portfolio. The results obtained using 5 shares of Tehran stock market as a study sample show that the efficiency and Sharpe ratio of proposed method is significantly better than traditional methods (without filtering suitable stocks) Manuscript profile
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