INVESTMENT KNOWLEDGE
Year:2019 | Volume:8 | Issue:30|Papers Count:20

Portfolio selection process is one of the problems that have been attracted many researchers. Various criteria that have been applied in this case have changed over time and this situation makes necessary the using of appropriate tools to support investment decisions. The purpose of this research is modeling and solving of portfolio selection problem. On the other hand, in some cases of a portfolio optimization, due to largeness of problem size, the problem would be impossible to solve in a reasonable time. In such situation, applying the methods that reduce the scale of problem can be useful. In current paper a Dantzig-Wolfe algorithm is used to solve the problem in which, after decomposing the basic problem into several sub problems and solving them, individually, the obtained results are aggregated. The results of applying this method showed its efficiency in solving the large-scale problems show.

Herding behavior among security analysts is described as similar behavior by analysts when forecasting main finance ratios of public companies and when giving investment recommendations. This type of behavior can be divided into two categories based on the different driving forces behind the analysts’ herding behavior. . For instance, if one analyst lacks the ability to research and provide recommendations, he or she may follow, or even copy, a famous analyst’ s reports. Such action will result in herding behaviorIn this paper, we build undirected weighted networks to study herding behavior among analysts and to analyze the characteristics and the structure of these networks. We then construct a new indicator based on the average degree of nodes and the average weighted clustering coefficient to research the various types of herding behavior. Our findings suggest that every industry has, to a certain degree, herding behavior among analysts. Furthermore, we relate the two types of herding behavior to stock price and find that uninformed herding behavior has a positive effect on market prices, whereas informed herding behavior has a negative effect.

Active management is one of the issues that is important in terms of violating effectiveness of financial markets financial markets. Because inefficient market, there is a potential to generate abnormal returns through active portfolio management. In many studies in this regard the reason for the surplus return compared to the baseline portfolio by minimizing the tracking error variance (TEV) in this regard, the risk of the entire portfolio is not taken into account. In this study, by using the differential evolution algorithm (DE) to optimize the active portfolio, with the goal of maximizing portfolio surplus returns compared to the standard portfolio, considering the risk of the entire portfolio from the calculated conditional risk value criterion (CVaR) based on the GARCH approach is used. The results of the portfolio consist of 14 stocks with a positive average yield from the beginning of 2011 to the end of June of 2017 from the top 50 stock exchanges on a monthly shows that subject to risk portfolio based on CVaR, causes better performance in the active optimization of the portfolio, based on backtesting method.

In this paper, we apply R-Vine copula-ARMA-APGARCH approach to investigate the dynamic relationship between banking, insurance and pension, investment and other financials sub-indexes in Tehran stock exchange. Using a sample of more than 8 years of daily return observations of the financial sub-indexes, we find evidence of significant and symmetric relationship between these variables. Finally, there is evidence to suggest that the application of the vine copula model improves the accuracy of VaR estimates, compared to traditional approaches. This paper results show that vine copula VaR is accurate at 1% and 5% significance levels. This paper’ s findings suggest the flexibility and capacity of vine copula structures in financial dependency modeling and risk management.

Investor’ s decision making is a subject of considerable debates in behavioral finance. Behavioral finance refers to how people make decisions under uncertainty conditions. This paper is devoted to The impact of investor’ s Perception of Risk on Portfolio Management. It is an applied study of descriptive-surveying type used to gather the required data through questionnaires. A simple sampling was used and the final sample included 104 investors. Investors were questioned about 24 possibly influencing factors of investor’ s reception of risk and 21 influencing factors Portfolio Management in the form of a Likert Scale. The data from questionnaires with SPSS and Smart PLS software using structural equation modeling (path analysis) were analyzed. Results of the study indicated that risk perceived risk factors directly and affecting the perceived risk indirectly is effective on the portfolio management.

The purpose of this research is identification of the profitable strategies on gold coin option contracts on the Iran mercantile exchange. In order to do this research, profit of each strategy was estimated by the daily price gold coin option on the Iran mercantile exchange. (from the investor approach) The profit derived from each strategy was calculated, in the period from December 2016 to July 2017and profitable strategies were identified. (150 working days in the Iran mercantile exchange) In this research, the symmetric and asymmetric strategies including, Long Call Butterfly, short Call Butterfly, Bull spread، Bear spread, Stradle, Streip, Strep, and Strangel have been analyzed in Exercise dates of January 2017, March 2017, July 2017, and september of2017. The results indicate that the Bull Call Spread for the gold coin option contracts on the Iran mercantile exchange with Exercise dates of January 2017, the the Bull Call Spread and Butterfly Spread for option contracts with the maturity of March/ july 2017 are profitable. Also most strategies with the maturity September 2017 option contracts have not been profitable, it is not recommended. It is recommended that the reverse position( End of investment)should not be in the first three days of the start of the contract on the Iran mercantile exchange.

Traders in stock market consider stock information in the past few days as well as the current day information when making decision about selling or buying stock. To imitate stock traders’ style of decision-making, in this article, League Championship Algorithm (LCA) equipped with teams which have network structure has been introduced to extract multi-order rules. Multi-order rules would be extracted by LCA which not only contain the current day information, but also information of the previous days. Thus, a memory to store useful information has been created for each rule. To evaluate the model, 20 shares of companies in different industrial parts of Tehran stock exchange are used. In the testing simulation, the proposed model shows higher profits or lower losses than the buy & hold and genetic network programming models.

The Dunning-Kruger effect is a kind of cognitive bias in unprofessional people who suffer from the illusion of superiority and incorrectly evaluate their ability to be overly real. This bias is attributed to the metacognitive inability of unprofessional individuals to identify their disability and is a blood stream in the human body. Financial managers also suffer from this cognitive error in their own assessment of others, as financial managers with a level of ability and experience usually evaluate themselves more often than they are. For example, those who have the capability of an accounting expert have their own accounting officer and those who have the ability to become accounting officer, they identify themselves as financial advisors and those who are capable of a financial manager, as financial advisers, and usually themselves more than what they are. Or vice versa, they are less than what they are, which is due to self-esteem or self-righteousness, or to Duning Kruger's. In this research, we examine the characteristics and general criteria of financial managers and identify the skills of financial managers, and the results show that the skills of financial managers are usually more than what they have in them.

This study aimed to investigate the influence of cultural factors on the risk power of companies in Iran's stock exchange. The companies surveyed included 178 companies selected by sampling method based on the specified criteria. To estimate the impact of cultural factors on the risk of active companies in the Iranian stock exchange and to analyze the relationships between the variables presented in the model with the use of panel data extracted from the financial statements in the stock exchange and other reports published by both statistical and religious institutions and Cultural was used. In this study, the panel method was used and before that Chow and Housman tests were used to determine the type of test. The results of the study on the effect of cultural factors on the riskiness of the companies active in the stock exchange showed that cultural factors have a significant effect on the standard deviation of the company's returns, the standard deviation of the firm's return on assets and the costs of research and development of the company, and This relationship is negative for all of the three risk aversion factors. In sum, it can be concluded that the promotion of cultural factors in the society influences all three indexes related to the risk appetite of companies in the stock market and thus reduces the risk aversion of these companies.

Since the atmosphere of financial markets is uncertain and ambiguous, Conditional Value at Risk measurement has been of great importance in recent years for financial companies and micro and macro investors. In this paper, we estimate the CVaR of the Tehran Stock Exchange Index for distribution of the Trial Student at confidence levels of 95% and 99% based on the Cipra method, which is proposed as a new approach for the estimation of the CVaR. In order to evaluate the performance of this approach, the comparison between the said approach and the conventional methods of GARCH, EGARCH and TGARCH was performed using four backtesting of unconditional coverage test, conditional coverage test, joint test and Lopez loss function test. The results show that robust Cipra method has a better and more reliable performance than the other methods in estimating the CVaR.

The aim of the study "A Pattern for Portfolio Optimization in A Speculative Bubble Condition According to Mental Accounting on companies listed in the Tehran Stock Exchange" is. The 10-year study period listed in the Tehran Stock Exchange during 2006-2015 were analyzed. The data of 110 firms were analyzed by using statistical software Matlab, spss20, Eviews7 and lingo software in the studied years. In this research, mental accounting is based on Fernandez as a moderator variable and the Sharp, Trainer and Jensen criteria, The speculative bubble based on the gilium pattern are used as a risk measurement indicator. The results indicate that the average return on the portfolio in the bubble of speculative space at a certain level of risk is greater than the return on a portfolio of non-bubble based on mental accounting, The second hypothesis was also claimed to be based on the larger average portfolio risk in the bubble of speculation at a certain level of return on the risk of a non-bubble portfolio based on mental accounting.

Studying the countries' stock market and global market interaction has been one of the most important research subjects in the global market. Thus, studying the relationships may have a significant role for the decision making of the investors. An appropriate estimation of the dependence structure has been the significant starting point at an investing period, for the investment risk control. The present research aims to study the interaction between dependence structure at Tehran stock market efficiency and the global price of gold and oil, at the period of 2010-2017, on a daily basis. In doing so, GARCH-Copula approach has been applied. The results show the asymmetric mutual relationship between the studied efficiencies. As it can be seen in the present paper, the t-student Copula functions can have a better recognition than other functions for both efficiencies; 'Tehran stock and gold market', and 'Tehran stock and oil market'. The results indicate that the Tehran stock market has been highly dependent to both oil and gold markets, and their threshold changes may lead to a stronger dependency of the markets together.

Financial literacy and behavioral biases (Machiavellian personality) are critical factors affecting the financial decisions and behaviors of investors. We survey 285 individual stock investors to measure their financial literacy, to examine their behavioral biases and to investigate the relationship between financial literacy and behavioral biases. This study was conducted in 20015 and 2016 years in Tehran stock exchange market, brokers and investment companies in Iran. Standard international questionnaire (after localization) was distributed among the investors and the answers were gathered, then variables were measured using multivariate regression in SPSS. In spite of research literature in the local context which offers a model for measuring financial literacy, this study specifically tends to find out the relationship between financial literacy and the behavioral biases among the Investors Results suggest that there is negative significant relationship between the financial literacy and the Machiavellian personality in Tehran Stock exchange market Investors.

Variables such as exchange rates and gold prices has a great importance for economic actors therefore the aim of this study were determined as prediction of U. S Dollar exchange rate and gold coin price in Iran Market. Forecasting has been done by Geometric Brownian Motion model that is considered as one of the stochastic differential equations. Data were collected and analyzed in the period from the beginning of 1392 until the end of 1395. also forecasting prices for each under study time series has been done in various forecasting horizons involved 7, 14, 21, 30, 60, 90, 180 and 360 day time period. The results show that Geometric Brownian Motion model can simulate the prices of gold coin and exchange rate highly accurate in accordance with the criteria of mean absolute percentage error. Also The other results obtained from this study is that According to ten different prediction accuracy criteria, By increasing the forecast horizon, ability of the GBM model in simulation and forecasting exchange rates and the price of gold coin decreases.

The purpose of this research is to investigate the relationship between investor sentiment, courage in predicting dividends and future performance of the company in Tehran Stock Exchange. The research is applied from the direction of the target, and, depending on the type of research project, relying on historical information, then the event. The method of research inference is inductive and correlation type and consists of 3 hypotheses. The research community is the accepted companies in Tehran Stock Exchange for a period of 5 years. To document the results of statistical analysis and provide final solutions, the researcher used a statistical method using Eviews software to analyze the questions and hypotheses. The research was conducted using regression Compound linear and F and t tests. The results of the test of research hypotheses showed that investor's feelings on courage affect the prediction of dividends and company growth, but not affect future returns.

The purpose of the present study was to compare the efficiency of neural network models and available criteria in risk criteria in optimal portfolio formation. At first, time series data related to the return rate of different companies were collected from the databases of the Securities and Exchange Organization of Iran since 2008-2017, and analyzed in the framework of neural network models and Spectral, Deviation and Coherent risk measures by using Kupiec, Christofferssen and Lopez test. The results of the Kupiec and Christofferssen test for neural network models and CVaR, showed that the LR test statistic for the whole group of investigated companies was larger than the critical value. Based on this, it was concluded that the performance of neural network models and CVaR criteria can be acceptable for the entire group of companies at a significant level of 5% and the LR test statistic is lower than the critical value for SE criteria for the whole group of investigated companies. This suggests that SE's performance is not acceptable to all companies at a significant level of 5%. On the other hand, based on the results of Kupiec and Christofferssen test for VaR, the LR test statistic for the six groups of companies was larger and for the four was smaller than the critical value. Therefore, we can say that in artificial neural network models, the average number of violations or the state of exception in the level of 5% were less than the spectral, deviation and coherent risk measures.

Forecasting financial markets is an important issue in finance area and research studies. Importance of forecasting on one hand and its complexity, on the other hand, researchers have done much work in this area and proposed many methods. In this research, we propose a hybrid model include wavelet transform, ARMA-EGARCH and NN for day-ahead forecasting of stock market price in different markets. At first WT is used to decompose and reconstruct time series into detailed and approximated parts. And then we used ARMA-EGARCH and NN models respectively for forecasting details and approximate series. In this model we used technical index by approximate part to the improvement of our NN model. Finally, we combine prediction of each model together. For validation, proposed model compare with ANN, ARIMA-GARCH and ARIMA-ANN models for forecasting stocks price in UA and Iran markets. Our results indicate that proposed model has better performance than others model in both markets.

Portfolio optimization is one of more important problems in financial area. The classic model consider that stocks is random variable with symmetric probability density function. But in real world, forecasting stock condition always faced with uncertainty and we need insert human factors in our forecasting. Fuzzy logic is one of methods that we can use this to model this condition. On other hand, experimental studies show that assets return isn’ t normal and symmetric, so we should use down risk measure such as semi variance and semi absolute deviation. In this research we consider two point in portfolio selection problem. Then we use two intelligent method based genetic and deferential evolutionary algorithm for solving the models. Making use of Tehran Stock Exchange data, it is concluded that considering semi absolute deviation has higher efficiency than semi variance model and intelligent method based deferential evolutionary algorithm has higher efficiency from intelligent method based genetic algorithm.

The banking system is a unit of economic system which its aim is absorption of any deposit and its allotment for providing financial demand of any economical activity. Terefore, Banks holding major part of society funds, have important effect on economic system and influence societys economical transaction and relation. At first, a conceptual model was developed for customer preferences following the three stage process of grounded theory method, namely open coding, axial coding, and selective coding. This model was then tested by conducting structural equation modeling using LISREL and SmartPLS. The result of this process was Identification of 11 categories The researcher succeeded in completing 13 deep interviews with banking customers. Thus, the study focused on a large statistical population of bank customers and data were collected from 500 respondents who were selected through stratified random sampling with proportional allocation. A 37-item questionnaire designed by the researchers was used for data collection. Each item of the questionnaire had to be answered based on a likert scale. The results supported the goodness-of-fit of the model, resulting in the presentation of a comprehensive model for customer preferences and do invest in Iran’ s banking industry.

An impressive growth has recently been witnessed in the Islamic Financial System. Nowadays, not only is Islamic Finance emphasized by the Islamic countries but the approach has also been adopted in other countries. The present research was conducted to identify and rate financing criteria through assets securitization in Bank Keshavarzi. The research, from the objective point of view, is a functional one and, from subject and research questions points of view, is a descriptive-survey type. The data collection tools, including questionnaires, are based on paired comparisons, through which the data were rated according to an hourly scale. The sample population, selected using snowball sampling method, consists of financial experts who identified 26 indices with Delphi technique. The rating was conducted using Analytical Hierarchy Technique. The results demonstrate that, based on experts' feedback, in the study of paired comparison matrix of assets securitization elements, selection of Special Purpose Vehicle (SPV) by the bank; regarding the assets to be securitized, government claims; in securitization process, the rate determination; in review of securities offering impacts on the financial structure of the originator, assets productivity; and to review securitization consequences for promotion of financial and banking health indices, the liquidity risks are prioritized. Moreover, with regards to inconsistency rate, there is complete consistency among the paired comparisons of the models.