جستجوی مقالات مرتبط با کلیدواژه « تحلیل بنیادی » در نشریات گروه « علوم انسانی »

This research aims to expand the Markowitz model in a way that aligns more closely with real-world conditions, considering various fundamental analysis factors and market constraints. Conducted on the Tehran Stock Exchange, this study utilizes two measures, semi-variance and mean absolute deviations, alongside the variance measure in the Markowitz model to better estimate risk levels. In addition, several constraints such as cardinality constraint, threshold constraint, and segmentation constraint are employed to bring the results of the Markowitz-based model closer to reality. To ensure that the stock return metric is not solely based on stock price changes, this research incorporates nine important fundamental analysis metrics in filtering company stocks and as a return metric in the Markowitz model. Due to the computational complexity of the mathematical programming model, sample problems were also solved using the Harmony Search algorithm. The results indicate that the mathematical model performs better in terms of the distance from the ideal point efficiency metric, while the harmony search algorithm excels in uniformity metrics, exploring diverse solutions, and solution time. Increasing the range of cardinality and threshold constraints results in selecting more stocks in the portfolio, and simultaneously, the risk and return objective functions will improve concurrently.

The purpose of this article is to evaluate the technical efficiency of listed companies in the pharmaceutical industry in 2021. To achive this, the additive model of two-stage network data envelopment analysis was investigated with semi-positive and negative indicators and simultaneously considering the production process(Fundamental Analysis) in the first stage and the financial production process (Technical Analysis) in the second stage. In addition, FAHP applied to determine the weights of the first and second stages. The results showed: the production process is more important in defining the total efficiency of a company in the Stock Exchange. In the first stage, %33 and in the second stage, %25 of the pharmaceutical industry companies achieved full efficiency of one. According to the efficiency one of %13 companies of the studied industry in both first and second stages, the efficiency of the mentioned companies was also full and found to be one; These companies include Toliddaru, Exir Pharmaceutical and Loghman Pharmaceutical & Hygienic Companies. The lowest total efficiency belongs to Sobhan Pharmaceutical Group. In general, 88% companies of the studied industry have an efficiency higher than 0.5.

The success of capital market investors depends on their mastery of market structure, opportunities and threats, also knowledge of financial market analysis methods. This study, in the time domain of the research (2017 to 2018) and in the statistical population of the research, which is all the companies of the two petroleum and chemical groups of the Tehran Stock Exchange, tries to compare the two analytical methods of CANSLIM and Ichimoku. In this research, while identifying the top stocks based on CANSLIM, the back testing of the Ichimoku trading strategy and its profitability evaluation has been done, and finally, while introducing the adjusted CANSLIM model and appropriate to the Tehran Stock Exchange, the profitability of the combined strategy of adjusted CANSLIM and Ichimoku has been evaluated. The general result of the research was that the profitability of the combined trading method of adjusted CANSLIM and Ichimoku, whose win rate in this research was at least 66%, is more profitable than the investment method based on CANSLIM. In this study, the criteria of new higher prices, market direction, and the institutional sponsorship, which are the constituent elements of adjusted consensus, were recognized as the most effective indicators for identifying superior stocks.

Modern investment management began with Markowitz's theory on how to select an optimal portfolio based on the mean-variance model, and then continued with various optimization methods such as conditional value at risk model, half-variance model, and the mean-absolute deviation model. One of the most important weaknesses of these models is not paying attention to investors' views and relying on past information. The Black Literman model has largely eliminated this weakness by combining a matrix of investor views and past returns. In this research, using fundamental analysis, the matrix of investor views is formed and then the performance of the optimal portfolio of the Black Literman model is compared with existing models. The research period is between 2016 to 2021 and MATLAB software has been used to obtain the optimal portfolio. The results show that using different evaluation criteria, the fundamental Black Literman model performs better than other existing optimization models.

Investors mostly rely on fundamental and technical analysis in applying past and present information to choose the optimum stock and its future trend in an attempt to increase returns. The present study investigates the relationship factors ranking of CANSLIM model in synthetic fundamental-technical model by Fuzzy Multiple Attribute Decision method with stock return using econometric models. The variables of the CANSLIM model include the percentage of seasonal earnings, the percent of change in annual profit, the new price, level Free Float Stock, the leading, the support of institutional investors, and the direction of the market (changes in the total index). The study also weighs stock by the Fuzzy-AHP using CANSLIM criteria, and measures its efficiency using TOPSIS technique is ranked annually. Population of the study includes 73 companies listed at stock exchange during 2010-2017 Multi-variable regression analysis based on synthetic and panel data was used. Results of testing hypotheses revealed direct effects of rating factors: percent of seasonal earnings change, percentage of annual profit changes, industry leading companies, free float stocks, CANSLIM model on stock returns.

Given the variety of factors influencing on financial decision making and subjective nature of the most decisions is only part of their features associated with Multi-Criteria Decision Making. The aim of study is the rating of companies at TSE based on fundamental analysis and the appraisal of investor’s utility during the period of 1390 to 1396 years. So first, after determining the weights of indicators used based on the opinion the experts and using the ARAS method, the companies have been ranked and then their utility basis on stochastic dominance method have been investigated. The findings of research show that the first-order stochastic dominance cannot be identified. However the result ofThe Davidson test for the stochastic dominance of the second and third order indicate that the high-rating stocks has dominance to low-rating stocks.

Investors and other contributors to stock exchange need a variety of tools, measures, and information in order to make decisions. One of the most common tools and criteria of decision makers is price-to earnings per share ratio. As a result, investors are in pursuit of ways to have a better assessment and forecast of price and dividends and get the highest returns on their investment. Previous research shows that neural networks have better predictability than statistical models. Thus, Harmony Search algorithm and neural network have been used in this work, since achieving the best forecast is more likely. For this purpose, a sample consisting of 87 companies has been selected from those listed at the Tehran Stock Exchange over a 10-year period (2006-2015). The results show the high accuracy of the designed model that predicts the price-to-earnings ratio at the stock exchange by hybridizing the balanced search algorithm with neural network.

PFM Revaluation is the replacement fair value of fixed assets instead of their historical value. Since the historical cost model is causing the difference between the current value and book value of assets, revaluation of assets can help the transparency and relevance of financial statements.In recent years, Increased capital firms, due to the assets revaluation has been declared exempt from tax.because of the types of capital increases emerging capital market of the country, the consequences and implications are not been fully investigated. In this paper, the fundamental analysis framework will be based on the analysis of Capital Increase .Fundamental analysis shows that, Although the Capital Increase from the location is associated advantages such as increased equity and borrowing capacity but it Causes the decrease of financial ratios, growth rates ranging from IGR and SGR Lower than the intrinsic value of the shares and decrease the P/E, at the risk and expected return of equity implications.

Technical trading strategies assume that past price trends predict future ones. Their application may be profitable if the past trend reflects fundamental information that has not yet been fully priced. However, if the trend merely reflects temporary pricing pressures, technical trading will presumably fail. We argue that using financial statements as an additional source of information helps to avoid such failure. We implement a trading strategy that uses operating cash flows to identify enduring past price upturns and composite with momentum and contrarian strategy. In this study, using panel data, the impact of technical and fundamental strategies independently and in combination on stock returns 90 companies listed in the Tehran Stock Exchange, in the period 1387 to 1392 were studied. For this purpose, the stock return as dependent variable and momentum, reverse and operating cash flow are considered as independent variables. The results show that due to the timing and strategies have been used to form portfolios, hybrid strategy is best returns.

What is important for the users of financial information is the output of the financial system, not the accounting principles and practices, because it helps them achieve their goals. The main objective of investors is maximizing their wealth. Wealth depends on two factors included risk and return. That's why the prediction of these factors is crucial to the shareholders. Therefore, they use any tool that can help them reach these goals. One of these tools with the increasing usage in recent years is financial ratio. Financial ratios are one of the most common methods to analyze financial information. These ratios are summary of financial statements and their application and interpretation is easier. Hence the aim of this article is to review the studies on the role of financial ratios to predict stock returns as one of the main objectives of the shareholders. In this study that refers to the domestic research, the results indicate that profitability ratios have higher share to predict stock returns compared with other groups of financial ratios. Findings show that ROA and ROE have the most ability to explain stock returns changes

This paper takes fundamental analysis research beyond the spatial and temporal bounds of previous studies. It was investigated that how detailed financial statement data enter the decisions of market makers by examining how current changes in the fundamental signals chosen can provide information on subsequent earnings changes. Using Tehran Stock Exchange’s firms data from 2003 to 2012, the role of fundamental signals for prediction of future earnings changes was tested. In addition, the influence of contextual factors including prior earnings news and macroeconomic variables (GDP growth and inflation) on the relationship between fundamental signals and future earnings changes was investigated. Results indicate that the fundamental signals are significant predictors of short-term but not long-term future earnings changes. Moreover, prior earnings news doesn’t affect earnings predictability, but this predictability is significantly higher in lower GDP and higher inflation periods. In addition to corroborating prior research with fundamental analysis, this research adds to what has previously been conducted and extends investigations with examination of the predictive link between the fundamental signals and future earnings change by introducing prior earnings news and macroeconomic conditions as contextual factors in order to look for a possible effect which has not been investigated in prior research.

How to select shares in the Stock Exchange is one of the main concerns of investors in this market is the selected share or basket of shares that the profit, earnings per share increased prices and the best is important For this reason many ways to determine if your portfolio is created and introduced. Most of these methods to select and decide a proper information and financial analysis are used. This study sought to determine appropriate models for investment decisions. In this regard, effective criteria to select the portfolio of Bynyady used in the analysis are considered. The importance of each criterion is examined through Shannon's entropy. Then the ranking of the sample, including petrochemical companies are members of the exchange, the techniques SAW, TOPSIS, ELECTR will be used. For this purpose, the average thirteen-year-old real data, in the period of 80 to 92 used The result show that the use of Mulite- criteria approach leads to different finally Using the Average rating can pay decisions.

One of the issues that always has been considered is selecting stocks for profitable investments in financial markets. If the investor decides reasonably in the stock selection, a return more than the market average could be achieved. Comparing different companies based on the industry which the company belongs to, and identifying the premier industries through analysis of their efficiency could be useful guideline for stakeholders of this field. The main purpose of this research is ranking the stock industry to help the efficiency of capital markets applying the data envelopment analysis. The nature of the model is constant return to scale and input-oriented that 67 companies in 16 industries were studied and finally 7 industries were introduced as efficient and 9 other as non-efficient. Then determining the efficiency boundary, the inefficient industries are ranking and to improve their performance, some units were introduced as reference units.

Stock Exchange holds a special place in countries’ financial system and many investors tend to invest (buy and sell) in this market; however, it is considered one of the most high-risk markets. Finding a good place for investment, especially in exchange market, has always been one of the most stressful decisions for investors to make. In such a market, investors who analyze the market with a more accurate vision and buy good shares are successful. To do this kind of analysis, employing a good and powerful investment model is helpful. This study is an effort to determine factors that investors must consider in order to have safe and successful investments. To find the factors, experts’ views are considered. In order to correctly model the conditions of uncertainty, fuzzy Delphi method (FDM) was employed. Research Question In this study, attempts have been made to address the following question: - What are the appropriate factors to evaluate and compare companies? In this study, data was collected through a questionnaire. In order to develop the questionnaire, a list of evaluation factors was gathered from literatures. Nineteen factors were found and put into the questionnaire. Then, experts [4 faculty members and 8 official Stock Exchange specialists (Brokers)] were asked to evaluate the factors by rating them from high to low; they were also asked to add to the list of evaluation factors if necessary. The questionnaire provided respondents with three sets of response choices: high, medium, and low. It is important to mention that faculty were asked to confirm the validity of questionnaire. Gathered data were then processed. Considering the steps of fuzzy Delphi method, certain numbers that were announced by experts must be converted to fuzzy numbers. The fuzzy numbers used in this study were trapezoidal fuzzy numbers. Therefore, the fuzzy score for each range (high, medium, low) was found to be (6,8,10,10), (3,4,6,7), and (0,0,2,4) for high, medium, and low range, respectively. Hence, the certain (de-fuzzy) scores for each range were 8.5, 5, and 1.5, respectively. Then, the last step of the first round of fuzzy Delphi method was finished by finding the average of experts’ evaluation of each factor through necessary calculations. In order to reach a consensus on evaluation factors gathered for the purpose of this study, fuzzy Delphi method must be continued. Therefore, a new questionnaire, which was also validated by faculty, was developed. For each expert, the new questionnaire also contained the difference between his/her evaluation number of each factor and the average calculated in previous step. All experts were then asked to either improve or confirm their evaluations. Collecting the second questionnaire, the average of experts’ evaluation numbers for each factor was again calculated. The new averages were compared with corresponding results from previous round and the difference between two numbers for each factor was calculated. In order to reach a consensus on each evaluation factor, it was stipulated that the difference must not change dramatically. The results of the second round reveal that experts reach the consensus on only two factors. Hence, the fuzzy Delphi method must be continued. The process was repeated 5 times until consensus on all factors was reached. Consequently, the qualified evaluation factors must be determined. Based on some investigations, it was decided that only factors with more than 2/3 (approximately 66%) of all scores to be the final factors of this study. It implies that only evaluation factors with scores greater or equal to 6.16 are qualified to be considered. After finishing all required calculation, it was found that 16 factors have the qualified score to be as the final factors. Thus far, final evaluation factors were selected. The final factors that can be categorized in 4 groups of Liquidity, Profitability, Market Value, and Growth are as follows: Quick Ratio, Earnings Per Share (EPS), Return on Equity (ROE), Operating Profit Margin, Basic Earnings Power Ratio (BEP), Dividend Per Share to Price Ratio, Earnings Per Share Coverage, Dividend Per Share (DPS), Cost of Goods Sold (COGS) to Sales Ratio, Price-Earnings Ratio(P/E), Intrinsic Value Per Share, Equity Growth, Earnings Per Share Growth, Operating Profit Growth, Sales Growth, and Capital Growth. Discussion and In order to be able to invest correctly, employing a good investment model can be very helpful. This study was an effort to determine all important evaluation factors that must be considered by investors to choose a good investment. To find the factors, experts’ opinions were considered. The final results that have been presented as a list of factors, not only must be complete and comprehensive, it also must be easy, user-friendly, and fast. It is important because it serves investors for whom time is an essential factor in investment, especially in a market such as exchange. In this study, to achieve such a result, the following steps were taken: first, searching the literature, a primarily list of important evaluation factors was prepared and experts were asked to evaluate the factors. In selecting the factors, attempts have been made to eschew the redundancy and similarity of factors. It was also tried to choose factors that have huge impact on evaluating companies. Then, all selected factors were put into a questionnaire and distributed between experts. It is important to mention that experts were also asked to add to the list of evaluation factors, if necessary. Adding this option to the questionnaire reduced the possibility of dropping any important factor. Eventually, using fuzzy Delphi method, the best factors were selected and presented as the final result.

with due attention to importance of investment in stock exchange and special attention of governments to prospering of this part of economy، in this research we want to introduce the best method of investment between two specialized common methods namely fundamental analysis and technical analysis. It is claimed by the investigator that investment on base of fundamental analysis is more efficient than by technical analysis. Therefore average efficiency of each method should be accounted and then compare with each other. This investigation for purpose of objective is applying and for purpose of method is descriptive - comparative and by nature is post-happening and considers past quantitative information. The results show that efficiency of fundamental analysis is more than technical analysis through the two years period of study and it verify investigator claim.

In the fundamental analysis، it is claimed that an increase in the ratio of selling، general، and administrative costs to sales (SG&A) represents management inefficiency in controlling costs and could be interpreted as negative signal about future profitability. This ignores some important aspects of SG&A cost behavior since both unchanged and sticky costs may cause the ratio of SG&A costs to sales increase. In this case، an increase in the SG&A cost ratio may actually convey positive information about managers’ expectations about future earnings. In this research، the impact of cost behavior on the relationship between future profitability and SG&A ratio was examined، using a sample of 137 firms during 1380 to 1389. The findings show that there is a negative relationship between future earnings and SG&A cost ratio in sales-increasing periods. But، inconsistent with traditional interpretation of SG&A cost changes، future earnings are positively related to changes in the SG&A cost ratio in the periods in which sales decline، and that the higher the SG&A cost ratio، the stronger the positive relationship between future earnings and SG&A cost ratio. Also، it was found that after eliminating the impact of cost behavior، the increase in SG&A cost ratio causes increase in the future earnings in both revenue-increasing and revenue-decreasing periods.

This study (for the first time) examined the way investment managers of mutual funds invest, by using questionnaire method. Respondents to the questionnaire are investment managers of mutual funds in Iran. The investment managers are asked to determine the use of each of methods such as technical & fundamental analysis, Modern Portfolio Theory, bulletins, confidential information and market rumors, for market forecasting and selecting assets properly and timely. The research statistic population includes investment managers of active mutual funds in Iran. Questionnaires were sent to all of them, and 40 percent of the questionnaires were returned. The findings of this study show that investment managers always pay most of their attention to fundamental analyses and then published bulletins; they rarely use technical analysis indicators (especially in the long term) and Modern Portfolio Theory (especially in the short term). Also investment managers are reluctant to use confidential information and market rumors in any time intervals.

In this paper, a model has been provided for selecting right portfolio in stock exchange. The ranking of financial industries and companies has been applied for the selection of the right stock in this model. These rankings have been done through PROMETHEE Decision- making Method. Technical Analysis aims to determine the right time to buy and sell the superior stocks. A survey study is also done for identifying effective criteria in the evaluation of industry and company. The model developed will be applied in Tehran Stock Exchange (TSE) as a real case to solve the problem. It is concluded that, by using both Fundamental and Technical Analysis, an investor can get higher return on stocks instead of using just one individual analysis. In other words, while Fundamental Analysis distinguishes which stocks is the best to buy, Technical Analysis represents when to buy the superior stocks.