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کاربرد نوع شرط:
- جایگاه : پژوهشی
- مجله: Iranian Journal of Finance
- نوع مقاله: Journal Article
- کلمات کلیدی: Stock Returns,Investors' Sentiment,Accounting information risk Investors’ trading behavior,Fama-French approach
- چکیده:
- چکیده انگلیسی: Behavioral finance is a new issue raised by some financial intellectuals over the past two decades and has been quickly addressed by professors, experts, and students throughout the world. Investigating the factors affecting investment decisions is carried out in the field of behavioral finance; in other words, the focus of behavioral finance is on the specific charac-teristics of human behavior and applying them in asset pricing. Empirically, pricing models rarely include psychological factors, but the noticeable point is that nowadays, researchers have found behavioral factors influencing empirical asset pricing models that can manipulate returns on asset mispricing. Behavioral asset pricing is the result of applying behavioral finance theories within traditional asset pricing theories. Thus, despite the existence of many asset pricing models, due to their weaknesses and lack of comprehensiveness, as well as the necessity of reviewing behavioral factors, this study aims to model asset pricing through behavioral models. Using the data from 141 listed firms in Tehran Stock Exchange over the years 2008 to 2017 and multivariate regression, this study is an attempts to model asset pric-ing through employing behavioral models and Fama-French approach. Using Fama-French approach, the results showed that accounting information risk, investors’ trading behavior, and investors' sentiment have a direct and significant impact on asset pricing.
- انتشار مقاله: 21-03-1398
- نویسندگان: Mohammad Nasiri,Nouroz Nourollahzadeh,Fatemeh Sarraf,Mohsen Hamidian
- مشاهده
- جایگاه : پژوهشی
- مجله: International Journal of Engineering, Transactions A: Basics
- نوع مقاله: Journal Article
- کلمات کلیدی: Genetic Algorithm,power losses,TOU,Daily Load Profile,ENS,Electric Distribution System
- چکیده:
- چکیده انگلیسی: Increased electric energy consumption in recent years, associated economic problems, reduced reliability and increased power losses in electric networks. One of the main solutions in smart grids to overcome the mentioned problems is demand response programs. In demand response programs, operators apply time-varying tariffs to consumers, and convince them to change their consumption pattern. Among the demand response programs, the most effective program for subscribers who receive electricity at fixed price is time-of-use (TOU) pricing. This paper offers a new approach to implementing TOU program, which is determining the scheduling and pricing of TOU tariff simultaneously taking into account the objectives of smoothing the load profile, reducing the losses and energy not supplied. The proposed method is simulated in MATLAB, and has been evaluated on an urban distribution network in Yazd Electrical Distribution Company (YEDC) that feeds 35 distribution transformers (20/0.4kV) through a radial feeder. Results show that implementation of this method has only a minor increase in cost and reduction in consumption for subscribers, and makes load profile more smooth, improve reliability and reduce power losses.
- انتشار مقاله: 11-10-1348
- نویسندگان: Ali Reza Sedighi,Mohsen Hamidian
- مشاهده
- جایگاه : پژوهشی
- مجله: International Journal of Finance and Managerial Accounting
- نوع مقاله: Journal Article
- کلمات کلیدی: Accounting,Speculativem,bubble,Mental
- چکیده:
- چکیده انگلیسی: The aim of the study " The Different Role of Mental Accounting on Optimal Portfolio Based on Speculative Bubble on companies listed in the Tehran Stock Exchange" is the 10-year study period listed in the Tehran Stock Exchange during 2008-2017 were analyzed.The data of 110 firms were analyzed by using statistical softwares including Matlab, spss20, Eviews7 and Lingo in the studied years. In this research, mental accounting is based on Fernandez, The speculative bubble based on the gilium pattern are used as a risk measurement indicator. The result of testing the above hypotheses showed that for the calculated returns because it is greater than the error level, the hypothesis of equality of the average returns of the portfolios is not rejected. In terms of speculation bubble (subject to speculation) based on subjective accounting there is no significant difference and efficiency based on standard deviation index is not higher. The result of the statistical test of these hypotheses shows that the significance value for the calculated returns is greater than the error level, the hypothesis of mean inequality of portfolio returns (research hypothesis) is rejected and in other words the speculative bubble portfolio returns (greater than Portfolio returns are not without bubbles.
- انتشار مقاله: 22-10-1398
- نویسندگان: Maryam Saberi,Roya Darabi,Mohsenmohsen Hamidian
- مشاهده
- جایگاه : پژوهشی
- مجله: International Journal of Finance and Managerial Accounting
- نوع مقاله: Journal Article
- کلمات کلیدی: CEO Overconfidence,Naive Bayesian Classification Algorithm,Probit Regression
- چکیده:
- چکیده انگلیسی: Corporate directors are influenced by overconfidence, which is one of the personality traits of individuals; it may take irrational decisions that will have a significant impact on the company's performance in the long run. The purpose of this paper is to validate and compare the Naive Bayesian Classification algorithm and probit regression in the prediction of Management's overconfident at present and in the future. Financial during the years are 2012 to 2017. To support the theoretical results, the samples were the companies admitted to the Tehran Stock Exchange, (financial data of 1292 companies/year in total). Data collection in the theoretical part of the study benefitted from the library method, and for calculating data, Excel software was used, and in order to test the research hypotheses Matlab 2017 and Eviews10.0 were used. The empirical findings demonstrate that, Gained nonlinear prediction model of the Naive Bayes Classification algorithm, has high ability to predict, and the Probit regression model, has limited ability to predict the over-confidence of management. Finally, the artificial intelligence prediction model (naive Bayesian classification algorithm) has better result compared with statistical binary regression prediction model (probit regression).
- انتشار مقاله: 23-10-1397
- نویسندگان: Shokoufeh Etebar,Roya Darabi,Mohsen Hamidian,Seiyedeh Mahbobeh Jafari
- مشاهده
- جایگاه : پژوهشی
- مجله: Advances in Mathematical Finance and Application
- نوع مقاله: Journal Article
- کلمات کلیدی: Stock Returns,Momentum,Market Conditions
- چکیده:
- چکیده انگلیسی: The purpose of this study is to compare the impacts of momentum on stock returns of companies listed in Tehran Stock Exchange in different market conditions. For this purpose, the sample size is 120 months from 2008 to 2017. The research hypotheses are estimated using multivariate linear regression using time series method. Based on the results of the hypotheses test, the momentum in each of the market conditions, including normal, ascending and descending conditions, has a positive and direct effect on the stock returns of the companies listed in Tehran Stock Exchange, which indicates the principle of investors' insatiability in the stock exchange Tehran seeking to maximize its return on investment with a certain risk that in a downside mode of market, their insatiability exits less and faster than their momentum conditions, which is a reason for investors' loss evasion in this situation.
- انتشار مقاله: 26-08-1397
- نویسندگان: Alireza Ghiyasvand,Roya Darabi,Mohsen Hamidian
- مشاهده
- جایگاه : پژوهشی
- مجله: Advances in Mathematical Finance and Application
- نوع مقاله: Journal Article
- کلمات کلیدی: financial,Performance,TOPSIS
- چکیده:
- چکیده انگلیسی: Due to the sublimation and perfection of human knowledge in economics, the concept of efficiency developed in the past two decades and the measurement of it, based on different theories and practice. In economics, efficiency means the maximum of possible output from a certain amount of input. The efficiency is very important for developing countries Because these countries face to a shortage of inputs, production factors and technologies. So the usage of existing resources is critical for these countries. This paper aims to evaluate and rank the financial performance of the chemical firms listed in Tehran stock exchange. We Use the data environment analysis and TOPSIS methods. This research includes one major question that which company performs better due to the financial ratios. The sample includes the firms in Tehran Stock Exchange within a 3-year period (2013-2015). The Results show that Ahvas Petrochemical company, Persian Gulf Petrochemical Industry company and Iran Chemical Industries company are more efficient than others.
- انتشار مقاله: 20-03-1396
- نویسندگان: Ali Asghar Anvary Rostami,Maryam Saberi,Mohsen Hamidian,Mahdihe Esfandiyar Pour
- مشاهده
- جایگاه : پژوهشی
- مجله: Advances in Mathematical Finance and Application
- نوع مقاله: Journal Article
- کلمات کلیدی: Loss functions,Portfolio allocation,Evaluating forecasts
- چکیده:
- چکیده انگلیسی: Portfolio theory assumes that investors accept risk. This means thatin the equal rate of return on the two assets, the assets were chosenthat have a lower risk level. Modern portfolio theory is accepted byinvestors who believe that they are not cope with the market. Sothey keep many different types of securities in order to access theoptimum efficiency rate that is close to the rate of return on market.One way to control investment risk is establishing the portfolioshares. There are many ways to choose the optimal portfolioshares. Among these methods in this study we use loss functions.For this, we choose all firms from the year2011to the end of 2015that had been a member in the Tehran Stock Exchange. The resultsof this research show that the likelihood functions have the bestperformance in Forecasting the optimal portfolio allocationprob-lem.
- انتشار مقاله: 20-07-1395
- نویسندگان: Adel Azar,Mohsen Hamidian,Maryam Saberi,Mohammad Norozi
- مشاهده