List of Articles رگرسیون فازی

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  1 - Presenting a model for predicting the Tehran Stock Exchange Index using ANFIS and fuzzy regression
  Mohammad Hossein Keshavarz Mohammad Reza Feylizadeh Ayad Hendalianpour
  The purpose of this study is to provide a prediction model for the Tehran Stock Exchange Index using Adaptive Neuro-Fuzzy Inference System (ANFIS) and fuzzy regression analysis. The behavior of this index is nonlinear and chaotic that traditional methods do not predict More

  The purpose of this study is to provide a prediction model for the Tehran Stock Exchange Index using Adaptive Neuro-Fuzzy Inference System (ANFIS) and fuzzy regression analysis. The behavior of this index is nonlinear and chaotic that traditional methods do not predict accurately. Hence, using the above two tools and identifying three macroeconomic variables including inflation rate, exchange rate and crude oil price as independent variables, we predicted the index of the total stock index for the next week. Then, the modeling was performed using the above three variables. By comparing the results, ANFIS performance was better than fuzzy regression. The Root Mean Square Error Performance criterion was obtained for the ANFIS output of 0.021248. The prediction of the next week showed an error reduction for both tools and ANFIS again with an error value of 0.007933, yielded superior performance of the study. Also, the model with four inputs was more accurate compared to the model with three inputs. The emphasis on using macroeconomic variables, predicting the next week's index number, using the two tools mentioned, analyzing the sensitivity of the models during the research are the characteristics of this research. This research can be used by all companies in the stock exchange, investors, brokers, and individuals and legal entities dealing in any way with the stock market. Manuscript profile
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  2 - Estimation of fuzzy parameters based on neural networks using trapezoidal data
  razieh naderkhani Mohammad Hassan Behzadi tahereh Razzaghnia rahman farnoosh
  Fuzzy regression is a generalized regression model that shows the relationship between independent and dependent variables in the fuzzy environment. Fuzzy linear regression analysis is the generalization of regression models that is appropriate using all data based on a More

  Fuzzy regression is a generalized regression model that shows the relationship between independent and dependent variables in the fuzzy environment. Fuzzy linear regression analysis is the generalization of regression models that is appropriate using all data based on a specific criterion. This paper uses an adaptive neural fuzzy inference system to analyze and predict a non-parametric fuzzy regression function with non-fuzzy inputs and symmetrical trapezoidal fuzzy outputs. To this end, a new hybrid algorithm is proposed in which fuzzy minimum squares and linear programming are used to optimize secondary weights. Algorithms are applied by multi layer validation to validate models. More precisely, the accuracy of the algorithms with simulations is fully confirmed. Finally, two simulation examples were used to examine the efficiency of the model, in which the data were defined as trapezoidal numbers and by teaching them and specifying the number of rules used, the unknown parameters were estimated. Manuscript profile
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  3 - Day of the Week Effect in Stock Returns by using Bootstrapping Fuzzy- GARCH Regression
  فاطمه بزازان شمس اله شیرین بخش ماسوله سولماز صفری
  This paper propounds to examine the day of the week effect on the returns of dailystock price entire index, in Tehran Stock Exchange market during 1383 to 1388.Various approaches have been presented for investigation about calendar effects onstock returns. We apply " Fu More

  This paper propounds to examine the day of the week effect on the returns of dailystock price entire index, in Tehran Stock Exchange market during 1383 to 1388.Various approaches have been presented for investigation about calendar effects onstock returns. We apply " Fuzzy regression with triangular membership function".This approach's base is, the fuzzification of the dummy variables through fuzzy logic.In fact, fuzzy logic regression enables us to capture the impression and nonlinearitiesin finance and human behavior which are main characteristics in finance industry andfurthermore, avoids the classification of dummy variables to values of one and zero, aswe do in the traditional statistical and econometric methodology. The paper concludesthat using fuzzy regression will lead to a positive effect on the returns on Sunday andnegative returns on Tuesday Manuscript profile
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  4 - بررسی ارتباط شفافیت مالی و اجتناب مالیاتی با توجه به مالکیت نهادی شرکت‌ها ( مطالعه موردی شرکت‌های بورس اوراق بهادار تهران )
  محمدرضا عباس زاده مرتضی فدایی محسن مفتونیان مائده بابایی کلاریجانی
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  5 - Investigating the Impact of Financial and Trade Sanctions on the Exchange Rate in Iran (Fuzzy Approach)
  Asghar Abolhasani Hestiani Mostafa Elmimoghadam Nasrin Mansouri Minoo Amini Milani
  10.30495/fed.2023.702185
  Abstract Exchange rate is one of the important economic variables that are affected by various factors. Since the exchange rate in any country is considered one of the basic indicators in determining the degree of international competition and explaining the internal s More

  Abstract Exchange rate is one of the important economic variables that are affected by various factors. Since the exchange rate in any country is considered one of the basic indicators in determining the degree of international competition and explaining the internal situation of that country's economy, with the aim of investigating the role of economic sanctions imposed on the exchange rate in Iran, this research was carried out. According to empirical studies, several visible and invisible factors have affected the exchange rate in the country; Factors that sometimes can not all be considered in one economic model; therefore, even with conventional methods, it is not possible to comment with certainty on the extent to which some of these factors affect the exchange rate. Based on this argument, in order to use an appropriate method, in order to investigate the effect of financial and commercial sanctions imposed on Iran along with other variables affecting the exchange rate in the period after the Islamic Revolution (1978-2020) from a fuzzy approach is used. The results show that severe economic sanctions with a high and strong fuzzy coefficient have had a positive and significant effect on the exchange rate in Iran. Also, liquidity, budget deficit, balance of payments, inflation and adaptive exchange rate expectations, respectively, after the severe sanctions, have had the greatest impact on increasing the exchange rate in recent years. The fuzzy coefficients obtained for the variables of oil revenues, the degree of openness of the economy, economic growth and interest rate on account of domestic investment deposit, indicate the negative effect of these variables on the exchange rate in Iran in this period. Manuscript profile
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  6 - ارتباط بین حاکمیت شرکتی و عملکرد شرکت بر مبنای رگرسیون فازی
  محمدرضا شورورزی محسن خلیلی حمید سلیمانی امید فروتن
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