List of Articles Abdolmajid Abdolbaghi Ataabadi

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  1 - The Effectiveness of the Automatic System of Fuzzy Logic-Based Technical Patterns Recognition: Evidence from Tehran Stock Exchange
  Abdolmajid Abdolbaghi Ataabadi Sayyed Mohammad Reza Davoodi Mohammad Salimi Bani
  10.22034/amfa.2019.585179.1185
  The present research proposes an automatic system based on moving average (MA) and fuzzy logic to recognize technical analysis patterns including head and shoulder patterns, triangle patterns and broadening patterns in the Tehran Stock Exchange. The automatic system was More

  The present research proposes an automatic system based on moving average (MA) and fuzzy logic to recognize technical analysis patterns including head and shoulder patterns, triangle patterns and broadening patterns in the Tehran Stock Exchange. The automatic system was used on 38 indicators of Tehran Stock Exchange within the period 2014-2017 in order to evaluate the effectiveness of technical patterns. Having compared the conditional distribution of daily returns under the condition of the discovered patterns and the unconditional distribution of returns at various levels of confidence driven from fuzzy logic with the mean returns of all normalized market indicators, we observed that in the desired period, after recognizing the pattern, all patterns investigated at the confidence level 0.95 with a fuzzy point 0.5 contained useful information, practically leading to abnormal returns. Manuscript profile
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  2 - Designing and evaluating the profitability of linear trading system based on the technical analysis and correctional property
  CharaghAli Bakhtiyari Asl Sayyed Mohammad Reza Davoodi Abdolmajid Abdolbaghi Ataabadi
  10.22034/amfa.2021.1906285.1474
  Traders in the capital market always seek methods to make full use of available information and combine them to find the best buying and selling strategy. The present study uses a linear hybrid system to combine 106 signals from moving averages oscillators and RSI signa More

  Traders in the capital market always seek methods to make full use of available information and combine them to find the best buying and selling strategy. The present study uses a linear hybrid system to combine 106 signals from moving averages oscillators and RSI signals in the technical analysis along with two buy and sell bonds. In addition, the system has correctional property and modifies its parameters over time and according to new information. The result of the research on the Tehran Exchange overall index in the period 1380 to 1397 indicates that the system after the optimal training on training data has an average of daily returns of 0/0025, 0/0048 risk, and a daily Sharp ratio of 0/52, which is better than the individual performance of each signal and market performance in daily average return and sharp ratio criterion. Manuscript profile
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  3 - Multi-objective possibility model for selecting the optimal stock portfolio
  Abdolmajid Abdolbaghi Ataabadi Alireza Nazemi Masoumeh Saki
  10.22034/amfa.2022.1952682.1705
  In this paper, we use fuzzy numbers and possibility theory to model possibility. The purpose of this work is to determine the optimal investment model based on the neural network method for fuzzy LR, trapezoidal and triangular numbers in an optimal portfolio. It is list More

  In this paper, we use fuzzy numbers and possibility theory to model possibility. The purpose of this work is to determine the optimal investment model based on the neural network method for fuzzy LR, trapezoidal and triangular numbers in an optimal portfolio. It is listed on the Tehran Stock Exchange to maximize "returns" and reduce "risk" to find the optimal portfolio. Therefore, to achieve this goal, the problem of multi-objective nonlinear programming is addressed. Also, by substituting the mean-variance model and the standard mean deviation instead of the Markowitz mean-variance model, the selection of the optimal portfolio in the possible space is examined. Finally, after calculating the model of the possibility of fuzzy numbers, we reach the optimal stock portfolio, which can be used to set the stock portfolio that has the highest returns and the lowest risk. Manuscript profile
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  4 - Analytical and numerical solutions for the pricing of a combination of two financial derivatives in a market under Hull-White model
  Hossein Sahebi Fard Elham Dastranj Abdolmajid Abdolbaghi Ataabadi
  10.22034/amfa.2021.1902303.1447
  In this paper‎ a combination of two financial derivatives in financial markets modelled of future interest rates is presented and evaluated. In fact ‎European option pricing is driven when zero-coupon bond is considered as underlying asset in a market under Hull More

  In this paper‎ a combination of two financial derivatives in financial markets modelled of future interest rates is presented and evaluated. In fact ‎European option pricing is driven when zero-coupon bond is considered as underlying asset in a market under Hull-White model‎. ‎For this purpose, the exact solutions of the valuation of this bond option are driven, using Lie group symmetries method. Then in the next part, the finite difference method is applied to find numerical solutions for assumed bond option pricing. Then the significance and usefulness of this approximated method is comparing with the exact solutions by some plotted graphs. Manuscript profile
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  5 - Option pricing with artificial neural network in a time dependent market
  Mehran Araghi Elham Dastranj Abdolmajid Abdolbaghi Ataabadi Hossein Sahebi Fard
  In this article, the pricing of option contracts is discussed using the Mikhailov and Nogel model and the artificial neural network method. The purpose of this research is to investigate and compare the performance of various types of activator functions available in ar More

  In this article, the pricing of option contracts is discussed using the Mikhailov and Nogel model and the artificial neural network method. The purpose of this research is to investigate and compare the performance of various types of activator functions available in artificial neural networks for the pricing of option contracts. The Mikhailov and Nogel model is the same model that is dependent on time. In the design of the artificial neural network required for this research, the parameters of the Mikhailov and Nogel model have been used as network inputs, as well as 700 data from the daily price of stock options available in the Tehran Stock Exchange market (in 2021) as the net-work output. The first 600 data are considered for learning and the remaining data for comparison and conclusion. At first, the pricing is done with 4 commonly used activator functions, and then the results of each are com-pared with the real prices of the Tehran Stock Exchange to determine which item provides a more accurate forecast. The results obtained from this re-search show that among the activator functions available in this research, the ReLU activator function performs better than other activator functions. Manuscript profile