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Open Access Article
1 - An Algorithmic Trading system Based on Machine Learning in Tehran Stock Exchange
Hamidreza Haddadian Morteza Baky Haskuee Gholamreza ZomorodianSuccessful trades in financial markets have to be conducted close to the key recurrent points. Researchers have recently developed diverse systems to help the identification of these points. Technical analysis is one of the most valid and all-purpose kinds of these syst MoreSuccessful trades in financial markets have to be conducted close to the key recurrent points. Researchers have recently developed diverse systems to help the identification of these points. Technical analysis is one of the most valid and all-purpose kinds of these systems. With its numerous rules, the technical analysis endeavors to create well-timed and correct signals so that these points are identified. However, one of the drawbacks of this system is its overdependence on human analysis and knowledge in selecting and applying these rules. Employing the three tools of genetic algorithm, fuzzy logic, and neural network, this study attempts to develop an intelligent trading system based on the recognized rules of the technical analysis. Indeed, the genetic algorithm will assist with the optimization of technical rules owing to computing complexities. The fuzzy inference will also help the recognition of the total current condition in the market. It is because a set of rules will be selected based on the market kind (trending or non-trending). Finally, the signal developed by every rule will be translated into a single result (buy, sell, or hold). The obtained results reveal that there is a statistically meaningful difference between a stock's buy and hold and the trading system proposed by this research. In other words, our proposed system displays an extremely higher profitability potential. Manuscript profile -
Open Access Article
2 - Portfolio optimization considering cardinality constraints and based on various risk factors using the differential evolution algorithm
Behnaz Ghadimi Mehrzad Minooei Gholamreza Zomorodian Mirfeiz FallahshamsAs the main achievement of the modern portfolio theory, portfolio diversifica-tion based on risk and return has attracted the attention of many researchers. The Markowitz mean-variance problem is a convex quadratic problem turned into a mixed-integer quadratic programmi MoreAs the main achievement of the modern portfolio theory, portfolio diversifica-tion based on risk and return has attracted the attention of many researchers. The Markowitz mean-variance problem is a convex quadratic problem turned into a mixed-integer quadratic programming problem when incorporating car-dinality constraints. Due to the high number of stocks in a market, this problem becomes an NP-hard problem. In this paper, a metaheuristic approach is pro-posed to solve the portfolio optimization problem with cardinality constraints using the differential evolution algorithm, while it is also intended to improve the solutions generated by the algorithm developed. In addition, variance, val-ue-at-risk, and conditional value-at-risk are assessed as risk measures. Candi-date models are solved for 50 top stocks introduced by the Tehran Stock Ex-change by considering the cardinality constraints of not more than five stocks within the portfolio and 24 trading periods. Finally, the obtained results are compared with the results of genetic algorithm. The results show that the pro-posed method has reached the optimal solution in a shorter time. Manuscript profile -
Open Access Article
3 - Analyzing the Effect of Monetary Volatility on the Iranian Stock Market
Nafiseh Vatanchi MirFaiz Falah Shams Lialestani Gholamreza ZomorodianNowadays, financial markets and especially the stock market are important and undeniable sources of financing for investment toward the economic growth and development of countries. These markets also have a tangible role as a basis for implementing monetary policy. Thi MoreNowadays, financial markets and especially the stock market are important and undeniable sources of financing for investment toward the economic growth and development of countries. These markets also have a tangible role as a basis for implementing monetary policy. This study aims to investigate the effect of monetary volatility on the seasonal performance of the Iranian stock market from April 2001 to March 2021.The TEDPIX index of the Tehran Stock Exchange was used for designing and explaining the research model for measuring monetary policy uncertainty in terms of the debt of banks to the Central Bank and to measure the Iranian stock market’s performance. With portfolio theory as the theoretical basis for the study, the housing price index and the exchange rate were added to the research model as other independent variables due to their importance to the portfolio of individuals. In this regard, monetary policy uncertainty was first calculated using the exponential general autoregressive conditional heteroskedastic (EGARCH) method. Then, the effect of uncertainty on the TEDPIX index was calculated using the vector auto regression (VAR) statistical method in EVIEWS 12. The findings indicate a significant negative correlation between monetary policy uncertainty and short and long term TEDPIX index. Moreover, exchange rate and housing price index has a significant positive effect on the TEDPIX index. Manuscript profile -
Open Access Article
4 - Effect of Oil Price Volatility and Petroleum Bloomberg Index on Stock Market Returns of Tehran Stock Exchange Using EGARCH Model
Gholamreza Zomorodian Laleh Barzegar Soghra Kazemi Mohammad PoortalebiThe present research aims to evaluate impacts of crude oil price return index, Bloomberg Petroleum Index and Bloomberg energy index on stock market returns of 121 companies listed in Tehran stock exchange in a 10 years' period from early 2006 to April 2016. First, expla MoreThe present research aims to evaluate impacts of crude oil price return index, Bloomberg Petroleum Index and Bloomberg energy index on stock market returns of 121 companies listed in Tehran stock exchange in a 10 years' period from early 2006 to April 2016. First, explanatory variables were aligned with petroleum products index mostly due to application of dollar data. Subsequently, to check variables stationary, Dickey-Fuller generalized test was considered and ARCH test was adopted to check for Heteroscedasticity in error terms and residual values. Finally, EGARCH was used to address model heteroscedasticity. The results showed that variations of Petroleum Bloomberg index, crude oil price and Bloomberg energy index could explain changes in Tehran stock exchange index returns. Any rise in oil prices increases total Stock Exchange returns. On the other hand, Stock Exchange index returns is aligned with Petroleum Bloomberg index.at the same time changes in Tehran stock exchange index returns was reversely correlated with changes in energy index return among others. Manuscript profile
List of Articles Gholamreza Zomorodian
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