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Open Access Article
1 - Modelling Crowdfunding Ensemble Learning Prediction
Mehran Saeidi Aghdam Akbar Alam Tabriz Alireza Bahiraie Ahmad SadeghiCrowdfunding is a new technology-enabled innovative process that is changing the capital market space. Internet-based applications, particularly those related to Web 2.0, have had a significant impact on sectors of society such as education, business, and medicine. The MoreCrowdfunding is a new technology-enabled innovative process that is changing the capital market space. Internet-based applications, particularly those related to Web 2.0, have had a significant impact on sectors of society such as education, business, and medicine. The goal of this research is to fill a gap in the literature on mathematical modelling and prediction of ensemble learning in order to evaluate crowdfunding projects. The Mathematical model determines the cost of funding for the entrepreneur and the return investors will receive per period. A correct financial model is essential in order to keep all three stakeholders involved in the long term. The results show the designed model improved performance in predicting the evaluation of success or failure of Crowdfunding projects. Manuscript profile -
Open Access Article
2 - Visualized Portfolio Optimization of stock market: Case of TSE
Fatemeh Lakzaie Alireza Bahiraie saeed mohammadianAn investment portfolio is a collection of financial assets consisting of investment tools such as stocks, bonds, and bank deposits, among others, which are held by a person or a group of persons. In this research, we use the Markowitz model to optimize the stock portfo MoreAn investment portfolio is a collection of financial assets consisting of investment tools such as stocks, bonds, and bank deposits, among others, which are held by a person or a group of persons. In this research, we use the Markowitz model to optimize the stock portfolio and identify the minimum spanning tree (MST) structure in the portfolio consisting of 50 stocks traded in the TSE. The observable which is used to detect the minimum spanning tree (MST) of the stocks of a given portfolio is the synchronous correlation coefficient of the daily difference of logarithm of closure price of stocks. The correlation coefficient is calculated between all the possible pairs of stocks present in the portfolio in a given time course. The goal of the present study is to obtain the taxonomy of a portfolio of stocks traded in the TSE by using the information of time series of stock prices only. In this research, report results obtained by investigating the portfolio of the stocks used to compute 50 stocks of the Iran Stock Exchange in the time period from January 2012 to October 2022. Manuscript profile
List of Articles alireza bahiraie
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