Iranian Journal of Finance

Abstract This research uses a fuzzy Delphi approach to identify the dimensions and components of investor risk and financing for IT-based startup companies. The statistical population for this study consisted of 30 experts and university professors familiar with the research concepts surveyed to select the dimensions and components identified from the literature and prior research. The results from the fuzzy Delphi method showed that the financing and investor risk dimensions were selected in 9 dimensions and 29 components. The weighting results for the research dimensions and components using the Best-Worst Method (BWM) prioritized each. The weighting results indicate that the industry status ranked first, followed by scientific factors and other components, ranked third to ninth in the LINGO software. Additionally, the intensity of relationships among the research dimensions was assessed using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique. The analysis of the intensity of relationships among the dimensions shows that the government factors dimension had the highest numerical value based on the row sum, making it the most influential dimension among those examined in financing startup companies using the DEMATEL technique. Conversely, based on the D-R analysis, the geographic factors dimension received the lowest value and was recognized as the most affected dimension. Using the fuzzy Delphi method, this research has identified specific and novel dimensions and components, such as governmental, geographical, and scientific factors, which have been less addressed in the existing literature.

Abstract Banked based financial sector of Iran leads us to focus on the banking industry and its components. One of the important aspects of this industry is its coupling structure. In this paper, we have analyzed the collective behavior of Iran banking sector by Random Matrix Approach (RMT). This technique is useful for splitting the information part of the correlation matrix from the random region. This research confirms good compliance with random matrix predictions. By removing the market mode of the system the average of the banking cross-correlation matrix changes. Then, by calculation of the participation ratio, node participation ratio and relative participation ratios of these banks, it is shown that the collective behavior of the system is so fragile. Also, by applying local and global perturbations on the banking sector, it is shown that this system is very sensitive to the global perturbation and the mean value of cross-correlations decreases rapidly that means some banks have crucial effects in the market. 

Abstract Networks are useful tools for presenting the relationships between financial institutions. During the previous years, many scholars have found that using single-layer networks cannot properly characterize and explain complex systems. The purpose of this research is to introduce a multiplex network in order to analyze, as accurately as possible, all aspects of communication between banks in capital market of Iran. In this article, each bank represents a node and three layers of return, trading volume and market Cap have been presented for analyzing the idea of multiplex networks. We have used the Granger causality method to determine the direction between nodes. For understanding the topology structure of these layers, different concepts have been used. The research findings show that the value layer topology has a significant similarity with the trading volume layer. Also according to the measure of centrality it can be seen that the centrality varies in different layers.