درخت حوزه‌های تخصصی

Exporting agricultural products is considered as one of the strategies for developing non-oil exports and achieving sustainable economic growth in developing countries. Saffron, as an export commodity, holds particular significance in Iran's non-oil exports. Given Iran's position among the top four saffron-exporting countries globally, this study aims to prioritize Iran's saffron target markets based on market competition indices and calculate its relative advantage and export stability index in the world market and Iran's export target countries. Comparison of the global market structure of the product during 2003 to 2022 revealed that despite the significant shares of Iran, Spain, England, and Nigeria in most years, the market structure has been characterized by a multi-sided monopoly, open and closed, and in some years dominated by oligopoly, indicating an increase in the number of competitors and the competitiveness of the export market for this product. Iran, with an average share of 13.6% in the saffron export market and producing over 80% of saffron, does not have a direct share in global exports, and most of Iran's saffron is exported to countries such as the UAE, Spain, China, and Oman, and then re-exported to other countries, for which strategies such as market expansion and branding need to be prioritized. The results showed that in 2022, four countries, Nigeria, Sri Lanka, Iran, and Spain, accounted for 93% of the total world exports, and Iran ranked second in terms of export volume in the saffron export market during the study period. Also, Iran had an export stability index of less than one (0.96) but the trend of this index indicates a decrease in Iran's stability. The results showed that the majority of Iran's saffron exports are concentrated in only four countries, with the composition of these countries varying over time. To enhance market stability and growth, it is crucial to expand the target export markets. Prioritization should be given to China, UAE, Spain, India, USA, Germany, France, Italy, Sweden, and Kuwait, with average priority ranks of 4.15, 6.85, 7.7, 7.95, 8.9, 12.3, 14.35, 15.25, 15.5, and 16.45 respectively. Furthermore, the results indicated that the export market for saffron is oligopolistic. Therefore, it is essential for all exporting countries to collaborate in determining the price and market share for each country. This collaborative approach can help in stabilizing the market, ensuring fair pricing, and promoting sustainable growth in the saffron industry.

In traditional Data Envelopment Analysis (DEA) techniques, in order to calculate the efficiency or performance score, for each decision-making unit (DMU), specific and individual DEA models are designed and resolved. When the number of DMUs are immense, due to an increase in complications, the skewed or outdated, calculating methods to compute efficiency, ranking and …. may not prove to be economical. The key objective of the proposed algorithm is to segregate the efficient units from that of the other units. In order to gain access to this objective, effectual indexes were created; and taken to assist, in regards the DEA concepts and the type of business (under study), to survey the indexes, which were relatively operative. Subsequently, with the help of one of the clustering techniques and the ‘concept of dominance’, the efficient units were absolved from the inefficient ones and a DEA model was developed from an aggregate of the efficient units. By eliminating the inefficient units, the number of units which played a role in the construction of a DEA model, diminished. As a result, the speed of the computational process of the scores related to the efficient units increased. The algorithm designed to measure the various branches of one of the mercantile banks of Iran with financial indexes was implemented; resulting in the fact that, the algorithm has the capacity of gaining expansion towards big data.

Using jumps in stock prices as a proxy for information shocks to examine investors' reactions to significant events is the most effective method for identifying information shocks. Compared to other studies, this method has advantages listed at the end of the literature review. We provide evidence consistent with short-term overreaction on the Tehran Stock Exchange. Thus, through the contrarian investment strategy, i.e., buying stocks with negative lagged jump returns and selling those with positive lagged jump returns, earn significantly positive returns over the next one- to three-month horizons. This research analyzed the adjusted daily closing prices of the top thirty stocks on the Tehran Stock Exchange in terms of market value and turnover during 2013-2020.

The stock market is one of the main components of the economy, and various factors cause fluctuations in it, one of which is the effect of investors' behavior. Therefore, present study seeks to answer the question of whether the feelings and sentiments of investors might intensify the fluctuations in the Tehran Stock Exchange or not. To answer this question, at first, in order to quantify sentiments, as non-abstract variables, the Equity Market Sentiment Index (EMSI) was used that investors are classified in 5 categories of completely risk-averse, risk-averse, neutral-risk, risk-taking and completely risk-taking. Using GARCHi-in-Mean, results indicate that the sentiments of investors will result in greater fluctuations in the Tehran Stock Exchange. Hence, if fluctuation is considered an indicator of market risk, the excitement associated with an abnormal rise in volumes will increase that risk.