چكيده به لاتين
This thesis identifies manifested and latent motivations, classification and modeling of speculation in Iran’s financial markets as well as making effort to present approaches for managing the mentioned motivations. The statistical sample includes ordinary people and active micro-investors in Iran’s financial markets; experts’ ideas were collected according to manifested interview for manifested motivations meanwhile doing latent unstructured -including indirect items, projection, and storytelling- for latent motivations, being enough for theoretical saturation. Summarizing and identifying of 27 main items of the questionnaire result in 251 samples. Finally, 12 motivations were categorized effectively on speculation out of which 10 were for manifested and 2 for latent ones. Exploratory and confirmatory factor analysis were utilized to reduce variables, while neural network and binary logistic regression for classification and modeling. This research is helpful for decision-makers and management teams of the central bank, ministry of economic affairs and finance, and ministry of industry, mine, and trade. Behavior not only in the capital market but also in other financial markets is the innovation of this research, which is done for thefirst time in Iran.
