Reza Jamali - Accounting MA student, Yazd university, Faculty of Economics, Management andAccounting, Yazd, Iran,
Sayed Majid Ayat - Chemical engineering PhD candidate, Isfahan University of Technology, ChemicalEngineering group, Pardis College, Isfahan, Iran,

Predicting the future of financial markets, especially the future trend of stock market indicators, is one of the challenging topics of forecasting, which has faced the phenomenon of failure of predicting in forecasting models due to the occurrence of structural disruptions in these trends. In this article, the modeling approaches of stock return prediction as one of the main trends of the stock market, in the conditions of structural breaks, have been examined and the approaches based on which can be predicted in the atmosphere of deep uncertainty have been analyzed. Considering that the purpose of this article was to establish the context of past research and plan new areas for future research in stock market prediction modeling, therefore, the library study method was used. The obtained results show that the modeling approaches in the conditions of structural break are categorized into three main strategies; In the strategy of "creating limitations in the parameters of the model" with the help of the interpretation obtained from the theoretical frameworks of financial economics, the parameters of the model are corrected. In the "regime shift" strategy, breakpoints in the time series are modeled with the help of Markov chains. In "integrated forecasting", the state of the stock market is predicted by combining quantitative models with survey data. This study shows that for predicting the stock market of International Stock Exchange in the conditions of environmental uncertainties, the presented strategies can be a suitable field for future research.

Predicting methods, prediction failure, structural break, stock returns, financial market.