development of a comprehensive model to predict stock prices in the stock market with an interpretive structural modeling approach

Predicting stock prices has long been a topic of interest for analysts and researchers. the aim of this study is to develop a comprehensive model for predicting stock prices in the tehran stock exchange using a combined approach of fuzzy delphi interpretive structural modeling with the use of technical, fundamental, macroeconomic, and emotional factors. in this study, first, using the fuzzy delphi method, 15 key criteria were identified from among 54 prediction criteria extracted from research literature according to investors’ perspectives. then, using the interpretive structural modeling approach, the relationships between them were examined and a hierarchical model was presented. based on the findings in the ism model, it is observed that the price is placed at the end of the hierarchy with high driving power, depending on earnings per share and cash flow index. the criteria that are placed at the bottom of the hierarchy are exchange rates and relative strength index and exponential moving average, which are the most influential indicators. this study is the first of its kind to identify stock price prediction criteria by considering all dimensions and developing hierarchical relationships between them using the ism approach.