عنوان مقاله [English]
نویسندگان [English]چکیده [English]
The purpose of study is to investigate comparative ability of accounting
information to predict indices volatility of companies listed in Tehran Stock
Exchange using intelligent methods including Support Vector Machine,
Artificial Neural Network and classic Logistic Regression model. Sample of
study includes 91 companies listed in Tehran Stock Exchange that have been
classified in 9 industrious groups during time period of 2003-3013.
Considering 11 corporate financial variables, study results show that despite
predicting ability of around 60% by Support Vector Machine and Artificial
Neural Network, there is significant difference between actual and predicted
results. Classic Logistic Regression model also can explain only 4%
industries’ indices volatility using selected 11 corporate financial variables.
Finally, although intelligent methods are superior to classic methods,
accounting information solely are not well-explainer variables for predicting
industry index volatility and variety of variables such as financial, political,
economical are effective in predicting industry index volatility.