Abstract:
The prediction of stock price crash risk is an important and widely studied topic in both
accounting and finance, since crash risk has a significant impact on shareholders, creditors,
managers, investors, and regulators. The aim of this research is to analyse Predicting factors
affecting the future stock price crash risk based on support vector machine. In this research
we study the data of 99 companies listed on the Tehran Stock Exchange (TSE) from 2011 to
2016.And since the Mean Absolute Error in the Testing Sample is less than Training, then
the model estimation is possible using the support vector machine method.
Machine summary:
Predicting factors affecting the future stock price crash risk based on support vector machine Mohammad Reza Razdar1, Ali Mohammad Zahmatkesh2, Sanaz Khaleh Oghlizadeh3 1Assistant Professor, Department of Accounting, Sanabad Golbahar Institute of Higher Education, Golbahar, Iran.
The aim of this research is to analyse Predicting factors affecting the future stock price crash risk based on support vector machine.
Therefore in this research, we Predicting factors affecting the future stock price crash risk By using support vector machine for the companies accepted in Tehran Stock Exchange during 2011- 2016.
Finally, the main research question in this case is whether predicting future stock price crash based on support vector machine is possible or not.
The aim of this study is to find the factors affecting the future stock price crash risk based on support vector machine (Ataei zadeh and Darabi, 2016).
3. Research History Ataei zadeh and Darabi (2016) In this study Predicting factors affecting the future stock price crash risk based on the Neural Network Based Radiological Basis Function of the listed companies in the Tehran Stock Exchange in years 2009 through 2015.
Findings of the research Predicting factors affecting future stock price crash risk is based on Neural network based Radial Basis Function is possible.
CFO : Operating cash flows In this study, the following research model is used to TAit 1 : Total assets of the firm estimate and predict factors affecting future stock price crash risk.
1, The aim of this research is to Predicting factors affecting the future stock price crash risk based on support vector machine.