@article{(Open Science Index):https://publications.waset.org/pdf/15069,
	  title     = {Robust Regression and its Application in Financial Data Analysis},
	  author    = {Mansoor Momeni and  Mahmoud Dehghan Nayeri and  Ali Faal Ghayoumi and  Hoda Ghorbani},
	  country	= {},
	  institution	= {},
	  abstract     = {This research is aimed to describe the application of robust regression and its advantages over the least square regression method in analyzing financial data. To do this, relationship between earning per share, book value of equity per share and share price as price model and earning per share, annual change of earning per share and return of stock as return model is discussed using both robust and least square regressions, and finally the outcomes are compared. Comparing the results from the robust regression and the least square regression shows that the former can provide the possibility of a better and more realistic analysis owing to eliminating or reducing the contribution of outliers and influential data. Therefore, robust regression is recommended for getting more precise results in financial data analysis.
	    journal   = {International Journal of Economics and Management Engineering},
	  volume    = {4},
	  number    = {11},
	  year      = {2010},
	  pages     = {2173 - 2178},
	  ee        = {https://publications.waset.org/pdf/15069},
	  url   	= {https://publications.waset.org/vol/47},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 47, 2010},