This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
2009 WRI World Congress on Computer Science and Information Engineering
A Computational Study on Window-Size Selection in Stock Market RILS Interval Forecasting
Los Angeles, California USA
March 31-April 02
ISBN: 978-0-7695-3507-4
The S & P 500 index is an important overall measurement of the stock market. Instead of using traditional point methods, He and Hu used rolling interval least squares(RILS) to forecast the annual variability of the index from 1940-2004 and obtained astonishing results [3] and [4]. They used a ten-year rolling window without detailed justification. In this study, we apply Fourier analysis to investigate if any periodical properties reside in the input data. Then, we try to apply such property, if any, in window size selection and to possibly improve the overall quality of the stock market annual interval forecasts. Our computational results indicate that the rolling window size used in [4] is fairly reasonable. In other words, it can produce overall comparable quality forecasts against the window size selected through Fourier analysis.
Citation:
Guanchen Chen, Chenyi Hu, "A Computational Study on Window-Size Selection in Stock Market RILS Interval Forecasting," csie, vol. 2, pp.297-301, 2009 WRI World Congress on Computer Science and Information Engineering, 2009
Usage of this product signifies your acceptance of the Terms of Use.