Financial markets: Very noisy information processing

被引：26
|
作者：
Magdon-Ismail, M [1 ]
Nicholson, A [1 ]
Abu-Mostafa, YS [1 ]
机构：
[1] CALTECH, Learning Syst Grp, Pasadena, CA 91125 USA
来源：
PROCEEDINGS OF THE IEEE | 1998年 / 86卷 / 11期
基金：
美国国家科学基金会;
关键词：
bounds; convergence; generalization error; learning; model limitation; noise; test error; volatility;
D O I：
10.1109/5.726786
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
We report new results about the impact of noise on information processing with application to financial markets. These results quantify the tradeoff between the amount of data and the noise level in the data. They also provide estimates for the performance of a learning system in terms of the noise level. We use these results to derive a method for detecting the change in market volatility from period to period. We successfully apply these results to the four major foreign exchange (FX) markets. The results hold for linear as well as nonlinear learning models and algorithms and for different noise models.
引用
收藏
页码：2184 / 2195
页数：12
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