Title :
Applying induced aggregation operator in designing intelligent monitoring system for financial market
Author :
Fonooni, Benjamin ; Moghadam, Seied Javad Mousavi
Author_Institution :
Artificial Intell. Alternative Solutions Lab., Tehran
fDate :
March 30 2009-April 2 2009
Abstract :
Financial intelligent monitoring system is emerging new research area and also has great commercial potentials. Traditional technical analysis relies on some statistics including technical indicators to determine turning point of the trend. Despite the fact that financial markets conform to some mathematical concepts and cause it to be analyzed with different Artificial Intelligence (AI) algorithms, this paper headed for applying Induced Ordered Weighted Averaging (IOWA) operator in order to support trading decisions based on technical analysis in Foreign Exchange Market.
Keywords :
artificial intelligence; foreign exchange trading; monitoring; artificial intelligence algorithms; financial market; foreign exchange market; induced aggregation operator; induced ordered weighted averaging operator; intelligent monitoring system; Algorithm design and analysis; Artificial intelligence; Economic forecasting; Information analysis; Intelligent systems; Java; Monitoring; Open wireless architecture; Pattern analysis; State estimation;
Conference_Titel :
Computational Intelligence for Financial Engineering, 2009. CIFEr '09. IEEE Symposium on
Conference_Location :
Nashville, TN
Print_ISBN :
978-1-4244-2774-1
DOI :
10.1109/CIFER.2009.4937506
