Title :
An approach to mining financial markets through market state classification
Author :
Ionescu, Valeriu ; Dinsoreanu, Mihaela
Author_Institution :
Comput. Sci. Dept., Tech. Univ. of Cluj-Napoca, Cluj-Napoca, Romania
Abstract :
Financial markets have always been one of the most common application areas for a multitude of data mining techniques. Over the years a large number of autonomous prediction systems have been designed. In this paper an approach is proposed that offers a higher degree of control over the prediction process and over the exact market aspects that are being analyzed by the system. The concept can be applied to any trading strategy with the aim of enhancing forecasting accuracy. The paper also demonstrates how the theoretical concept can be applied in practice and concludes by illustrating the gains obtained by using the proposed approach.
Keywords :
data mining; stock markets; autonomous prediction systems; data mining techniques; financial markets; market state classification; trading strategy; Data mining; Feature extraction; Forecasting; Neural networks; Optimization; Silicon; Time series analysis; classification; data mining; financial markets; market state; time series;
Conference_Titel :
Intelligent Computer Communication and Processing (ICCP), 2013 IEEE International Conference on
Conference_Location :
Cluj-Napoca
Print_ISBN :
978-1-4799-1493-7
DOI :
10.1109/ICCP.2013.6646078