Financial time series prediction using polynomial pipelined neural networks

Expert Systems with Applications

Volumn 35, Issue 3, 2008, Pages 1186-1199

  Hussain, Abir Jaafar ^a   Knowles, Adam ^a   Lisboa, Paulo J G ^a   El Deredy, Wael ^b  

^a LIVERPOOL JOHN MOORES UNIVERSITY   (United Kingdom)

^b UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

Exchange rate time series; Financial time series prediction; Pipelined network; Polynomial neural network

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER NETWORKS; EXPERIMENTS; FORECASTING; IMAGE CLASSIFICATION; METROPOLITAN AREA NETWORKS; MICROFLUIDICS; NETWORK PROTOCOLS; POLYNOMIAL APPROXIMATION; POLYNOMIALS; SET THEORY; SIGNAL TO NOISE RATIO; TECHNOLOGY; TIME SERIES ANALYSIS; VEGETATION;

DIVIDE-AND-CONQUER (DAC); ELSEVIER (CO); EXCHANGE RATES; FINANCIAL TIME SERIES (FTS) PREDICTION; HIGHER ORDER; HIGHLY NONLINEAR; INPUT DATA; INPUT SIGNALS; NON STATIONARY; NON STATIONARY SIGNALS; NON-STATIONARY DATA; SIGNAL TO NOISE; US DOLLAR;

NEURAL NETWORKS;

EID: 44949210424     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2007.08.038     Document Type: Article

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