Support vector regression with chaos-based firefly algorithm for stock market price forecasting

Support vector regression with chaos-based firefly algorithm for stock market price forecasting

Due to the inherent non-linearity and non-stationary characteristics of financial stock market price time series, conventional modeling techniques such as the Box–Jenkins autoregressive integrated moving average (ARIMA) are not adequate for stock market price forecasting. In this paper, a forecastin...

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Bibliographic Details
Main Authors: Kazem, A., Sharifi, E., Hussain, Farookh Khadeer, Saberi, Morteza, Hussain, Omar
Format: Journal Article
Published: Elsevier 2012
Subjects:
support vector regression
firefly algorithm
stock market price forecasting
chaotic mapping
Online Access:http://hdl.handle.net/20.500.11937/26170

Internet

http://hdl.handle.net/20.500.11937/26170

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