Research on Early Warning of China’s Energy Market Volatility Based on Self-Organizing Competitive Neural Networks

Ning Liu () and Jiaxin Wang ()
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Ning Liu: Hebei University of Science and Technology
Jiaxin Wang: Beijing Polytechnic

A chapter in LISS 2014, 2015, pp 1525-1529 from Springer

Abstract: Abstract This paper extracts seven indicators from energy production, per capita consumption and energy import and export trade in elements of energy market as the basic data for analyzing China’s energy market volatility. It establishes a self-organizing competitive neural networks model after normalizing the data, and then makes an empirical analysis of the volatility from year 1990 to 2009. It finds that the results of the model are in line with reality. It is significant to master the market rule and predict the energy market volatility.

Keywords: Neural networks; Energy market; Volatility; Early-warning (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-662-43871-8_219

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DOI: 10.1007/978-3-662-43871-8_219

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