Extracting trading information from the stock market to construct accurate forecasting models that filter signals and noise is a challenge. This research employs big data analytics to construct a computation platform for stock selection and trading strategies. It adopts elite particle swarm optimization (EPSO) to elucidate optimal trading opportunities and combines growing hierarchical self-organizing map (GHSOM) and EPSO in its stock selection strategy. EPSO–GHSOM distinguishes companies’ operating profitability, identifies price signals, and sets decision rules for buying and selling.
Mike Y. J. Lee,
EPSO-GHSOM Stock Selecting and Trading Strategy on Big Data, International Journal of Intelligent Information Systems.
Vol. 6, No. 2,
2017, pp. 7-20.
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