Hong Kong Stock Markets Prediction Using Neural Networks: The Case of HENDERSON LAND Monthly Stock PriceTools Wang, Han (2016) Hong Kong Stock Markets Prediction Using Neural Networks: The Case of HENDERSON LAND Monthly Stock Price. [Dissertation (University of Nottingham only)]
AbstractOwing the fact that stock markets is accessible as a significant economic activity, predicting the stock price is considerably regarded.This study aims at evaluating the effectiveness of using ANN (artificial neural network) in predicting stock price movements. Technical and fundamental indicators were combined as the network inputs, the accurate rate of POCID (Prediction of Change in Direction) and mean profit were evaluated as the main performance indicators. HENDERSON LAND, traded in Hong Kong stock exchange, was used as a case study. The methodology presented could be adapted to other stocks. Data were achieved from Bloomberg, neural network was built by MATLAB.
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