  Predicting the prices of stocks at any stock market remains a quest for many
investors and researchers. Those who trade at the stock market tend to use
technical, fundamental or time series analysis in their predictions. These
methods usually guide on trends and not the exact likely prices. It is for this
reason that Artificial Intelligence systems, such as Artificial Neural Network,
that is feedforward multi-layer perceptron with error backpropagation, can be
used for such predictions. A difficulty in neural network application is the
determination of suitable network parameters. A previous research by the author
already determined the network parameters as 5:21:21:1 with 80% training data
or 4-year of training data as a good enough model for stock prediction. This
model has been put to the test in predicting selected Shanghai Stock Exchange
stocks in the future period of 21-Sep-2016 to 11-Oct-2016, about one week after
the publication of these predictions. The research aims at confirming that
simple neural network systems can be quite powerful in typical stock market
predictions.
