| Summary: | 碩士 === 國立臺灣大學 === 電機工程學系研究所 === 86 === Recently , because the improvement of both theory in neural network and functi
on of personal computer , there are more and more examples using artificial in
telligent in financial market. Using artificial intelligent not only can help
us to deal with large information , but also can reduce the error caused by hu
man emotion. In this paper, we hope that we can use artificial intelligent in
Taiwan Stock Market from the aspect of market operation process. To use artifi
cial intelligent in financial market, we have to concern about two major
problems : (1)How to build the analysis model for the system ? and (2)What ki
nd of artificial intelligent we need ? In the first problem , we build our ana
lysis model based on characteristics of Taiwan Stock Market. In the second pro
blem, we use two kinds of neural network : Adaptive Resonance Theory Network(
ART-2) and Backpropagation Network (BPN) according to the analysis model we bu
ild. We also make some improvements to accelerate the operation of entire syst
em.In thispaper, we use the data of Taiwan Stock Market date from 1997.12.12 t
o 1998.5.8 as the input of system , and try to forecast the stock price trend
for ten stocks. In our simulation , we get better profit return than the raise
of Taiwan Stock Market Index.
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