| Summary: | 碩士 === 國立交通大學 === 資訊管理研究所 === 85 === To the investors and speculators in the uncertain stock market,
the most they desire to know is the analysis point of stock
volatility. However, the volatility is critically related to
profits and strategies of companies they invested. Therefore, if
we can further hold and make use of the financial reports of
individual industry to predict the future operation performance
which will become the basis of comparison and analysis.This
research is based on the neural network to control the behavior
mode of volatility rate under important financial index, and use
the volatility rate of financial index as a factor to verify if
the volatility is ahead of the financial reports announced.At
the same time, the research is also from the viewpoint of system
integration to combine the database with the outcome of behavior
mode described as above and apply to the internet under the
modified infrastructure of client-sever database and the World-
Wide-Web for the public to operate this analysis system and
access what they need.We attribute two consequences after
research 1、By the way of financial volatility rate this month
to learn the stock volatility rate this month, the hit rate is
the highest in predicting stock volatility. However, on the
other side, we get the lowest hit rate by this month to predict
next month. This result shows there is not much relativity
between share price and financial information after financial
reports announced. In other words, share prices have fluctuated
before financial reports announced.2、For the complex and fast-
updating environment under the client-server database system, we
use the communicators and publishers and subscribers to modify
the client-server infrastructure, not only to reduce the load of
core database, but also enhance the performance of system,
moreover, we can provide the more convenient and easier way for
system conversion and data exchange.
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