发帖
雷达卡
The analysis of the financial market always draws a lot of attention
from investors and researchers. The trend of stock market is very complex and
is influenced by various factors. Therefore to find out the most significant factors
to the stock market is very important. Feature Selection is such an algorithm
that can remove the redundant and irrelevant factors, and figure out the
most significant subset of factors to build the analysis model. This paper analyzes
a series of technical indicators used in conventional studies of the stock
market and uses various feature selection algorithms, such as principal component
analysis, genetic algorithms, and sequential forward search, to find out the
most important indicators.
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